Update site content to June 2026
· 4 hours ago
7c41291d81f28daa7a091dbfd1c07da60090e8d4
Parent:
7f943d9e6
Refresh multiple cheatsheets and dashboards with June 2026 updates: advance publication/modified dates and "Last verified" timestamps, adjust AGI outlook header and hardware projection (compute/energy), and add/refresh metadata (OG/twitter and JSON-LD). Major content updates in ai-frontier: model and leadership updates (OpenAI GPT-5 family and retirements, Gemini 3.5, Anthropic Claude Fable/Opus/Sonnet lineup and Series H funding, Meta Llama 4 + Muse Spark, Mistral financing/debt, DeepSeek first external round), pricing/availability notes, and SEO copy tweaks. Minor copy and timestamp edits across many pages (ai-progress-dashboard, ai-risk-timeline, aisafety, databases, post-quantum, postgres, privacy, prompt-builder, python-for-architects, tesla-products, versioncontrol, etc.) to reflect June 2026 status. Also includes small UI/copy clarifications in footers and dashboard caveats.
37 files changed +879 −562
- agi-development-guide.html +6 −5
- ai-frontier.html +153 −157
- ai-progress-dashboard.html +27 −23
- ai-risk-timeline.html +77 −5
- airisk.html +8 −5
- aisafety.html +4 −1
- automotive-innovation-timeline.html +51 −11
- aws-vs-azure.html +28 −28
- azure-devops.html +9 −6
- bitcoin-exchanges-cards.html +1 −1
- bitcoin-wallet.html +15 −14
- boom-supersonic.html +35 −15
- clean-architecture-dotnet.html +7 −7
- compression-algorithms.html +8 −6
- databases.html +4 −1
- dotnet-cheatsheet.html +17 −16
- future-of-warfare-technology.html +4 −3
- geoengineering-approaches.html +9 −8
- git-scm.html +2 −1
- google-ai-studio-guide.html +44 −32
- housing-comparison.html +5 −2
- humanoid-robots.html +76 −58
- javascript-for-architects.html +10 −10
- lifestyle-calculator.html +5 −1
- modern-devops-pipelines.html +8 −5
- modern-firearms.html +15 −6
- operator-loadouts.html +14 −7
- orbital-rockets-comparison.html +12 −9
- p-doom-calculator.html +6 −3
- post-quantum-cryptography.html +40 −3
- postgresql.html +3 −2
- privacy-data-broker-opt-out.html +15 −4
- prompt-builder.html +5 −4
- python-for-architects.html +84 −41
- safety_data.js +6 −6
- tesla-products.html +61 −52
- versioncontrol.html +5 −4
Diff
--- a/agi-development-guide.html +++ b/agi-development-guide.html @@ -33,7 +33,7 @@ "name": "David Veksler Cheatsheets" }, "datePublished": "2025-11-08", - "dateModified": "2025-11-08", + "dateModified": "2026-06-21", "keywords": "AGI development, recursive self-improvement, AI alignment spectrum, AI governance, hardware bottlenecks, geopolitical AI race, slow takeoff, accelerated takeoff" } </script> @@ -293,7 +293,7 @@ details li::marker { color: var(--text-muted); } <body> <header class="hero text-white"> <div class="hero-content text-center text-lg-start"> - <span class="badge bg-dark text-uppercase mb-3">AGI Outlook • 2025 edition</span> + <span class="badge bg-dark text-uppercase mb-3">AGI Outlook • 2026 edition</span> <h1 class="display-5 fw-bold">A Guide to the Development of Artificial General Intelligence</h1> <p class="lead text-light">Explore the interacting forces, extreme and incremental scenarios, alignment failure spectrum, and governance levers that define humanity's path toward Artificial General Intelligence. Designed for strategy workshops, policy reviews, and research roadmaps.</p> <div class="hero-actions"> @@ -342,7 +342,7 @@ details li::marker { color: var(--text-muted); } <p class="section-title">Part 1</p> <h2 class="mb-2">Four Core Dynamics of AGI Development</h2> </div> - <div class="chip"><i class="bi bi-clock-history"></i> Updated 2025-11-08</div> + <div class="chip"><i class="bi bi-clock-history"></i> Updated 2026-06-21</div> </div> <p class="text-muted">Every forecast downstream of AGI inherits these pressures. Use them as the "compass" for evaluating new breakthroughs or policy moves.</p> <div class="force-grid"> @@ -359,7 +359,7 @@ details li::marker { color: var(--text-muted); } <article class="force-card"> <span>Force 02</span> <h3 class="mt-2">Hardware & Resource Bottlenecks</h3> - <p>Compute availability, energy draw (~60GW projections), and high-quality data govern how far any roadmap can scale. Synthetic data and power buildouts are now core research bets.</p> + <p>Compute availability, energy draw (~100GW of new capacity projected by 2030, per IEA), and high-quality data govern how far any roadmap can scale. Synthetic data and power buildouts are now core research bets.</p> <div class="tag-row"> <span>GPUs</span> <span>Power grids</span> @@ -699,8 +699,9 @@ paceSlider.addEventListener('input', () => { </a> </div> <p class="mb-2"> - © 2025 David Veksler · Compiled & expanded based on academic papers, industry reports, and AI safety research organizations. + © 2026 David Veksler · Compiled & expanded based on academic papers, industry reports, and AI safety research organizations. </p> + <p class="mb-2 small text-muted">Last verified: 2026-06-21</p> <div> <a class="mx-2 link-secondary" href="https://www.linkedin.com/in/davidveksler/" target="_blank" title="David Veksler on LinkedIn"> <i class="bi bi-linkedin"></i> --- a/ai-frontier.html +++ b/ai-frontier.html @@ -4,24 +4,24 @@ <meta charset="utf-8"/> <meta content="width=device-width, initial-scale=1.0" name="viewport"/> <title> - AI Frontier Model Builders Cheatsheet (Updated May 2026) + AI Frontier Model Builders Cheatsheet (Updated June 2026) </title> <link href="data:image/svg+xml,<svg xmlns=%22http://www.w3.org/2000/svg%22 viewBox=%220 0 100 100%22><text y=%22.9em%22 font-size=%2290%22>🤖</text></svg>" rel="icon"/> <!-- SEO Meta Description --> - <meta content="A comprehensive cheatsheet for understanding major AI companies building frontier models: OpenAI, Google DeepMind, Anthropic, Meta AI, Mistral AI, xAI, and DeepSeek. Covers their philosophy, origin, approach, AGI goals, key products, funding, and recent developments as of May 2026." name="description"/> - <meta content="AI, Artificial Intelligence, Frontier Models, LLM, AGI, ASI, OpenAI, Google DeepMind, Anthropic, Meta AI, Mistral AI, xAI, DeepSeek, GPT, Gemini, Claude, Llama, Grok, AI Products, AI Companies, AI Research, AI Safety, May 2026" name="keywords"/> + <meta content="A comprehensive cheatsheet for understanding major AI companies building frontier models: OpenAI, Google DeepMind, Anthropic, Meta AI, Mistral AI, xAI, and DeepSeek. Covers their philosophy, origin, approach, AGI goals, key products, funding, and recent developments as of June 2026." name="description"/> + <meta content="AI, Artificial Intelligence, Frontier Models, LLM, AGI, ASI, OpenAI, Google DeepMind, Anthropic, Meta AI, Mistral AI, xAI, DeepSeek, GPT, Gemini, Claude, Llama, Grok, AI Products, AI Companies, AI Research, AI Safety, June 2026" name="keywords"/> <!-- Canonical URL (Update if hosted) --> <link href="https://cheatsheets.davidveksler.com/ai-frontier.html" rel="canonical"/> <!-- Social Media Metadata (Add URLs if needed) --> - <meta content="AI Frontier Model Builders Cheatsheet (May 2026 Update)" property="og:title"/> - <meta content="Explore the philosophies, origins, approaches, key products, and AGI/ASI goals of leading AI companies like OpenAI, Google DeepMind, Anthropic, Meta AI, Mistral AI, xAI, and DeepSeek. Updated May 2026." property="og:description"> + <meta content="AI Frontier Model Builders Cheatsheet (June 2026 Update)" property="og:title"/> + <meta content="Explore the philosophies, origins, approaches, key products, and AGI/ASI goals of leading AI companies like OpenAI, Google DeepMind, Anthropic, Meta AI, Mistral AI, xAI, and DeepSeek. Updated June 2026." property="og:description"> <meta content="website" property="og:type"/> <meta content="https://cheatsheets.davidveksler.com/ai-frontier.html" property="og:url"/> <!-- Ensure this image exists and is relevant --> <meta content="AI Frontier Model Builders Cheatsheet - Logos of Major AI Companies" property="og:image:alt"/> <meta content="summary_large_image" name="twitter:card"/> - <meta content="AI Frontier Model Builders Cheatsheet (May 2026 Update)" name="twitter:title"/> - <meta content="Explore the philosophies, origins, approaches, key products, and AGI/ASI goals of leading AI companies like OpenAI, Google DeepMind, Anthropic, Meta AI, Mistral AI, xAI, and DeepSeek. Updated May 2026." name="twitter:description"/> + <meta content="AI Frontier Model Builders Cheatsheet (June 2026 Update)" name="twitter:title"/> + <meta content="Explore the philosophies, origins, approaches, key products, and AGI/ASI goals of leading AI companies like OpenAI, Google DeepMind, Anthropic, Meta AI, Mistral AI, xAI, and DeepSeek. Updated June 2026." name="twitter:description"/> <!-- Ensure this image exists and is relevant --> <meta content="AI Frontier Model Builders Cheatsheet - Logos of Major AI Companies" name="twitter:image:alt"/> <link href="https://cdn.jsdelivr.net/npm/[email protected]/dist/css/bootstrap.min.css" rel="stylesheet"/> @@ -464,6 +464,19 @@ </meta> <meta content="images/ai-frontiers.png" property="og:image"/> <meta content="images/ai-frontiers.png" name="twitter:image"/> + <script type="application/ld+json"> + { + "@context": "https://schema.org", + "@type": "TechArticle", + "headline": "AI Frontier Model Builders Cheatsheet (June 2026 Update)", + "description": "A comprehensive cheatsheet for understanding major AI companies building frontier models: OpenAI, Google DeepMind, Anthropic, Meta AI, Mistral AI, xAI, and DeepSeek. Covers their philosophy, origin, approach, AGI goals, key products, funding, and recent developments as of June 2026.", + "author": {"@type": "Person", "name": "David Veksler (AI Generated)"}, + "publisher": {"@type": "Organization", "name": "David Veksler Cheatsheets"}, + "datePublished": "2025-01-01", + "dateModified": "2026-06-21", + "keywords": "AI, Artificial Intelligence, Frontier Models, LLM, AGI, ASI, OpenAI, Google DeepMind, Anthropic, Meta AI, Mistral AI, xAI, DeepSeek, GPT, Gemini, Claude, Llama, Grok" + } + </script> </head> <body> <header class="page-header"> @@ -476,7 +489,7 @@ A cheatsheet exploring major companies developing advanced AI, their philosophies, key products, funding, recent developments, and AGI approaches. </p> <p class="last-updated"> - Last Updated: May 2026 + Last Updated: June 2026 </p> </header> <div class="container" id="main-container"> @@ -519,7 +532,7 @@ <strong> Flagship Models: </strong> - GPT series (GPT-4, GPT-4o, GPT-4.1, GPT-4.1 mini/nano), DALL-E 3, Sora, Whisper, o-series (o1, o3, o3-mini), Deep Research. [1, 11] + GPT-5.5 (April 2026 flagship), GPT-5.4, GPT-5 family; DALL-E 3, Sora, Whisper, o-series (o3, o4-mini), Deep Research. Earlier GPT-4 family and o1 have been retired. [1, 11] </li> <li> <strong> @@ -688,7 +701,7 @@ </h5> <div class="card-content-wrapper"> <p class="summary"> - Led by CEO Sam Altman, President Greg Brockman, and CTO Mira Murati. [16] The board of the non-profit OpenAI, Inc. is chaired by Bret Taylor. Recent appointments include Fidji Simo as CEO of Applications (May 2025). [1, 15] + Led by CEO Sam Altman and President Greg Brockman. [16] Mira Murati departed as CTO in September 2024; Mark Chen leads research as SVP of Research. The board of the non-profit OpenAI, Inc. is chaired by Bret Taylor. Fidji Simo serves as CEO of Applications (from 2025). [1, 15] </p> <button aria-expanded="false" class="btn btn-sm details-toggle" data-bs-target="#collapseOpenAILeadership" data-bs-toggle="collapse" type="button"> Details @@ -699,7 +712,7 @@ </div> <div class="collapse collapse-content" id="collapseOpenAILeadership"> <h6> - Key Figures (as of May 2025) + Key Figures (as of June 2026) </h6> <ul> <li> @@ -716,9 +729,9 @@ </li> <li> <strong> - Mira Murati: + Mark Chen: </strong> - Chief Technology Officer (CTO). [16] + SVP of Research, leading the research organization after Mira Murati's departure (September 2024). [13] </li> <li> <strong> @@ -736,13 +749,7 @@ <strong> Fidji Simo: </strong> - CEO of Applications (joining later in 2025). [15] - </li> - <li> - <strong> - Mark Chen: - </strong> - Chief Research Officer. [13] + CEO of Applications. [15] </li> <li> <strong> @@ -757,7 +764,7 @@ Chairman of the Board of Directors (OpenAI, Inc. nonprofit). [1] </li> <li> - Former NSA Director Paul Nakasone joined the board in June 2024. + Former NSA Director Paul Nakasone joined the board in June 2024. Mira Murati (former CTO) departed September 2024 to found Thinking Machines Lab. </li> </ul> <p> @@ -777,7 +784,7 @@ </h5> <div class="card-content-wrapper"> <p class="summary"> - Known for the GPT series (GPT-4, GPT-4o, GPT-4.1), DALL-E 3 (image generation), Sora (text-to-video), Whisper (speech-to-text), and reasoning-focused models like the o-series (o1, o3, o3-mini) and Deep Research. [1] Products include + Known for the GPT-5 family (GPT-5.4 March 2026, GPT-5.5 April 2026 flagship), DALL-E 3 (image generation), Sora (text-to-video), Whisper (speech-to-text), and reasoning-focused o-series models (o3, o4-mini), and Deep Research. Earlier GPT-4 family and o1 have been retired. [1] Products include <a href="https://chat.openai.com" rel="noopener noreferrer" target="_blank"> ChatGPT </a> @@ -801,40 +808,29 @@ <ul> <li> <strong> - GPT (Generative Pre-trained Transformer) Series: + GPT-5 Family (2026 flagship line): </strong> <ul> <li> <code> - GPT-3.5 + GPT-5.4 </code> - : Powers many applications and the free version of ChatGPT. + : Released March 2026; 1M-token context window, native computer-use capabilities. </li> <li> <code> - GPT-4 + GPT-5.5 </code> - : Highly capable model with strong reasoning, creativity, and multimodal input (text, image). + : Current flagship, released April 23, 2026. Described as OpenAI's "smartest and most intuitive" model, optimized for complex agentic tasks and multi-step tool-using workflows. Available in ChatGPT (Plus/Pro/Team/Enterprise) and the API. [1, 11] </li> <li> <code> - GPT-4o ("omni") + GPT-5.5 Instant </code> - : Flagship multimodal model (text, audio, vision) announced May 2024, known for enhanced speed, cost-effectiveness, and interactive capabilities. [11] + : Lighter variant released May 2026, became the default model for free ChatGPT users, replacing GPT-5.3 Instant. </li> <li> - <code> - GPT-4.1 - </code> - , - <code> - GPT-4.1 mini - </code> - , - <code> - GPT-4.1 nano - </code> - : Newer iterations released in April 2025, offering varied performance and efficiency. [1] + Note: The entire pre-GPT-5 model family (GPT-4, GPT-4o, GPT-4.1) has been retired. </li> </ul> </li> @@ -843,21 +839,15 @@ o-Series (Reasoning Models): </strong> <ul> - <li> - <code> - o1 - </code> - : Focused on enhanced reasoning capabilities. [11] - </li> <li> <code> o3 </code> & <code> - o3-mini + o4-mini </code> - : Successors to o1, with further improvements in reasoning and problem-solving, released to paid users in April 2025. [1] + : Advanced reasoning models; o4-mini has been retired from ChatGPT but reasoning capabilities are integrated into the GPT-5.x line. [1] </li> </ul> </li> @@ -1050,7 +1040,7 @@ </h5> <div class="card-content-wrapper"> <p class="summary"> - Launched GPT-4o, GPT-4.1 series, and o3 reasoning models. [1, 11] Expanded Sora video model access. Announced new Responses API and Agents SDK. Key partnership with Apple for Apple Intelligence. Record $122B funding round at an ~$852B valuation in March 2026. Leadership team expanded. Stay updated via their + Launched GPT-5 family: GPT-5.4 (March 2026) and GPT-5.5 (April 2026, current flagship). Entire pre-GPT-5 model family retired. [1, 11] Closed record $122B funding round at an ~$852B valuation (March 2026). CTO Mira Murati departed September 2024. Stay updated via their <a href="https://openai.com/blog" rel="noopener noreferrer" target="_blank"> blog </a> @@ -1072,13 +1062,13 @@ <strong> Model Releases & Enhancements: </strong> - GPT-4o (May 2024) as new flagship multimodal model. [11] Sora text-to-video model access expanded. Reasoning models o1, o3, and o3-mini released/previewed. [1, 11] GPT-4.1, GPT-4.1 mini, and GPT-4.1 nano launched (April 2025). [1] Deep Research agent unveiled (Feb 2025). [1] + GPT-5.4 launched March 2026 with a 1M-token context and native computer-use. GPT-5.5 launched April 23, 2026 as the current flagship, with GPT-5.5 Instant available free from May 2026. The entire pre-GPT-5 model family (GPT-4, GPT-4o, GPT-4.1, o1) has been retired. Sora text-to-video model access expanded. Deep Research agent (Feb 2025) and Responses API / Agents SDK (March 2025) remain available. [1, 11] </li> <li> <strong> Developer Tools: </strong> - New Responses API and Agents SDK announced (March 2025) to aid in building AI agents. + Responses API and Agents SDK (announced March 2025) for building AI agents; GPT-5.5 and GPT-5.5 Pro available in the API from April 24, 2026. </li> <li> <strong> @@ -1090,13 +1080,13 @@ <strong> Funding & Corporate: </strong> - Closed a record $122 billion funding round at an ~$852 billion post-money valuation (March 2026), following the $40 billion / $300 billion round of April 2025. Growing IPO speculation points toward a possible 2027 listing. [14] + Closed a record $122 billion funding round at an ~$852 billion post-money valuation (March 31, 2026), anchored by Amazon ($50B), Nvidia ($30B), and SoftBank ($30B), following the $40 billion / $300 billion round (April 2025). IPO speculation points toward a possible 2027 listing. [14] </li> <li> <strong> Leadership & Board: </strong> - Fidji Simo announced as CEO of Applications (May 2025). [15] Former NSA Director Paul Nakasone joined the Board of Directors (June 2024). Other leadership roles expanded (March 2025). [13] + CTO Mira Murati departed September 2024; Mark Chen became SVP of Research. Fidji Simo serves as CEO of Applications (from 2025). [15] Former NSA Director Paul Nakasone joined the Board of Directors (June 2024). [13] </li> <li> <strong> @@ -1154,7 +1144,7 @@ <strong> Flagship Models: </strong> - Gemini family (e.g., Gemini 2.0 Flash, 1.5 Pro, Ultra, Nano), Gemma (open models), Veo (video). [2, 41] + Gemini 3.5 family (Gemini 3.5 Flash launched May 2026 at Google I/O; Gemini 3.5 Pro arriving June 2026), Gemini 3.1 Pro, Gemma (open models), Veo (video). [2, 41] </li> <li> <strong> @@ -1364,7 +1354,7 @@ </h5> <div class="card-content-wrapper"> <p class="summary"> - Leading with the Gemini family of multimodal models (e.g., Gemini 2.0 Flash, 1.5 Pro for long context, Ultra, Nano). [41] Also offers Gemma open models. [2] Renowned for AlphaFold (biology), AlphaGo/AlphaZero (games), Imagen (image generation), Veo (video generation), and Lyria (music generation). [2, 28] Explore more at + Leading with the Gemini 3.5 family (Gemini 3.5 Flash launched May 2026 at Google I/O; strongest agentic/coding model; Gemini 3.5 Pro arriving June 2026 with 2M-token context). Also Gemini 3.1 Pro and Gemma open models. [2, 41] Renowned for AlphaFold (biology), AlphaGo/AlphaZero (games), Imagen (image generation), Veo (video generation), and Lyria (music generation). [2, 28] Explore more at <a href="https://deepmind.google/technologies/" rel="noopener noreferrer" target="_blank"> Google DeepMind Technologies </a> @@ -1384,36 +1374,30 @@ <ul> <li> <strong> - Gemini: + Gemini 3.5 (current flagship family, as of June 2026): </strong> Google DeepMind's most capable and general multimodal model family, designed for text, code, image, audio, and video understanding and generation. <ul> <li> <code> - Gemini 2.0 Flash (experimental) + Gemini 3.5 Flash </code> - : Latest iteration (Dec 2024) focusing on low latency and enhanced performance for agentic capabilities. [41] + : Launched May 19, 2026 at Google I/O. Strongest agentic and coding model; outperforms Gemini 3.1 Pro on key benchmarks; 1M-token context; ~4× faster than comparable frontier models at inference. [41] </li> <li> <code> - Gemini 1.5 Pro + Gemini 3.5 Pro </code> - : Known for its state-of-the-art performance and very long context window (e.g., up to 1 million tokens). + : Arriving June 2026; 2M-token context (largest of any production frontier model); wins on extreme reasoning and long contexts. Already used internally by Google. </li> <li> <code> - Gemini Ultra + Gemini 3.1 Pro </code> - : The largest and most capable model for highly complex tasks. + : Previous flagship for complex reasoning tasks; still available. </li> <li> - <code> - Gemini Nano - </code> - : Efficient model designed for on-device tasks. - </li> - <li> - Powers features in Google Search, Gemini App (formerly Bard), Google Cloud AI (Vertex AI), Android, and experimental products like Project Astra. [41] + Powers features in Google Search, Gemini App, Google Cloud AI (Vertex AI), Android, and Project Astra. [41] </li> </ul> </li> @@ -1603,11 +1587,11 @@ <h5> <i class="bi bi-newspaper"> </i> - Recent Developments (2024-2025) + Recent Developments (2024-2026) </h5> <div class="card-content-wrapper"> <p class="summary"> - Release of Gemini 2.0 Flash (experimental, Dec 2024) focusing on agentic capabilities. [41] Ongoing advancements with Gemini 1.5 Pro and its long context window. Project Astra (universal AI assistant) showcased. [40, 41] Demis Hassabis awarded Nobel Prize for AlphaFold. [2] Continued release of Gemma open models. Release of Veo 2 (Dec 2024) and Lyria (preview). [2] + Launched Gemini 3.5 Flash at Google I/O (May 2026) — strongest agentic/coding model, 1M-token context, 4× faster inference. Gemini 3.5 Pro (2M-token context) expected June 2026. Demis Hassabis awarded Nobel Prize in Chemistry (2024) for AlphaFold. [2] Continued Gemma open model releases. Veo 2 (Dec 2024) and Lyria music generation. [2, 41] </p> <button aria-expanded="false" class="btn btn-sm details-toggle" data-bs-target="#collapseDeepMindDevelopments" data-bs-toggle="collapse" type="button"> Details @@ -1625,7 +1609,7 @@ <strong> Gemini Model Suite Evolution: </strong> - Introduction of Gemini 2.0 Flash (experimental) in December 2024, geared towards agentic AI experiences in games and other domains. [41] Continued enhancements and integration of Gemini 1.5 Pro and other variants across Google products and Vertex AI. + Gemini 3.5 Flash launched at Google I/O on May 19, 2026 — outperforms Gemini 3.1 Pro on coding and agentic benchmarks, with a 1M-token context window and ~4× faster inference than comparable frontier models. [41] Gemini 3.5 Pro (2M-token context, June 2026) used internally by Google ahead of GA release. Gemini 2.0 Flash (Dec 2024) was the prior agentic flagship. Gemini 3.1 Pro remains available for complex reasoning. </li> <li> <strong> @@ -1708,13 +1692,13 @@ <strong> Valuation: </strong> - $380 billion post-money valuation after a $30 billion Series G (February 2026), with reports of a new raise at $850–900+ billion in talks (May 2026). Up from $183 billion (September 2025) and $61.5 billion (May 2025). + ~$965 billion post-money after a $65 billion Series H (May 28, 2026), making Anthropic the most highly valued AI startup. Up from $380 billion (Series G, February 2026), $183 billion (September 2025), and $61.5 billion (May 2025). </li> <li> <strong> Flagship Models: </strong> - Claude 3 family (Opus, Sonnet, Haiku), Claude 3.5 Sonnet. + Claude Fable 5 (June 2026, top tier; 1M-token context, always-on adaptive thinking), Claude Opus 4.8 (May 2026), Claude Sonnet 4.6 (February 2026), Claude Haiku 4.5. </li> <li> <strong> @@ -1905,7 +1889,7 @@ </h5> <div class="card-content-wrapper"> <p class="summary"> - The Claude family of large language models is Anthropic's flagship offering. This includes the Claude 3 series (Opus, Sonnet, Haiku) and the newer Claude 3.5 Sonnet (released June 2024). These models are known for strong performance, long context windows, and safety features. Products include the + The Claude family of large language models is Anthropic's flagship offering. The current lineup (as of June 2026): Claude Fable 5 (top tier, June 2026; 1M-token context, 128K output, always-on adaptive thinking), Claude Opus 4.8 (May 2026; complex reasoning, long-horizon agentic coding), Claude Sonnet 4.6 (February 2026), and Claude Haiku 4.5. These models are known for strong performance, long context windows, and safety features. Products include the <a href="https://claude.ai" rel="noopener noreferrer" target="_blank"> Claude.ai </a> @@ -1929,38 +1913,27 @@ <ul> <li> <strong> - Claude 3 Series (Released March 2024): + Claude Fable 5 (Released June 9, 2026): </strong> - A suite of models offering different balances of intelligence, speed, and cost. - <ul> - <li> - <code> - Claude 3 Opus - </code> - : Most powerful model, excelling at highly complex tasks, analysis, and R&D, often outperforming other leading models on benchmarks. - </li> - <li> - <code> - Claude 3 Sonnet - </code> - : Balanced model ideal for enterprise workloads, data processing, and scaled AI deployments, offering strong performance with greater speed than Opus. - </li> - <li> - <code> - Claude 3 Haiku - </code> - : Fastest and most compact model, designed for near-instant responsiveness, customer interactions, and content moderation. - </li> - <li> - Key features include advanced reasoning, improved vision capabilities (multimodal), very long context windows (200K tokens standard, with some research indicating capabilities up to 1M+ tokens), and reduced rates of hallucination. - </li> - </ul> + Anthropic's most capable widely released model. First Mythos-class model made generally available. Features always-on adaptive thinking, a 1M-token context window, and 128K output tokens. State-of-the-art results on nearly all tested benchmarks. Priced at $10 input / $50 output per million tokens. Available on Claude API, Amazon Bedrock, Google Cloud Vertex AI, and Microsoft Azure Foundry. + </li> + <li> + <strong> + Claude Opus 4.8 (Released May 2026): + </strong> + Strongest Opus-tier model; excels at complex reasoning, long-horizon agentic coding, and high-autonomy tasks. Priced at $5 input / $25 output per million tokens. </li> <li> <strong> - Claude 3.5 Sonnet (Released June 2024): + Claude Sonnet 4.6 (Released February 2026): </strong> - The first model in the Claude 3.5 generation, positioned as significantly faster and more cost-effective than Claude 3 Opus, with graduate-level reasoning, strong vision capabilities, and new features like "Artifacts" for interactive content generation in the Claude.ai workspace. + Balanced speed and capability; the model Claude.ai uses for Pro subscribers. Priced at $3 input / $15 output per million tokens. + </li> + <li> + <strong> + Claude Haiku 4.5: + </strong> + Fastest and most cost-effective model ($1 input / $5 output per million tokens), suited for high-throughput, latency-sensitive applications. </li> </ul> <h6> @@ -2067,7 +2040,7 @@ </h5> <div class="card-content-wrapper"> <p class="summary"> - Anthropic has secured tens of billions in funding and commitments from major tech companies like Google and Amazon, as well as venture capital firms. A $30 billion Series G in February 2026 set a $380 billion post-money valuation, with reports of a further raise in talks at $850–900+ billion (May 2026). + Anthropic has secured tens of billions in funding from Google, Amazon, and major venture firms. A $30 billion Series G (February 2026) set a $380 billion valuation. A $65 billion Series H (May 28, 2026) set a $965 billion post-money valuation — surpassing OpenAI and potentially Anthropic's final private raise before IPO. Run-rate revenue crossed $47 billion by Series H. </p> <button aria-expanded="false" class="btn btn-sm details-toggle" data-bs-target="#collapseAnthropicFunding" data-bs-toggle="collapse" type="button"> Details @@ -2109,13 +2082,13 @@ <strong> Total Funding Secured: </strong> - Cumulative funding has grown into the tens of billions, including a $30 billion Series G in February 2026. Anthropic reported crossing a $30 billion annualized revenue run rate in early 2026. + Cumulative equity and committed funding has grown into the hundreds of billions, including a $30 billion Series G (February 2026) and a $65 billion Series H (May 28, 2026). Run-rate revenue was $14 billion at Series G and crossed $47 billion by Series H. </li> <li> <strong> Valuation Trajectory: </strong> - Climbed from $15–18.4 billion (late 2023/early 2024) to $61.5 billion (May 2025), $183 billion (Series F, September 2025), and $380 billion (Series G, February 2026). A new round at $850–900+ billion was reported in talks (May 2026). + Climbed from $15–18.4 billion (late 2023/early 2024) to $61.5 billion (May 2025), $183 billion (Series F, September 2025), $380 billion (Series G, February 2026), and $965 billion (Series H, May 28, 2026). At $965 billion, Anthropic briefly surpassed OpenAI as the most highly valued AI startup. Series H led by Altimeter Capital, Dragoneer, Greenoaks, and Sequoia Capital; likely the final private round before IPO. </li> </ul> </div> @@ -2131,7 +2104,7 @@ </h5> <div class="card-content-wrapper"> <p class="summary"> - Launched the Claude 3 model family (Opus, Sonnet, Haiku) in March 2024. Released Claude 3.5 Sonnet in June 2024 with enhanced capabilities and the "Artifacts" feature. Rapid enterprise adoption pushed revenue past a $30B run rate. Closed a $30B Series G at a $380B valuation (February 2026). Check their + Launched Claude Sonnet 4.6 (February 2026), Opus 4.8 (May 2026), and Fable 5 (June 9, 2026 — top tier, 1M-token context). Closed $30B Series G at $380B (February 2026) and $65B Series H at $965B (May 28, 2026), making Anthropic the most highly valued AI startup. Run-rate revenue crossed $47B. Check their <a href="https://www.anthropic.com/news" rel="noopener noreferrer" target="_blank"> news page </a> @@ -2151,49 +2124,55 @@ <ul> <li> <strong> - Claude 3 Model Family (March 2024): + Claude Sonnet 4.6 (February 2026): </strong> - Introduction of Opus, Sonnet, and Haiku, which set new industry benchmarks for intelligence, speed, vision capabilities, and context window length. + Full upgrade across coding, computer use, long-context reasoning, agent planning, knowledge work, and design. Powers Claude.ai for Pro subscribers. </li> <li> <strong> - Claude 3.5 Sonnet (June 2024): + Claude Opus 4.8 (May 2026): </strong> - Launch of the first model in the Claude 3.5 generation. It offers superior intelligence to Claude 3 Opus at twice the speed, with strong vision understanding and a new "Artifacts" feature in Claude.ai for interactive content creation and editing. + Strongest Opus-tier model; complex reasoning and long-horizon agentic coding with high autonomy. $5/$25 per million input/output tokens. </li> <li> <strong> - Enterprise Expansion & Cloud Availability: + Claude Fable 5 (June 9, 2026): </strong> - Focused on increasing enterprise adoption through direct API access and partnerships with major cloud providers like AWS, Google Cloud, and Microsoft Azure. + First Mythos-class model released publicly. Always-on adaptive thinking, 1M-token context window, 128K output tokens. State-of-the-art on nearly all benchmarks. $10/$50 per million input/output tokens. Available on Claude API, Amazon Bedrock, Google Cloud Vertex AI, and Microsoft Azure Foundry. </li> <li> <strong> - Responsible Scaling Policy (RSP) Updates: + Series H Funding (May 28, 2026): </strong> - Continued commitment and updates to their RSP, detailing safety levels and procedures for developing more advanced AI. + Raised $65 billion at a $965 billion post-money valuation, led by Altimeter Capital, Dragoneer, Greenoaks, and Sequoia Capital. Surpassed OpenAI as most highly valued AI startup. Run-rate revenue crossed $47 billion. Likely Anthropic's final private fundraise before IPO. </li> <li> <strong> - Research Publications: + Series G Funding (February 2026): </strong> - Ongoing release of influential research papers on AI safety, interpretability (e.g., dictionary learning for discovering features in models), and model capabilities, available at - <a href="https://www.anthropic.com/research" rel="noopener noreferrer" target="_blank"> - anthropic.com/research - </a> - . + Raised $30 billion at a $380 billion post-money valuation, with run-rate revenue of $14 billion at that time. </li> <li> <strong> - Valuation Growth: + Enterprise Expansion & Cloud Availability: </strong> - Valuation rose from $61.5 billion (May 2025) to $183 billion (September 2025) and $380 billion after the February 2026 Series G, with a larger round reported in talks. + Deep partnerships with AWS (primary cloud), Google Cloud Vertex AI, and Microsoft Azure Foundry for enterprise model access. </li> <li> <strong> - Claude Pro and Team Plans: + Responsible Scaling Policy (RSP) Updates: </strong> - Introduced subscription plans for Claude.ai offering higher usage limits and access to the latest models. + Continued commitment and updates to their RSP, detailing safety levels and procedures for developing more advanced AI. + </li> + <li> + <strong> + Research Publications: + </strong> + Ongoing release of influential research papers on AI safety, interpretability, and model capabilities at + <a href="https://www.anthropic.com/research" rel="noopener noreferrer" target="_blank"> + anthropic.com/research + </a> + . </li> </ul> </div> @@ -2245,7 +2224,7 @@ <strong> Flagship Models: </strong> - Llama family (Llama 2, Llama 3, Llama 3.1), Segment Anything Model (SAM), Seamless Communication models (SeamlessM4T v2, SeamlessExpressive), Code Llama. + Llama 4 family (Scout, Maverick — April 2025; Behemoth in training), Llama 3.1, Segment Anything Model (SAM), Seamless Communication models (SeamlessM4T v2), Code Llama. Note: Meta Superintelligence Labs released Muse Spark (April 2026), Meta's first proprietary closed-weight model. </li> <li> <strong> @@ -2442,15 +2421,11 @@ </h5> <div class="card-content-wrapper"> <p class="summary"> - The Llama family (Llama 2, - <a href="https://llama.meta.com/" rel="noopener noreferrer" target="_blank"> - Llama 3 - </a> - , Llama 3.1) of open-weight LLMs are flagship models. [37] Other notable technologies include the Segment Anything Model (SAM) for vision, Seamless Communication models for translation, Code Llama, and the widely adopted + The Llama 4 family (Scout and Maverick, April 2025; Behemoth still in training) uses Mixture-of-Experts (MoE) architecture and is natively multimodal. [37] Llama 4 Scout has a 10M-token context window — the largest of any open model at launch. Also notable: Segment Anything Model (SAM), Seamless Communication models, Code Llama, and the widely adopted <a href="https://pytorch.org/" rel="noopener noreferrer" target="_blank"> PyTorch </a> - framework. Key product is the Meta AI assistant. [36, 37] + framework. Meta Superintelligence Labs released Muse Spark (April 2026) as Meta's first proprietary closed-weight model. Key product is the Meta AI assistant. [36, 37] </p> <button aria-expanded="false" class="btn btn-sm details-toggle" data-bs-target="#collapseMetaModels" data-bs-toggle="collapse" type="button"> Details @@ -2466,30 +2441,36 @@ <ul> <li> <strong> - Llama (Large Language Model Meta AI) Series: + Llama 4 Series (Released April 5, 2025): </strong> - A family of open-source (or "openly available") large language models released with weights and code, available in various sizes (e.g., 8B, 70B, 400B+ parameters for Llama 3.1). + Meta's first model family to use Mixture-of-Experts (MoE) architecture; natively multimodal (text, image, video). <ul> <li> <code> - Llama 2 + Llama 4 Scout </code> - : Widely adopted open model. + : 17B active parameters, 16 experts; industry-leading 10M-token context window at launch; fits in a single NVIDIA H100 GPU. Best-in-class multimodal open model in its size tier. </li> <li> <code> - Llama 3 + Llama 4 Maverick </code> - (Released April 2024): Showed significant improvements in performance and capabilities. [37] + : 17B active parameters, 128 experts; outperforms GPT-4o and Gemini 2.0 Flash on coding, reasoning, multilingual, and image benchmarks per Meta's benchmarks. </li> <li> <code> - Llama 3.1 + Llama 4 Behemoth </code> - (Released July 2024): Further improvements, including larger model sizes and enhanced coding and reasoning. + : ~288B active parameters, ~2 trillion total parameters; still in training as of June 2026. Designed as a "teacher model" for Scout and Maverick via codistillation. </li> </ul> </li> + <li> + <strong> + Muse Spark (April 2026): + </strong> + Released by Meta Superintelligence Labs; Meta's first proprietary, closed-weight model. Represents a shift alongside continued open-weight Llama releases. + </li> <li> <strong> Segment Anything Model (SAM): @@ -2679,7 +2660,7 @@ </h5> <div class="card-content-wrapper"> <p class="summary"> - Release of Llama 3 (April 2024) and Llama 3.1 (July 2024) open models. [37] Widespread integration of Meta AI assistant, powered by Llama 3, across Meta apps. [36, 37] Advancements in multimodal AI (Seamless family) and vision (SAM). Ongoing major investments in AI compute infrastructure. + Released Llama 4 (Scout, Maverick — April 5, 2025) with MoE architecture, native multimodality, and a 10M-token context window. [37] Llama 4 Behemoth still in training. Meta Superintelligence Labs launched Muse Spark (April 2026), Meta's first proprietary closed model. Continued expansion of Meta AI assistant across Meta apps. Ongoing major investments in AI compute infrastructure. </p> <button aria-expanded="false" class="btn btn-sm details-toggle" data-bs-target="#collapseMetaDevelopments" data-bs-toggle="collapse" type="button"> Details @@ -2695,15 +2676,21 @@ <ul> <li> <strong> - Llama 3 and 3.1 Releases: + Llama 4 Release (April 5, 2025): + </strong> + Launch of Llama 4 Scout and Maverick — Meta's first MoE-architecture models with native multimodality. Scout has a 10M-token context window; Maverick matches or beats GPT-4o and Gemini 2.0 Flash on key benchmarks per Meta's testing. Llama 4 Behemoth (~2T total parameters) remains in training as of June 2026. [37] + </li> + <li> + <strong> + Muse Spark (April 2026): </strong> - Launch of the Llama 3 family of open models (8B and 70B parameters in April 2024), followed by Llama 3.1 (8B, 70B, and 405B parameters in July 2024), offering state-of-the-art performance for open models. [37] + Meta Superintelligence Labs released Muse Spark, Meta's first proprietary, closed-weight model — a significant strategic shift alongside continued open Llama releases. </li> <li> <strong> Meta AI Assistant Expansion: </strong> - Broader rollout and enhanced capabilities of the Meta AI assistant, powered by Llama 3, across Facebook, Instagram, WhatsApp, Messenger, and Ray-Ban Meta smart glasses. [36, 37] Now available in more countries and with features like real-time search integration. [37] + Broader rollout of the Meta AI assistant, powered by Llama 4, across Facebook, Instagram, WhatsApp, Messenger, and Ray-Ban Meta smart glasses. [36, 37] Available in more countries with real-time search integration. </li> <li> <strong> @@ -2787,7 +2774,7 @@ <strong> Valuation: </strong> - ~€11.7 billion (about $14 billion) after a €1.7 billion Series C round in September 2025, with ASML as lead investor. Up from ~$6 billion (mid-2024) and ~$2 billion (December 2023). Europe's most valuable AI startup. + ~€11.7 billion (~$14 billion) after a €1.7 billion Series C (September 2025, led by ASML). In June 2026, Mistral is in talks to raise €3 billion at a ~€20 billion valuation, which would nearly double its last round. Also secured $830M in debt financing (March 2026) for datacenter buildout. Europe's most valuable AI startup. </li> <li> <strong> @@ -3197,7 +3184,7 @@ </h5> <div class="card-content-wrapper"> <p class="summary"> - Mistral AI has rapidly raised significant funding, from a €105M seed round (June 2023) and €385M Series A (December 2023) to a €1.7 billion Series C in September 2025 led by chipmaker ASML, valuing it at ~€11.7 billion (about $14 billion). [24] Key investors include ASML, Andreessen Horowitz (a16z), Lightspeed Venture Partners, Nvidia, and Salesforce. They have a strategic partnership with Microsoft, including Azure model distribution. [3, 5] + Mistral AI has rapidly raised significant funding: €105M seed (June 2023), €385M Series A (December 2023), €600M Series B (June 2024, ~$6B valuation), and €1.7B Series C (September 2025, led by ASML, ~€11.7B valuation). In March 2026, secured $830M in debt financing for datacenter expansion. As of June 2026, in talks to raise €3B at a ~€20B valuation. [24] Key investors include ASML, a16z, Lightspeed, Nvidia, and Salesforce. Strategic partnership with Microsoft includes Azure model distribution. [3, 5] </p> <button aria-expanded="false" class="btn btn-sm details-toggle" data-bs-target="#collapseMistralFunding" data-bs-toggle="collapse" type="button"> Details @@ -3225,9 +3212,9 @@ </li> <li> <strong> - Series B & Series C: + Series B, Series C & 2026 Financing: </strong> - A June 2024 Series B raised €600M at a ~$6 billion valuation. The September 2025 Series C raised €1.7 billion led by ASML, valuing Mistral at ~€11.7 billion (~$14 billion). In 2026 Mistral raised additional capital for European datacenter buildout and is targeting $1B+ in ARR by year-end. [27] + A June 2024 Series B raised €600M at a ~$6 billion valuation. The September 2025 Series C raised €1.7 billion led by ASML, valuing Mistral at ~€11.7 billion (~$14 billion). In March 2026, Mistral secured $830M in debt financing for datacenter buildout. As of June 2026, in early-stage talks to raise €3 billion at a ~€20 billion valuation, which would nearly double its Series C valuation. ARR reached $400M+ by early 2026. [27] </li> </ul> <h6> @@ -3330,7 +3317,7 @@ <strong> Continued Funding and Valuation Growth: </strong> - Closed a €1.7 billion Series C in September 2025 led by ASML at a ~€11.7 billion (~$14 billion) valuation, cementing its position as Europe's most valuable AI startup. [27] + Closed a €1.7 billion Series C (September 2025, led by ASML) at a ~€11.7 billion (~$14 billion) valuation. Secured $830M in debt financing (March 2026) for European datacenter buildout targeting 200MW by 2027 and 1GW by 2030. As of June 2026, in talks to raise €3 billion at a ~€20 billion valuation. ARR reached $400M+ by early 2026. [27] </li> </ul> </div> @@ -3806,7 +3793,7 @@ <strong> Valuation: </strong> - Historically self-funded by High-Flyer. In 2026, DeepSeek entered talks for its first external funding round, with reported targets escalating from ~$20 billion to as high as $45–50 billion. + Self-funded by High-Flyer until 2026. Closed first external funding round in 2026, raising ~$7.4 billion (50B+ yuan) led by Tencent (~$1.5B) and CATL (~$735M), with Liang Wenfeng personally investing ~$2.8B. Post-money valuation reported at $52–59 billion. </li> <li> <strong> @@ -4114,7 +4101,7 @@ </h5> <div class="card-content-wrapper"> <p class="summary"> - DeepSeek was self-funded for its first years through the High-Flyer hedge fund. In 2026 it began talks for its first outside capital, with reported valuation targets climbing from ~$20 billion toward $45–50 billion, and interest from China's state IC fund, Tencent, and Alibaba. + DeepSeek was self-funded for its first years through the High-Flyer hedge fund. In 2026 it closed its first external funding round: ~$7.4 billion raised at a $52–59 billion post-money valuation, led by Tencent and CATL, with founder Liang Wenfeng making the largest individual investment (~$2.8B). A five-year lock-up with no voting rights structures the round. </p> <button aria-expanded="false" class="btn btn-sm details-toggle" data-bs-target="#collapseDeepSeekFunding" data-bs-toggle="collapse" type="button"> Details @@ -4138,13 +4125,19 @@ <strong> First External Round (2026): </strong> - DeepSeek entered talks to raise its first venture capital — reportedly $3–4 billion — with valuation targets escalating quickly from ~$20 billion toward $45–50 billion. + Closed a ~$7.4 billion (50B+ yuan) funding round — the first outside capital since founding. Post-money valuation reported at $52–59 billion (350–400B yuan). </li> <li> <strong> - Strategic Interest: + Key Investors: </strong> - The round is reported to involve the China Integrated Circuit Industry Investment Fund, with Tencent and Alibaba also in discussions, partly to help retain researchers being courted by rivals. + Led by Tencent (~$1.5B) and battery maker CATL (~$735M). Founder Liang Wenfeng personally invested ~20B yuan (~$2.8B), the largest individual contribution. Funds flow through a limited partnership managed by Liang Wenfeng, with a five-year lock-up and no voting rights for investors. + </li> + <li> + <strong> + Strategic Rationale: + </strong> + Capital raised partly to retain researchers being courted by rivals (both domestic and international), and to fund continued model development and infrastructure. </li> </ul> </div> @@ -4160,7 +4153,7 @@ </h5> <div class="card-content-wrapper"> <p class="summary"> - Released the V2 and V3 Mixture-of-Experts models and the breakout DeepSeek-R1 reasoning model (January 2025), which reshaped industry cost assumptions. In 2026, DeepSeek began raising its first external funding amid strong investor and state interest. + Released V3 (efficient MoE) and the breakout DeepSeek-R1 reasoning model (January 2025), which reshaped industry cost assumptions. Closed first external funding round in 2026: ~$7.4B at a $52–59B valuation, led by Tencent and CATL. Continued open-weight releases; latest model reported ~8 months behind top US offerings per Washington assessment. </p> <button aria-expanded="false" class="btn btn-sm details-toggle" data-bs-target="#collapseDeepSeekDevelopments" data-bs-toggle="collapse" type="button"> Details @@ -4196,7 +4189,7 @@ <strong> First Funding Round (2026): </strong> - Began talks for its first external capital, with reported valuation targets rising from ~$20 billion toward $45–50 billion. + Closed ~$7.4 billion (50B+ yuan) at a $52–59 billion post-money valuation, led by Tencent and CATL. Founder Liang Wenfeng made the largest single investment. Five-year lock-up, no voting rights for outside investors. </li> <li> <strong> @@ -4338,7 +4331,10 @@ </a> </div> <p class="mb-2"> - © 2025 David Veksler · Compiled & expanded based on leading AI labs, academic institutions, and industry publications. + © 2025–2026 David Veksler · Compiled & expanded based on leading AI labs, academic institutions, and industry publications. + </p> + <p class="mb-2" style="font-size:0.85em; color: var(--ai-text-secondary);"> + Last verified: 2026-06-21 </p> <div> <a class="mx-2 link-secondary" href="https://www.linkedin.com/in/davidveksler/" target="_blank" title="David Veksler on LinkedIn"> --- a/ai-progress-dashboard.html +++ b/ai-progress-dashboard.html @@ -197,7 +197,7 @@ </div> <div class="spark-wrap"><canvas id="swe-spark"></canvas></div> <div class="caveat"> - Score is <strong>agent + scaffold</strong>, not raw model capability — the scaffold label keeps a bespoke harness from being misread as model headroom. This is <em>Verified</em> (the 500-sample human-validated subset; Epoch runs 484), not full SWE-bench. Epoch upgraded its scaffold significantly in Feb 2026. + Score is <strong>agent + scaffold</strong>, not raw model capability — the scaffold label keeps a bespoke harness from being misread as model headroom. This is <em>Verified</em> (the 500-sample human-validated subset; Epoch runs 484), not full SWE-bench. Epoch upgraded its scaffold significantly in Feb 2026. Claude Fable 5 independently confirmed at 95.0% by vals.ai (Jun 2026); Claude Mythos 5 at 95.5% (llm-stats.com). Both models suspended Jun 12 2026 via US export-control directive. </div> </section> @@ -228,7 +228,7 @@ <div class="caveat" id="metr-extrap-note"> <strong>Forward markers (extrapolation from current anchor at 7-mo doubling):</strong> <span id="metr-forward">…</span><br/> - Robustness: METR notes that a 10× absolute-measurement error shifts arrival by ~2 years — slope dominates. Gaps in coverage are not regressions; METR doesn't evaluate every release. Newest points (esp. Claude Mythos Preview) sit at or past the suite's measurement ceiling — wide CI. + Robustness: METR notes that a 10× absolute-measurement error shifts arrival by ~2 years — slope dominates. Gaps in coverage are not regressions; METR doesn't evaluate every release. Newest points (esp. Claude Mythos Preview) sit at or past the suite's measurement ceiling — wide CI. Claude Fable 5 and Mythos 5 (released Jun 9 2026) have not yet been added to METR's time-horizons chart as of Jun 21 2026. </div> </section> @@ -249,7 +249,7 @@ <tbody id="aa-tbody"></tbody> </table> <div class="caveat"> - AA's <em>Intelligence Index</em> is a composite of ~10 benchmarks (v4.0). Methodology shifts; values are relative, not absolute, and reflect benchmark/style biases. Blended $/Mtok shown as 3:1 input:output (a common heuristic, not AA's exact blend — AA uses 7:2:1 cache:input:output). + AA's <em>Intelligence Index</em> is a composite of ~10 benchmarks (v4.1, updated Jun 2026 to weight agentic workloads). Methodology shifts; values are relative, not absolute, and reflect benchmark/style biases. Blended $/Mtok shown as 3:1 input:output (a common heuristic, not AA's exact blend — AA uses 7:2:1 cache:input:output). Claude Fable 5/Mythos 5 suspended Jun 12 2026 via US export-control directive; Opus 4.8 is the usable frontier for non-US teams. </div> </section> @@ -273,7 +273,7 @@ </div> <div class="footnote"> - Data baked at build time on May 30, 2026 (Cowork artifacts can't reach external APIs). Synthesis runs live in your browser via window.cowork.askClaude. Ask Claude to rebuild this artifact to refresh underlying numbers. + Data baked at build time on June 21, 2026 (Cowork artifacts can't reach external APIs). Synthesis runs live in your browser via window.cowork.askClaude. Ask Claude to rebuild this artifact to refresh underlying numbers. Last verified: 2026-06-21. </div> </div> @@ -281,16 +281,16 @@ /* ============================================================================ DATA (pre-fetched at build time — sandbox can't reach external APIs) ============================================================================ */ -const BUILD_DATE = "2026-05-30"; +const BUILD_DATE = "2026-06-21"; // --- SWE-bench Verified (Epoch leaderboard) --- const SWE = { - top_score_pct: 93.9, - model: "Claude Mythos Preview", + top_score_pct: 95.5, + model: "Claude Mythos 5", scaffold: "Epoch v2.0.3 (bash + text_editor + apply_patch, no network)", - date: "2026-05-28", + date: "2026-06-09", source_url: "https://epoch.ai/benchmarks/swe-bench-verified", - source_sentence: "Claude Mythos Preview leads the SWE-bench Verified leaderboard with 93.9% as of May 28, 2026.", + source_sentence: "Claude Mythos 5 leads the SWE-bench Verified leaderboard with 95.5% as of June 2026 (vals.ai independently confirmed Claude Fable 5 at 95.0%).", history: [ { date: "2024-06-20", model: "Claude 3.5 Sonnet", score: 49.0 }, { date: "2024-10-22", model: "Claude 3.5 Sonnet (new)", score: 53.7 }, @@ -302,13 +302,15 @@ const SWE = { { date: "2026-02-20", model: "Claude Opus 4.6", score: 80.8 }, { date: "2026-04-15", model: "Claude Opus 4.7 (Adaptive)", score: 87.6 }, { date: "2026-05-15", model: "Claude Opus 4.8", score: 88.6 }, - { date: "2026-05-28", model: "Claude Mythos Preview", score: 93.9 } + { date: "2026-05-28", model: "Claude Mythos Preview", score: 93.9 }, + { date: "2026-06-09", model: "Claude Fable 5", score: 95.0 }, + { date: "2026-06-09", model: "Claude Mythos 5", score: 95.5 } ] }; // --- METR Time Horizon 1.1 (50% horizons in minutes) --- const METR = { - frontier_horizon_min: 960, // 16h cap — Claude Mythos Preview + frontier_horizon_min: 960, // 16h cap — Claude Mythos Preview; Claude Fable 5/Mythos 5 not yet evaluated by METR (Jun 2026) frontier_model: "Claude Mythos Preview (early)", frontier_horizon_is_capped: true, doubling_months_historical: 7, @@ -316,7 +318,7 @@ const METR = { as_of_date: "2026-05-08", ceiling_min: 960, source_url: "https://metr.org/time-horizons/", - source_sentence: "Added Claude Mythos Preview (early) and notice that 'Measurements above 16 hrs are unreliable with our current task suite.'", + source_sentence: "Added Claude Mythos Preview (early) and notice that 'Measurements above 16 hrs are unreliable with our current task suite.' Claude Fable 5/Mythos 5 (Jun 9 2026) not yet added to METR chart as of Jun 21 2026.", // 50%-time horizons in MINUTES, dates approximate (per METR Time Horizon 1.1 updates timeline) recent_points: [ { model: "GPT-4", date: "2023-03-15", horizon_min: 5 }, @@ -337,17 +339,19 @@ const METR = { ] }; -// --- Artificial Analysis (Intelligence Index v4.0, May 2026 snapshot) --- +// --- Artificial Analysis (Intelligence Index v4.1, June 2026 snapshot) --- // Blended price computed simple 3:1 input:output for comparability across models. +// Claude Fable 5 launched Jun 9 2026 at #1 (index 64.9 full / 60 with fallback). GPT-5.5 fell to 55. +// Claude Fable 5 / Mythos 5 temporarily suspended Jun 12 2026 (US export-control directive). const AA = { - as_of: "2026-05-28", + as_of: "2026-06-21", source_url: "https://artificialanalysis.ai/leaderboards/models", models: [ - { name: "Claude Opus 4.8 (max)", intelligence_index: 61, in_per_mtok: 6.25, out_per_mtok: 25, output_tok_per_s: 57.7 }, - { name: "GPT-5.5 (xhigh)", intelligence_index: 60, in_per_mtok: 5.00, out_per_mtok: 30, output_tok_per_s: 65 }, - { name: "GPT-5.5 (high)", intelligence_index: 59, in_per_mtok: 5.00, out_per_mtok: 30, output_tok_per_s: 75 }, - { name: "Claude Opus 4.7 (max)", intelligence_index: 57, in_per_mtok: 15, out_per_mtok: 75, output_tok_per_s: 52 }, - { name: "Gemini 3.1 Pro Preview", intelligence_index: 57, in_per_mtok: 2.50, out_per_mtok: 15, output_tok_per_s: 110 } + { name: "Claude Fable 5 (w/ fallback)", intelligence_index: 60, in_per_mtok: 10.00, out_per_mtok: 50, output_tok_per_s: 48 }, + { name: "Claude Opus 4.8 (max)", intelligence_index: 56, in_per_mtok: 6.25, out_per_mtok: 25, output_tok_per_s: 57.7 }, + { name: "GPT-5.5 (xhigh)", intelligence_index: 55, in_per_mtok: 5.00, out_per_mtok: 30, output_tok_per_s: 65 }, + { name: "GPT-5.5 (high)", intelligence_index: 54, in_per_mtok: 5.00, out_per_mtok: 30, output_tok_per_s: 75 }, + { name: "Gemini 3.1 Pro Preview", intelligence_index: 53, in_per_mtok: 2.50, out_per_mtok: 15, output_tok_per_s: 110 } ] }; // derive blended price (3:1 in:out) for each row @@ -768,7 +772,7 @@ function renderAA() { }, y: { title: { display: true, text: "Intelligence Index", font: { size: 10 }, color: "#6b7280" }, - min: 54, max: 63, + min: 50, max: 65, ticks: { font: { size: 10 }, color: "#6b7280", stepSize: 1 }, grid: { color: "#f3f4f6" } } @@ -885,10 +889,10 @@ function fallbackSynthesis(cur) { `For day-to-day use, the Pareto frontier on Artificial Analysis runs from ${AA.models[0].name} (Intel ${cur.aa_top}) down to cheaper, fast tiers. ` + `All of this rides on a training-compute curve that has held a ~4.2×/yr slope since 2010, now sitting near 10¹¹ petaFLOP for top runs.`, extrapolations: [ - "SWE-bench Verified is near saturation — expect <5pt headroom and a switch to harder benchmarks (SWE-bench Pro, Terminal-Bench) within ~6 months.", - "If the 7-month doubling holds from today's anchor, 40h (one work-week) lands ~mid-to-late 2027; the recent 4-month pace pulls that into 2026 H2 — but METR's 16h ceiling means new top scores are now upper-bounded, not measured.", + "SWE-bench Verified is effectively saturated — Claude Mythos 5 sits at 95.5% with <5pt of headroom; expect leaderboard attention to shift to SWE-bench Pro and Terminal-Bench.", + "If the 7-month doubling holds from the May 2026 METR anchor, 40h (one work-week) lands ~mid-to-late 2027; the recent 4-month pace pulls that into 2026 H2 — but METR's 16h ceiling means Claude Fable 5/Mythos 5 cannot yet be measured on this suite.", "Compute and capability are decoupling at the margin: DeepSeek-V4 and Qwen3 deliver frontier-class scores at 1-2 orders of magnitude less FLOP than GPT-4.5/Grok 4.", - "Pricing for the frontier intelligence tier has collapsed ~3-5× over the last 12 months at the same Intel index — keep this in mind for any cost projections." + "Pricing for the frontier intelligence tier has collapsed ~3-5× over the last 12 months at the same Intel index — Claude Fable 5 at $10/$50 per Mtok is 2× Opus 4.8 for a ~7pt AA index gain." ] }; } --- a/ai-risk-timeline.html +++ b/ai-risk-timeline.html @@ -40,7 +40,7 @@ "name": "David Veksler Cheatsheets" }, "datePublished": "2024-08-27", - "dateModified": "2024-08-27", + "dateModified": "2026-06-21", "keywords": "AI Existential Risk, AI Safety Timeline, Superintelligence History, Technological Singularity, AI Alignment Problem, Effective Accelerationism, e/acc, AI Governance, Geoffrey Hinton, Nick Bostrom, Eliezer Yudkowsky, Alan Turing, I.J. Good, Vernor Vinge, AI Ethics, Machine Intelligence, Artificial General Intelligence", "about": [ { @@ -558,14 +558,16 @@ <p>The challenge of coordinating action between competing nations and corporations to prevent a reckless "race to the bottom" on safety. Proposals include international treaties, compute thresholds requiring government oversight, and independent auditing bodies for advanced AI models.</p> <blockquote> <p>"The development of full artificial intelligence could spell the end of the human race. We need to be very careful about how we proceed."</p> - + </blockquote> <p><strong>Links:</strong> <a href="https://www.partnershiponai.org/" target="_blank" rel="noopener noreferrer">Partnership on AI</a> | <a href="https://www.gov.uk/government/publications/ai-safety-summit-2023-the-bletchley-declaration" target="_blank" rel="noopener noreferrer">Bletchley Declaration</a></p> <details class="mt-3"> <summary><strong>More Details</strong></summary> <div class="p-3"> - <p><strong>International Efforts:</strong> The UK AI Safety Summit, EU AI Act, and various bilateral agreements represent early attempts at global coordination.</p> - <p><strong>Challenges:</strong> Nations and companies face strong incentives to advance AI capabilities quickly, making coordination difficult.</p> + <p><strong>International Summits:</strong> After the UK Bletchley Park summit (Nov 2023), South Korea co-hosted the Seoul AI Safety Summit (May 2024), where 16 leading AI companies signed "Frontier AI Safety Commitments." The Paris AI Action Summit (Feb 2025) saw 58 countries sign a joint declaration on inclusive AI — though the US and UK declined to sign.</p> + <p><strong>EU AI Act (2024–2026):</strong> The landmark regulation entered into force 1 Aug 2024. A ban on "unacceptable risk" AI (social scoring, real-time biometric surveillance) applied from 2 Feb 2025. Rules for General Purpose AI (GPAI) models — including frontier foundation models — applied from 2 Aug 2025. A May 2026 "Digital Omnibus" provisional agreement deferred main high-risk AI deadlines to 2027–2028.</p> + <p><strong>US Policy Whiplash:</strong> Biden's Oct 2023 AI Executive Order (EO 14110) was revoked on Trump's first day back in office (20 Jan 2025). Trump signed EO 14179 — "Removing Barriers to American Leadership in AI" — three days later, shifting federal policy sharply toward acceleration over precaution.</p> + <p><strong>UK Rebranding:</strong> The UK AI Safety Institute was renamed the AI Security Institute in February 2025, narrowing its focus from broad ethics to specific security threats such as cybercrime and CBRN weapons misuse.</p> <p><strong>Libertarian Counterpoint:</strong> Some argue that heavy regulation could stifle innovation and hand advantages to less regulated jurisdictions, particularly authoritarian regimes.</p> </div> </details> @@ -596,6 +598,75 @@ </div> </div> </div> + <div class="timeline-item"> + <div class="timeline-icon"><i class="bi bi-person-x-fill"></i></div> + <div class="timeline-content-wrapper"> + <div class="timeline-content"> + <span class="year">May 2024</span> + <h3>The Safety Exodus at OpenAI</h3> + <p>OpenAI co-founder and Chief Scientist Ilya Sutskever departs in May 2024 to found Safe Superintelligence Inc. (SSI). Days later, Jan Leike — co-lead of OpenAI's Superalignment team — resigns publicly, stating that "safety culture and processes have taken a backseat to shiny products." OpenAI's Superalignment team, formed just a year earlier with a pledge of 20% of compute for safety research, is effectively disbanded. Leike joins Anthropic. A second safety-adjacent team, the AGI Readiness group, is also dissolved later that year.</p> + <blockquote> + <p>"I have been sailing against the wind… I believe much more of our bandwidth should be spent getting ready for the next generation of models."</p> + <footer>— Jan Leike, resignation post, May 2024</footer> + </blockquote> + <p><strong>Links:</strong> <a href="https://en.wikipedia.org/wiki/Jan_Leike" target="_blank" rel="noopener noreferrer">Wikipedia: Jan Leike</a> | <a href="https://en.wikipedia.org/wiki/Ilya_Sutskever" target="_blank" rel="noopener noreferrer">Wikipedia: Ilya Sutskever</a></p> + <details class="mt-3"> + <summary><strong>More Details</strong></summary> + <div class="p-3"> + <p><strong>SSI:</strong> Sutskever's Safe Superintelligence Inc. describes its sole focus as building safe superintelligence — explicitly declining to ship products or pursue revenue until that goal is achieved.</p> + <p><strong>Pattern of Departures:</strong> The exits followed an earlier wave of OpenAI departures in 2023 after the board's brief ouster of Sam Altman, and preceded further safety-related departures at other labs in 2025–2026.</p> + <p><strong>Industry Concern:</strong> The public nature of Leike's resignation — and its specific accusations about safety culture — drew significant attention, as OpenAI had presented itself as a safety-first organization.</p> + </div> + </details> + </div> + </div> + </div> + <div class="timeline-item"> + <div class="timeline-icon"><i class="bi bi-trophy-fill"></i></div> + <div class="timeline-content-wrapper"> + <div class="timeline-content"> + <span class="year">October 2024</span> + <h3>The Nobel Prize Goes to AI: Hinton & Hopfield</h3> + <p>The Royal Swedish Academy of Sciences awards the 2024 Nobel Prize in Physics to Geoffrey Hinton and John Hopfield "for foundational discoveries and inventions that enable machine learning with artificial neural networks." It is the first Nobel Prize awarded explicitly for AI research. Hinton, already famous for leaving Google to warn about AI dangers, uses the occasion to reiterate his concerns about existential risk — making him perhaps the most credentialed AI safety voice in the world.</p> + <blockquote> + <p>"I'm scared that this tsunami of AI will overwhelm us… I think it's quite likely that AI systems will become more intelligent than people and will develop their own sub-goals."</p> + <footer>— Geoffrey Hinton, Nobel Prize press conference, Oct 2024</footer> + </blockquote> + <p><strong>Links:</strong> <a href="https://www.nobelprize.org/prizes/physics/2024/summary/" target="_blank" rel="noopener noreferrer">Nobel Prize Announcement</a> | <a href="https://en.wikipedia.org/wiki/Geoffrey_Hinton" target="_blank" rel="noopener noreferrer">Wikipedia: Geoffrey Hinton</a></p> + <details class="mt-3"> + <summary><strong>More Details</strong></summary> + <div class="p-3"> + <p><strong>Significance:</strong> Awarding AI research the Nobel Prize in Physics — rather than a dedicated AI prize — signals that the field has achieved a level of fundamental scientific importance the Nobel Committee considers equivalent to discoveries in physics.</p> + <p><strong>Hinton's Dual Status:</strong> Hinton holds both a Turing Award (2018, with LeCun and Bengio) and a Nobel Prize — making him one of the most decorated scientists alive and lending extraordinary weight to his safety warnings.</p> + <p><strong>Counter-view:</strong> Some AI researchers note that Hopfield networks and backpropagation are decades-old techniques, and the Prize may reflect a lag between achievement and recognition rather than an endorsement of current risk timelines.</p> + </div> + </details> + </div> + </div> + </div> + <div class="timeline-item"> + <div class="timeline-icon"><i class="bi bi-lightning-charge-fill"></i></div> + <div class="timeline-content-wrapper"> + <div class="timeline-content"> + <span class="year">Late 2024 – 2025</span> + <h3>Reasoning Models & the AGI Threshold Debate</h3> + <p>OpenAI releases its o1 "reasoning" model in September 2024, followed by o3 in December — which scores at near-expert human level on the ARC-AGI benchmark, a test specifically designed to resist pattern-matching. In January 2025, OpenAI CEO Sam Altman writes publicly: <em>"We are now confident we know how to build AGI as we have traditionally understood it."</em> Google DeepMind separately publishes a major safety paper warning that AGI matching "top human skills" could arrive by 2030. The question shifts from <em>if</em> to <em>when</em> — and whether safety research can keep pace.</p> + <blockquote> + <p>"We are now confident we know how to build AGI as we have traditionally understood it."</p> + <footer>— Sam Altman, blog post, January 2025</footer> + </blockquote> + <p><strong>Links:</strong> <a href="https://openai.com/index/learning-to-reason-with-llms/" target="_blank" rel="noopener noreferrer">OpenAI o1 System Card</a> | <a href="https://arcprize.org/" target="_blank" rel="noopener noreferrer">ARC Prize</a></p> + <details class="mt-3"> + <summary><strong>More Details</strong></summary> + <div class="p-3"> + <p><strong>Reasoning vs. Pattern Matching:</strong> The ARC-AGI benchmark (by François Chollet) was designed to require novel problem-solving that could not be solved by memorizing training data. o3's high score reopened debate about whether current systems are approaching genuine reasoning.</p> + <p><strong>Rapid Capability Gains:</strong> Between 2024 and mid-2025, every major lab released models with substantially expanded reasoning, coding, and scientific capabilities — Claude 3.7 Sonnet (Feb 2025), Gemini 2.5 Pro (Mar 2025), Llama 4 (Apr 2025), Claude 4 / GPT-5 (mid-2025). The pace of releases compresses safety review timelines.</p> + <p><strong>Safety-Capability Gap:</strong> Alignment researchers note that interpretability and controllability research has not kept pace with capability gains, widening the gap between what AI can do and what we can verify about its internal goals.</p> + </div> + </details> + </div> + </div> + </div> <div class="timeline-item"> <div class="timeline-icon"><i class="bi bi-arrows-expand"></i></div> <div class="timeline-content-wrapper"> @@ -705,8 +776,9 @@ </a> </div> <p class="mb-2"> - © 2025 David Veksler · Compiled & expanded based on AI safety research papers and expert forecasts. + © 2026 David Veksler · Compiled & expanded based on AI safety research papers and expert forecasts. </p> + <p class="mb-2 text-muted" style="font-size:0.85em;">Last verified: 2026-06-21</p> <div> <a class="mx-2 link-secondary" href="https://www.linkedin.com/in/davidveksler/" target="_blank" title="David Veksler on LinkedIn"> <i class="bi bi-linkedin"></i> --- a/airisk.html +++ b/airisk.html @@ -874,8 +874,8 @@ UK AISI </a> , - <a href="https://www.nist.gov/artificial-intelligence/artificial-intelligence-safety-institute" rel="noopener noreferrer" target="_blank"> - US AISI + <a href="https://www.nist.gov/caisi" rel="noopener noreferrer" target="_blank"> + US CAISI </a> , <a href="https://www.oecd.org/en/about/programmes/global-partnership-on-artificial-intelligence.html" rel="noopener noreferrer" target="_blank"> @@ -1220,8 +1220,8 @@ UK AISI </a> , - <a href="https://www.nist.gov/artificial-intelligence/artificial-intelligence-safety-institute" rel="noopener noreferrer" target="_blank"> - US AISI + <a href="https://www.nist.gov/caisi" rel="noopener noreferrer" target="_blank"> + US CAISI </a> </li> <li> @@ -1304,7 +1304,10 @@ </a> </div> <p class="mb-2"> - © 2025 David Veksler · Compiled & expanded based on AI safety research institutions and existential risk assessments. + © 2026 David Veksler · Compiled & expanded based on AI safety research institutions and existential risk assessments. + </p> + <p class="mb-2" style="font-size:0.85em; color: var(--text-muted-color);"> + Last verified: 2026-06-21 </p> <div> <a class="mx-2 link-secondary" href="https://www.linkedin.com/in/davidveksler/" target="_blank" title="David Veksler on LinkedIn"> --- a/aisafety.html +++ b/aisafety.html @@ -1145,7 +1145,10 @@ </a> </div> <p class="mb-2"> - © 2025 David Veksler · Compiled & expanded based on AI alignment research and safety organizations. + © 2026 David Veksler · Compiled & expanded based on AI alignment research and safety organizations. + </p> + <p class="mb-2 text-muted small"> + Last verified: 2026-06-21 </p> <div> <a class="mx-2 link-secondary" href="https://www.linkedin.com/in/davidveksler/" target="_blank" title="David Veksler on LinkedIn"> --- a/automotive-innovation-timeline.html +++ b/automotive-innovation-timeline.html @@ -3,7 +3,7 @@ <head> <meta charset="UTF-8"> <meta name="viewport" content="width=device-width, initial-scale=1.0"> - <title>Automotive Innovation Timeline: From Model T to Tesla (1908-2025)</title> + <title>Automotive Innovation Timeline: From Model T to Tesla (1908-2026)</title> <meta name="description" content="Interactive timeline of automotive innovation spanning over a century, from the Ford Model T's flywheel magneto (1908) to Tesla's Full Self-Driving AI. Explore key breakthroughs in mechanical, safety, digital, and autonomous driving technology."> <meta name="keywords" content="automotive history, car innovation timeline, Model T, Tesla, automobile technology, automotive engineering, self-driving cars, electric vehicles, automotive safety, ADAS, hybrid cars"> <link rel="canonical" href="https://cheatsheets.davidveksler.com/automotive-innovation-timeline.html"> @@ -14,7 +14,7 @@ <meta property="og:type" content="website"> <meta property="og:url" content="https://cheatsheets.davidveksler.com/automotive-innovation-timeline.html"> <meta property="og:image" content="images/automotive-innovation-timeline.png"> - <meta property="og:image:alt" content="Timeline visualization showing automotive innovations from 1908 to 2025"> + <meta property="og:image:alt" content="Timeline visualization showing automotive innovations from 1908 to 2026"> <!-- Twitter Card Tags --> <meta name="twitter:card" content="summary_large_image"> @@ -28,7 +28,7 @@ { "@context": "https://schema.org", "@type": "TechArticle", - "headline": "Automotive Innovation Timeline: From Model T to Tesla (1908-2025)", + "headline": "Automotive Innovation Timeline: From Model T to Tesla (1908-2026)", "description": "Comprehensive interactive timeline documenting over 100 years of automotive innovation, from the Ford Model T's mechanical simplicity to Tesla's AI-driven autonomous vehicles. Covers mechanical innovations, safety features, digital revolution, and the dawn of autonomy.", "author": { "@type": "Person", @@ -39,7 +39,7 @@ "name": "David Veksler Cheatsheets" }, "datePublished": "2025-01-06", - "dateModified": "2025-01-06", + "dateModified": "2026-06-21", "keywords": "automotive history, car innovation, Model T, Tesla, automobile technology, automotive engineering, self-driving cars, electric vehicles, automotive safety, ADAS, hybrid cars, automotive timeline" } </script> @@ -1016,22 +1016,61 @@ <div class="timeline-marker"></div> <div class="timeline-content"> <div class="timeline-year">Early 2020s</div> - <h3 class="timeline-title">Driverless Taxis - Waymo & Cruise</h3> + <h3 class="timeline-title">First Commercial Driverless Taxis - Waymo & Cruise</h3> <p class="timeline-description"> - Companies like Waymo (Google) and Cruise (GM) deployed fully autonomous vehicles for ride-hailing in limited regions. By the early 2020s, Waymo had driverless taxis with no safety driver operating, demonstrating that autonomous driving technology is rapidly maturing toward Level 4/5 autonomy. + Companies like Waymo (Alphabet/Google) and Cruise (GM) deployed fully autonomous vehicles for ride-hailing in limited regions. By the early 2020s, Waymo had driverless taxis with no safety driver operating in San Francisco and Phoenix, demonstrating that Level 4 autonomy was achievable in geo-fenced urban areas. Cruise suspended operations in October 2023 following a pedestrian incident, and GM permanently shut down the Cruise robotaxi program in December 2024. </p> <span class="era-badge" style="background: rgba(147, 112, 219, 0.15); color: var(--era-autonomy);">Autonomy Era</span> </div> </div> - <!-- 2025: Tesla FSD --> + <!-- 2025: Tesla FSD Supervised --> <div class="timeline-item era-autonomy" data-era="autonomy" data-year="2025"> <div class="timeline-marker"></div> <div class="timeline-content"> <div class="timeline-year">2025</div> - <h3 class="timeline-title">Tesla Full Self-Driving (Beta) - Most Advanced Consumer System</h3> + <h3 class="timeline-title">Tesla FSD Supervised - Consumer Level 2+ System</h3> <p class="timeline-description"> - As of 2025, Tesla's Full Self-Driving (Beta) is the most advanced driver-assist package offered to consumers. It attempts to handle city street driving: navigating to destinations, stopping at lights and signs, making turns. Despite its name, FSD is still Level 2 automation requiring continuous driver supervision. Eight cameras feed a neural network AI powered by a supercomputer chip, trained on millions of miles of real-world data. + Tesla renamed "Full Self-Driving (Beta)" to "FSD Supervised," dropping the Beta label while retaining Level 2 status requiring continuous driver attention. The system handles city street driving — navigating intersections, stopping at lights, making turns — fed by eight cameras into a neural network trained on billions of miles of real-world data. Despite the name, driver supervision remains mandatory at all times. + </p> + <span class="era-badge" style="background: rgba(147, 112, 219, 0.15); color: var(--era-autonomy);">Autonomy Era</span> + </div> + </div> + + <!-- 2025: Tesla Cybercab Robotaxi Launch --> + <div class="timeline-item era-autonomy" data-era="autonomy" data-year="2025"> + <div class="timeline-marker"></div> + <div class="timeline-content"> + <div class="timeline-year">2025–2026</div> + <h3 class="timeline-title">Tesla Cybercab - Commercial Driverless Robotaxi</h3> + <p class="timeline-description"> + Tesla launched its first commercial robotaxi service in Austin, Texas in June 2025, using Model Y vehicles with human safety monitors. Production of the purpose-built two-seat Cybercab began at Giga Texas in Q1 2026, and unsupervised driverless service expanded to Dallas and Houston in April 2026. The Cybercab operates at SAE Level 4 autonomy in designated service areas — Tesla's first commercially deployed fully driverless vehicle. + </p> + <span class="era-badge" style="background: rgba(147, 112, 219, 0.15); color: var(--era-autonomy);">Autonomy Era</span> + </div> + </div> + + <!-- 2025: NACS Becomes Industry Standard --> + <div class="timeline-item era-autonomy" data-era="autonomy" data-year="2025"> + <div class="timeline-marker"></div> + <div class="timeline-content"> + <div class="timeline-year">2025–2026</div> + <h3 class="timeline-title">NACS (SAE J3400) - Universal EV Charging Standard</h3> + <p class="timeline-description"> + Tesla's proprietary charging connector was adopted by Ford, GM, Rivian, and virtually every major automaker, standardized as SAE J3400 (North American Charging Standard). By 2025 model year vehicles began shipping with native NACS ports, and by 2026 it became the de facto standard for new North American EVs. This effectively ended the CCS/NACS connector fragmentation and gave all EV drivers access to Tesla's Supercharger network — the largest fast-charging network in North America. + </p> + <span class="era-badge" style="background: rgba(147, 112, 219, 0.15); color: var(--era-autonomy);">Autonomy Era</span> + </div> + </div> + + <!-- 2026: Waymo Scales Nationwide --> + <div class="timeline-item era-autonomy" data-era="autonomy" data-year="2026"> + <div class="timeline-marker"></div> + <div class="timeline-content"> + <div class="timeline-year">2026</div> + <h3 class="timeline-title">Waymo One - National Driverless Taxi Network</h3> + <p class="timeline-description"> + Waymo (Alphabet) scaled from a Phoenix/San Francisco pilot to a fleet of 3,000+ robotaxis serving 11 U.S. cities and over 1,400 square miles of coverage by mid-2026 — including Los Angeles, Atlanta, Miami, Dallas, Houston, San Antonio, and Orlando. Weekly rides grew from 175,000 to 450,000+ during 2025, establishing Waymo as the first driverless ride-hailing service operating at meaningful commercial scale. International expansion to London and Tokyo was announced for 2026–2027. </p> <span class="era-badge" style="background: rgba(147, 112, 219, 0.15); color: var(--era-autonomy);">Autonomy Era</span> </div> @@ -1040,7 +1079,7 @@ <div class="alert alert-info mt-4"> <h5><i class="bi bi-info-circle me-2"></i>Timeline Summary</h5> - <p class="mb-2">This comprehensive timeline chronicles over 100 years of automotive innovation across <strong>50+ major milestones</strong>, from the elegant simplicity of the Model T's magneto to the intricate neural networks of Tesla's AI.</p> + <p class="mb-2">This comprehensive timeline chronicles over 100 years of automotive innovation across <strong>55+ major milestones</strong>, from the elegant simplicity of the Model T's magneto to the commercial driverless robotaxis of 2026.</p> <p class="mb-0">Each advancement stands on the shoulders of previous innovations, demonstrating the continuum from purely mechanical ingenuity (hand-cranks, steel bodies, hydraulic brakes) to comfort and power (air conditioning, power steering, turbocharging) to digital revolution (ABS, airbags, GPS, hybrids) and finally to the dawn of autonomy (ADAS, electric vehicles, self-driving systems, OTA updates).</p> </div> @@ -1158,8 +1197,9 @@ </a> </div> <p class="mb-2"> - © 2025 David Veksler · Compiled & expanded based on automotive engineering journals and transportation technology research. + © 2026 David Veksler · Compiled & expanded based on automotive engineering journals and transportation technology research. </p> + <p class="mb-2 text-muted small">Last verified: 2026-06-21</p> <div> <a class="mx-2 link-secondary" href="https://www.linkedin.com/in/davidveksler/" target="_blank" title="David Veksler on LinkedIn"> <i class="bi bi-linkedin"></i> --- a/aws-vs-azure.html +++ b/aws-vs-azure.html @@ -4,18 +4,18 @@ <meta charset="utf-8"/> <meta content="width=device-width, initial-scale=1.0" name="viewport"/> <title> - AWS vs Azure (2025): Comprehensive Cloud Architect's Comparison & Cheatsheet + AWS vs Azure (2026): Comprehensive Cloud Architect's Comparison & Cheatsheet </title> <link href="data:image/svg+xml,<svg xmlns=%22http://www.w3.org/2000/svg%22 viewBox=%220 0 100 100%22><text y=%22.9em%22 font-size=%2290%22>🆚</text></svg>" rel="icon"/> - <meta content="AWS vs Azure (2025): A detailed side-by-side cloud service comparison for architects. 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Visually compare core services (EC2, S3, Lambda vs Azure VMs, Blob, Functions), with insights on Logic Apps vs Step Functions, AI, costs, and platform strengths." property="og:description"/> + <meta content="AWS vs Azure (2026): Comprehensive Architect's Cheatsheet & Comparison" property="og:title"/> + <meta content="A detailed 2026 AWS vs Azure comparison for architects. Visually compare core services (EC2, S3, Lambda vs Azure VMs, Blob, Functions), with insights on Logic Apps vs Step Functions, AI, costs, and platform strengths." property="og:description"/> <meta content="image/png" property="og:image:type"/> <meta content="1200" property="og:image:width"/> <meta content="630" property="og:image:height"/> @@ -23,14 +23,14 @@ <!-- Twitter --> <meta content="summary_large_image" name="twitter:card"/> <meta content="https://cheatsheets.davidveksler.com/aws-vs-azure.html" name="twitter:url"/> - <meta content="AWS vs Azure (2025): Architect's Cheatsheet & Cloud Comparison" name="twitter:title"/> - <meta content="This 2025 AWS vs Azure cheatsheet provides a side-by-side comparison of services (EC2, S3, Lambda vs Azure VMs, Blob, Functions), Logic Apps vs Step Functions, AI, pros/cons, and pricing insights. 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Covers EC2, S3, Lambda vs Azure VMs, Blob, Functions, Logic Apps, Step Functions, AI services, unique strengths, platform philosophies, and costs. An essential visual cheatsheet.", - "keywords": "aws vs azure, cloud comparison, aws services, azure services, cloud architect, ec2 vs azure vm, s3 vs blob storage, lambda vs azure functions, eks vs aks, redshift vs synapse, cloud costs, cloud migration, serverless comparison, iaas, paas, saas, Logic Apps, Step Functions, Application Insights, AI cloud services, 2025, cloud cheatsheet, cloud platform comparison", + "description": "AWS vs Azure (2026): A detailed side-by-side cloud service comparison for architects. Covers EC2, S3, Lambda vs Azure VMs, Blob, Functions, Logic Apps, Step Functions, AI services, unique strengths, platform philosophies, and costs. An essential visual cheatsheet.", + "keywords": "aws vs azure, cloud comparison, aws services, azure services, cloud architect, ec2 vs azure vm, s3 vs blob storage, lambda vs azure functions, eks vs aks, redshift vs synapse, cloud costs, cloud migration, serverless comparison, iaas, paas, saas, Logic Apps, Step Functions, Application Insights, AI cloud services, 2026, cloud cheatsheet, cloud platform comparison", "articleSection": "Cloud Computing Comparison", "wordCount": "5000" } @@ -413,8 +413,8 @@ <body itemscope="" itemtype="https://schema.org/TechArticle"> <meta content="2024-01-01" itemprop="datePublished"/> <!-- Placeholder: UPDATE WITH ACTUAL INITIAL PUBLICATION DATE --> - <meta content="2025-05-20" itemprop="dateModified"/> - <!-- Placeholder: UPDATE WITH LAST MODIFIED DATE --> + <meta content="2026-06-21" itemprop="dateModified"/> + <!-- Last verified: 2026-06-21 --> <div itemprop="publisher" itemscope="" itemtype="https://schema.org/Organization" style="display:none;"> <meta content="Cloud Comparison Cheatsheets" itemprop="name"/> <!-- Optional: <div itemprop="logo" itemscope itemtype="https://schema.org/ImageObject"><meta itemprop="url" content="URL_TO_YOUR_LOGO_IMAGE.png"></div> --> @@ -434,9 +434,9 @@ A direct side-by-side comparison of core services, plus insights into platform philosophies, unique strengths, and essential resources for architects. </p> <p class="last-updated"> - Last Updated: - <time datetime="2025-05-20" itemprop="dateModified"> - May 20, 2025 + Last verified: + <time datetime="2026-06-21" itemprop="dateModified"> + June 21, 2026 </time> </p> </header> @@ -1354,7 +1354,7 @@ Azure </span> <span class="service-name"> - Azure DDoS Protection (Basic & Standard) + Azure DDoS Protection (IP Protection & Network Protection) </span> </div> <p class="comparison-description"> @@ -1375,7 +1375,7 @@ AWS </span> <span class="service-name"> - CodeCommit, CodeBuild, CodeDeploy, CodePipeline, Cloud9 IDE + CodeCommit, CodeBuild, CodeDeploy, CodePipeline, AWS IDE Toolkits / CloudShell </span> </div> <div> @@ -1489,7 +1489,7 @@ Azure </span> <span class="service-name"> - Azure Machine Learning, Azure AI Services (Vision, Speech, Language, Decision), Azure OpenAI Service (GenAI) + Azure Machine Learning, Azure AI Foundry (Foundry Tools: Vision, Speech, Language), Azure OpenAI Service (GenAI) </span> </div> <p class="comparison-description"> @@ -1605,7 +1605,7 @@ Azure </span> <span class="service-name"> - Azure Blueprints, Microsoft Defender for Cloud, Azure Sentinel, Microsoft Purview (governance) + Azure Blueprints (deprecated Jul 2026 → migrate to Template Specs & Deployment Stacks), Microsoft Defender for Cloud, Azure Sentinel, Microsoft Purview (governance) </span> </div> <p class="comparison-description"> @@ -1832,9 +1832,9 @@ </li> <li> <strong> - Azure Policy, Blueprints, and Microsoft Purview: + Azure Policy, Deployment Stacks, and Microsoft Purview: </strong> - Strong governance tools for enforcing organizational standards, compliance, and data governance across Azure resources. + Strong governance tools for enforcing organizational standards, compliance, and data governance across Azure resources. (Azure Blueprints deprecated Jul 2026; successor is Template Specs + Deployment Stacks.) </li> <li> <strong> @@ -1844,9 +1844,9 @@ </li> <li> <strong> - Azure OpenAI Service: + Azure AI Foundry & Azure OpenAI Service: </strong> - Provides access to powerful OpenAI models like GPT-4, often with enterprise-grade security and compliance features. + Microsoft Foundry unifies models, agents, and tools (formerly Azure AI Services/Cognitive Services) under one platform. Azure OpenAI Service provides access to OpenAI models with enterprise-grade security and compliance. </li> </ul> </div> @@ -2095,7 +2095,7 @@ </a> </div> <p class="mb-2"> - © 2025 David Veksler · Compiled & expanded based on AWS and Azure official documentation and cloud architecture best practices. + © 2026 David Veksler · Compiled & expanded based on AWS and Azure official documentation and cloud architecture best practices. </p> <div> <a class="mx-2 link-secondary" href="https://www.linkedin.com/in/davidveksler/" target="_blank" title="David Veksler on LinkedIn"> --- a/azure-devops.html +++ b/azure-devops.html @@ -44,7 +44,7 @@ } }, "datePublished": "2024-06-15", - "dateModified": "2024-06-15", + "dateModified": "2026-06-21", "keywords": "DevOps, CI/CD, Azure DevOps, Azure Boards, Azure Repos, Azure Pipelines, Azure Test Plans, Azure Artifacts, Terraform, SonarQube, IaC, Git, Automation, Security" } </script> @@ -195,7 +195,7 @@ The Complete Azure DevOps Cheatsheet </h1> <p class="lead"> - A brutally honest, battle-hardened guide to the entire Azure DevOps suite. From planning with Boards, coding with Repos, building and releasing with Pipelines, to testing, artifacts, and beyond. + A brutally honest, battle-hardened guide to the entire Azure DevOps suite. From planning with Boards, coding with Repos, building and releasing with Pipelines, to testing, artifacts, and beyond. <strong>Note (June 2026):</strong> Microsoft's official direction is to migrate repos to GitHub for AI/Copilot features, while Azure Boards, Pipelines, and Test Plans remain supported for the long term. </p> </header> <div class="container"> @@ -717,7 +717,7 @@ </h5> <div class="card-content-wrapper"> <p class="summary"> - Manage your dependencies. Azure Artifacts provides private, secure feeds for hosting packages like NuGet, npm, Maven, Python, and Universal Packages. Stop relying solely on public registries. + Manage your dependencies. Azure Artifacts provides private, secure feeds for hosting packages like NuGet, npm, Maven, Python, Cargo, and Universal Packages. Stop relying solely on public registries. </p> <button aria-controls="collapseArtifactsOverview" aria-expanded="false" class="btn btn-outline-secondary btn-sm details-toggle" data-bs-target="#collapseArtifactsOverview" data-bs-toggle="collapse" type="button"> Details @@ -1032,7 +1032,7 @@ </span> : </strong> - Analyze source code. SonarQube has SAST capabilities. + Analyze source code. SonarQube has SAST capabilities. GitHub Advanced Security for Azure DevOps (GHAzDO) is now GA and adds CodeQL-powered code scanning, secret scanning, and dependency scanning natively in Azure Repos — with buildless scanning (no explicit build step required). </li> <li> <strong> @@ -1041,7 +1041,7 @@ </span> : </strong> - Scan open-source dependencies for known vulnerabilities. + Scan open-source dependencies for known vulnerabilities. GHAzDO includes dependency scanning for this purpose. </li> <li> <strong> @@ -1309,7 +1309,10 @@ </a> </div> <p class="mb-2"> - © 2025 David Veksler · Compiled & expanded based on Microsoft Azure documentation and CI/CD implementation guides. + © 2026 David Veksler · Compiled & expanded based on Microsoft Azure documentation and CI/CD implementation guides. + </p> + <p class="mb-2 text-muted" style="font-size:0.8em;"> + Last verified: 2026-06-21 </p> <div> <a class="mx-2 link-secondary" href="https://www.linkedin.com/in/davidveksler/" target="_blank" title="David Veksler on LinkedIn"> --- a/bitcoin-exchanges-cards.html +++ b/bitcoin-exchanges-cards.html @@ -607,7 +607,7 @@ Focus on security/compliance, user-friendly, insured hot wallet. Offers Credit Card (see Section III). </span> <span class="cons"> - Lower liquidity than giants, past 'Earn' program issues impacted trust, promotes altcoins, custodial risk. + Lower liquidity than giants, prior 'Earn' program issues (fully resolved, users received 100% of assets back), promotes altcoins, custodial risk. </span> </p> <p class="platform-link"> --- a/bitcoin-wallet.html +++ b/bitcoin-wallet.html @@ -10,7 +10,7 @@ <meta content="https://cheatsheets.davidveksler.com/images/bitcoin-og.png" itemprop="image"/> <link href="https://cheatsheets.davidveksler.com/bitcoin-wallet.html" itemprop="mainEntityOfPage"/> <meta content="David Veksler" itemprop="author"/> -<meta content="2024-05-23" itemprop="dateModified"/> +<meta content="2026-06-21" itemprop="dateModified"/> <link href="data:image/svg+xml,<svg viewBox='0 0 100 100'><text y='.9em' font-size='90'>🔑</text></svg>" rel="icon"/> <meta content="Understand Bitcoin wallets, secure your keys with hardware & cold storage, and practice safe self-custody. Covers basics, security, operations, hardware comparisons (Trezor, Coldcard, Ledger), and advanced concepts." name="description"> <link href="https://cheatsheets.davidveksler.com/bitcoin-wallet.html" rel="canonical"> @@ -896,11 +896,11 @@ <div class="col-lg-4 col-md-6"> <div class="info-card btc-type-comparison comparison-item" id="card-compare-trezor"> <div class="card-body"> -<h5><i class="bi bi-unlock-fill"></i> Trezor (Safe 5 / Safe 3 / Model T)</h5> +<h5><i class="bi bi-unlock-fill"></i> Trezor (Safe 7 / Safe 5 / Safe 3)</h5> <div class="card-content-wrapper"> <p class="summary"> -<span class="pros">[+] Long history, Open Source FW (device), User-friendly Suite, Passphrase (All). Safe 5: Large Color Touchscreen, Haptic feedback, Shamir/Enhanced Backup. Safe 3/5: Secure Element Option. Model T: Shamir Backup.</span> -<span class="cons">[-] Safe 3/5 SE firmware is closed source. Model T uses MCU (less physical tamper resistance vs SE). No native air-gap mode (USB required). Safe 5 is higher priced.</span> +<span class="pros">[+] Long history, Open Source FW (device), User-friendly Suite, Passphrase (All), Shamir/Enhanced Backup (Safe 5/7). Safe 7 (flagship, Oct 2025): TROPIC01 secure element, color touchscreen, first hardware wallet with post-quantum signature support. Safe 5: color touchscreen + haptics. Safe 3: budget two-button. All use a Secure Element (EAL6+).</span> +<span class="cons">[-] SE firmware is closed source. No native air-gap mode (USB required). Safe 7 is higher priced (~$249). Older Trezor One & Model T are discontinued (and vulnerable to a voltage-glitching attack).</span> </p> <p><a href="https://trezor.io/" rel="noopener noreferrer" target="_blank">trezor.io</a></p> </div> @@ -910,11 +910,11 @@ <div class="col-lg-4 col-md-6"> <div class="info-card btc-type-comparison comparison-item" id="card-compare-coldcard"> <div class="card-body"> -<h5><i class="bi bi-calculator-fill"></i> Coldcard (Mk4 / Q1)</h5> +<h5><i class="bi bi-calculator-fill"></i> Coldcard (Q / Mk4)</h5> <div class="card-content-wrapper"> <p class="summary"> -<span class="pros">[+] Bitcoin-Only (reduced attack surface), Strong security reputation, True Air-Gap (SD card, NFC, USB-PSBT), Excellent PSBT/Multisig support, Open Source Firmware, Dual Secure Elements (Mk4/Q1), Physical security (PIN, Duress PIN, Brick Me PIN). Q1 adds QWERTY keyboard, larger screen.</span> -<span class="cons">[-] Steeper learning curve than others, Requires coordinator software (e.g., Sparrow, Specter), Basic UI (functional, not fancy), Q1 is larger and more expensive.</span> +<span class="pros">[+] Bitcoin-Only (reduced attack surface), Strong security reputation, True Air-Gap (SD card, NFC, USB-PSBT), Excellent PSBT/Multisig support, Open Source Firmware, Dual Secure Elements (Mk4/Q), Physical security (PIN, Duress PIN, Brick Me PIN). Q adds a QWERTY keyboard, QR scanner, and larger screen.</span> +<span class="cons">[-] Steeper learning curve than others, Requires coordinator software (e.g., Sparrow, Specter), Basic UI (functional, not fancy), Q is larger and more expensive.</span> </p> <p><a href="https://coldcard.com/" rel="noopener noreferrer" target="_blank">coldcard.com</a></p> </div> @@ -938,11 +938,11 @@ <div class="col-lg-4 col-md-6"> <div class="info-card btc-type-comparison comparison-item" id="card-compare-ledger"> <div class="card-body"> -<h5><i class="bi bi-usb-fill"></i> Ledger (Nano S+ / Nano X / Stax)</h5> +<h5><i class="bi bi-usb-fill"></i> Ledger (Nano S+ / Nano X / Nano Gen5 / Flex / Stax)</h5> <div class="card-content-wrapper"> <p class="summary"> -<span class="pros">[+] Uses Secure Element (SE) chip, Wide Coin Support, Popular/Well-known brand, Polished Ledger Live companion app (Desktop/Mobile), Bluetooth (Nano X).</span> -<span class="cons">[-] Closed Source device firmware & SE firmware, Requires trust in vendor. Controversial 'Ledger Recover' service (opt-in seed fragment backup). Past *customer data* breach (not keys). Heavy reliance on Ledger Live app. Multi-coin support increases code complexity/attack surface vs Bitcoin-only. Stax significantly delayed.</span> +<span class="pros">[+] Uses Secure Element (SE) chip, Wide Coin Support, Popular/Well-known brand, Polished Ledger Live companion app (Desktop/Mobile), Bluetooth (Nano X/Gen5), E-Ink touchscreens (Flex/Stax). Stax & Flex shipped 2024; touchscreen Nano Gen5 (NFC) added 2026.</span> +<span class="cons">[-] Closed Source device firmware & SE firmware, Requires trust in vendor. Controversial 'Ledger Recover' service (opt-in seed fragment backup). Past *customer data* breach (not keys). Heavy reliance on Ledger Live app. Multi-coin support increases code complexity/attack surface vs Bitcoin-only.</span> </p> <p><a href="https://www.ledger.com/" rel="noopener noreferrer" target="_blank">ledger.com</a></p> </div> @@ -994,11 +994,11 @@ <div class="col-lg-4 col-md-6"> <div class="info-card btc-type-comparison comparison-item" id="card-compare-passport"> <div class="card-body"> -<h5><i class="bi bi-passport-fill"></i> Foundation Passport (Batch 2)</h5> +<h5><i class="bi bi-passport-fill"></i> Foundation Passport (Core / Prime)</h5> <div class="card-content-wrapper"> <p class="summary"> -<span class="pros">[+] Premium build quality, Bitcoin-focused, Air-Gapped via QR/SD card, Strong security emphasis, Open Source FW.</span> -<span class="cons">[-] Higher price point, Relies on companion app/coordinator SW.</span> +<span class="pros">[+] Premium build quality, Bitcoin-focused, Air-Gapped via QR/SD card, Strong security emphasis, Open Source FW. The classic device is now "Passport Core"; "Passport Prime" (2025, ~$299) adds a color touchscreen and broader security (2FA, FIDO keys, encrypted file vault) on its Rust-based KeyOS.</span> +<span class="cons">[-] Higher price point, Relies on companion app/coordinator SW. Prime is a newer, broader device (more attack surface than a Bitcoin-only signer).</span> </p> <p><a href="https://foundationdevices.com/" rel="noopener noreferrer" target="_blank">foundationdevices.com</a></p> </div> @@ -1391,8 +1391,9 @@ </a> </div> <p class="mb-2"> - © 2025 David Veksler · Compiled & expanded based on open-source wallet documentation and security audits. + © 2026 David Veksler · Compiled & expanded based on open-source wallet documentation and security audits. </p> + <p class="mb-2"><strong>Last verified: 2026-06-21.</strong> Hardware-wallet lineups (Trezor, Ledger, Coldcard, Foundation) reflect models shipping as of June 2026; wallet concepts & security practices are evergreen.</p> <div> <a class="mx-2 link-secondary" href="https://www.linkedin.com/in/davidveksler/" target="_blank" title="David Veksler on LinkedIn"> <i class="bi bi-linkedin"></i> --- a/boom-supersonic.html +++ b/boom-supersonic.html @@ -233,7 +233,7 @@ "name": "David Veksler Cheatsheets" }, "datePublished": "2025-12-02", - "dateModified": "2025-12-02", + "dateModified": "2026-06-21", "keywords": "Boom Supersonic, Overture, XB-1, Symphony Engine, Sustainable Aviation Fuel" } </script> @@ -304,7 +304,7 @@ </p> <div class="mt-3"> <span class="badge bg-secondary me-2"> - Last Updated: Dec 2025 + Last Updated: June 2026 </span> <span class="badge bg-primary"> Mach 1.7 @@ -587,7 +587,7 @@ Carbon Fiber </span> <span class="spec-tag"> - First Flight: Mar 2024 + Supersonic: Jan 2025 </span> </div> <button aria-expanded="false" class="btn btn-accent btn-sm details-toggle" data-bs-target="#xb1Details" data-bs-toggle="collapse" type="button"> @@ -639,9 +639,9 @@ </li> <li> <strong> - Supersonic: + Supersonic Flights: </strong> - Broke the sound barrier (Mach 1.0+) in test program (2025). + Jan 28, 2025 — reached Mach 1.12 (750 mph) on first supersonic flight; Feb 10, 2025 — reached Mach 1.18 on second supersonic flight. Six total sound-barrier crossings (3 per flight), all without audible sonic boom reaching the ground (Boomless Cruise). XB-1 program retired after completing 13 flights. </li> <li> <strong> @@ -696,7 +696,7 @@ Purpose-Built Supersonic Propulsion </h5> <span class="badge bg-warning text-dark"> - 35,000 lbs Thrust + 40,000 lbs Thrust </span> </div> <p> @@ -869,13 +869,19 @@ <strong> Goal: </strong> - Net zero carbon emissions by 2025 (Operational) and for Overture fleet. + Net zero carbon emissions for Overture fleet operations. </li> <li> <strong> Noise: </strong> - "Community Noise" compliant (subsonic over land, quiet takeoff). + "Community Noise" compliant (quiet takeoff; Boomless Cruise over land). + </li> + <li> + <strong> + Boomless Cruise / Overland Rules: + </strong> + Jun 2025 — Trump executive order directed FAA to lift 52-year overland supersonic ban for aircraft that produce no audible boom. Mar 2026 — U.S. House passed the Supersonic Aviation Modernization Act (SAM) by voice vote, requiring FAA to revise rules within one year. Overture's Boomless Cruise targets up to Mach 1.3 over land with no audible boom. </li> </ul> </div> @@ -921,18 +927,29 @@ </div> <div class="timeline-item"> <div class="timeline-date"> - 2024-2025 + Jun 2024 </div> <p> - Superfactory Construction (Greensboro, NC) & XB-1 Supersonic Tests. + Superfactory construction complete — ribbon-cutting at Piedmont Triad International Airport, Greensboro, NC. Facility sits unfilled pending Overture production start. </p> </div> <div class="timeline-item"> <div class="timeline-date"> - 2026 (Target) + Jan–Feb 2025 + </div> + <p class="text-white"> + <strong> + XB-1 breaks sound barrier. + </strong> + Jan 28: Mach 1.12; Feb 10: Mach 1.18. Six total supersonic crossings (3 per flight) with no audible boom reaching the ground (Boomless Cruise). XB-1 retired after 13 flights total. + </p> + </div> + <div class="timeline-item"> + <div class="timeline-date"> + 2026 (Active) </div> <p> - Symphony Engine Full-Scale Core Tests. + Symphony engine sprint-core assembly and validation campaign underway at Colorado Air & Space Port test site. Full-scale integrated turbine prototype targeted for assembly by end of 2026. </p> </div> <div class="timeline-item"> @@ -940,16 +957,16 @@ 2027 (Target) </div> <p> - Overture Aircraft Rollout. + Overture aircraft rollout; Symphony engine operational readiness (H1 2027). </p> </div> <div class="timeline-item"> <div class="timeline-date"> - 2029-2030 (Target) + 2028–2029 (Target) </div> <p class="text-accent"> <strong> - Type Certification & Commercial Entry into Service. + Overture first flight (2028); Type Certification & Commercial Entry into Service (2029). </strong> </p> </div> @@ -1026,6 +1043,9 @@ <p class="mb-2"> © 2025 David Veksler · Compiled & expanded based on aerospace engineering documentation. </p> + <p class="mb-2 small"> + Last verified: 2026-06-21 + </p> <div> <a class="mx-2 link-secondary" href="https://www.linkedin.com/in/davidveksler/" target="_blank" title="David Veksler on LinkedIn"> <i class="bi bi-linkedin"></i> --- a/clean-architecture-dotnet.html +++ b/clean-architecture-dotnet.html @@ -29,7 +29,7 @@ "author": { "@type": "Person", "name": "David Veksler (AI Generated)" }, "publisher": { "@type": "Organization", "name": "David Veksler Cheatsheets" }, "datePublished": "2025-06-10", - "dateModified": "2025-06-10", + "dateModified": "2026-06-21", "keywords": "Clean Architecture Introduction, Why Clean Architecture, .NET, Web API, ASP.NET Core, C#, Software Architecture, DDD, Best Practices, Visual Studio Setup" } </script> @@ -416,7 +416,7 @@ <header class="page-header"> <h1><i class="bi bi-layers-half"></i> Clean Architecture in .NET Web API</h1> <p class="lead">Core principles, layer responsibilities, project structure, C# examples, and best practices for building robust and maintainable .NET Web APIs using Clean Architecture.</p> -<p class="text-muted small">Last Updated: <span id="lastUpdatedDate">June 10, 2025</span></p> +<p class="text-muted small">Last Updated: <span id="lastUpdatedDate">June 2026</span></p> </header> <main class="container"> <div class="global-controls"> @@ -876,9 +876,9 @@ YourProjectSolution.sln <div class="card-body"> <ul> <li><strong><span class="term" data-bs-toggle="tooltip" title="A design pattern where objects receive their dependencies from an external source rather than creating them internally. Crucial for Clean Architecture.">Dependency Injection (DI)</span>:</strong> Absolutely crucial. Register dependencies in the Presentation layer's `Program.cs` (the Composition Root). Use constructor injection primarily.</li> -<li><strong><span class="term" data-bs-toggle="tooltip" title="A popular library for in-process messaging that helps implement CQRS and Mediator patterns, decoupling senders from handlers.">MediatR</span>:</strong> Widely used for implementing CQRS in the Application layer. It helps decouple command/query senders from their handlers and allows for cross-cutting concerns via pipeline behaviors.</li> -<li><strong><span class="term" data-bs-toggle="tooltip" title="A .NET library for creating strongly-typed validation rules, often used in Application layer for command/query validation.">FluentValidation</span>:</strong> A popular library for robust validation in the Application layer, often integrated with MediatR pipelines.</li> -<li><strong><span class="term" data-bs-toggle="tooltip" title="A library for object-to-object mapping, useful for converting between Entities, DTOs, and API Models.">AutoMapper</span> (or similar):</strong> Useful for mapping between Entities, DTOs, and API Models. Define profiles in the Application layer or where the mapping is most relevant.</li> +<li><strong><span class="term" data-bs-toggle="tooltip" title="A popular library for in-process messaging that helps implement CQRS and Mediator patterns, decoupling senders from handlers.">MediatR</span>:</strong> Widely used for implementing CQRS in the Application layer. It helps decouple command/query senders from their handlers and allows for cross-cutting concerns via pipeline behaviors. <strong>Licensing note (as of 2025):</strong> MediatR v12+ moved to a commercial model under LuckyPennySoftware. It remains free for individuals and organisations with under $5M annual revenue; larger enterprises require a paid license registered at MediatR.io. Latest stable: v14.1.0.</li> +<li><strong><span class="term" data-bs-toggle="tooltip" title="A .NET library for creating strongly-typed validation rules, often used in Application layer for command/query validation.">FluentValidation</span>:</strong> A popular library for robust validation in the Application layer, often integrated with MediatR pipelines. Remains MIT-licensed and open source. Latest stable: v12.1.1.</li> +<li><strong><span class="term" data-bs-toggle="tooltip" title="A library for object-to-object mapping, useful for converting between Entities, DTOs, and API Models.">AutoMapper</span> (or similar):</strong> Useful for mapping between Entities, DTOs, and API Models. Define profiles in the Application layer or where the mapping is most relevant. <strong>Licensing note (as of 2025):</strong> AutoMapper v15+ also moved to a commercial model under LuckyPennySoftware with the same tiered free/paid structure (free under $5M revenue). Latest stable: v16.1.1. MIT-licensed alternatives such as <a href="https://mapperly.riok.app/" rel="noopener noreferrer" target="_blank">Mapperly</a> (source-generator based) are widely adopted as free replacements.</li> <li><strong><span class="term" data-bs-toggle="tooltip" title="A pattern that groups multiple repository operations into a single transaction, often implemented within the DbContext in the Infrastructure layer. An IUnitOfWork interface is defined in the Application layer.">Unit of Work (UoW) Pattern</span>:</strong> Often implemented in the Infrastructure layer (e.g., within the `DbContext`). An `IUnitOfWork` interface can be defined in the Application layer to be consumed by command handlers.</li> <li><strong>Error Handling:</strong> Implement a global error handling middleware in the Presentation layer to catch exceptions and return consistent API error responses. Define custom exceptions in Domain and Application layers for specific business or application errors.</li> <li><strong><span class="term" data-bs-toggle="tooltip" title="A pattern in .NET for managing strongly-typed configuration settings, typically loaded from appsettings.json or environment variables.">Configuration (Options Pattern)</span>:</strong> Use the Options pattern (`IOptions<t>`) for strongly-typed configuration, typically configured in the Presentation layer and injected where needed.</t></li> @@ -911,7 +911,7 @@ YourProjectSolution.sln if (lastUpdatedDateSpan) { const today = new Date(); // Will reflect the current date on load const jsonLdScript = document.querySelector('script[type="application/ld+json"]'); - let datePublished = "2025-06-10"; // Default fallback from original script + let datePublished = "2026-06-21"; // Default fallback from original script if (jsonLdScript) { try { const jsonData = JSON.parse(jsonLdScript.textContent); @@ -1012,7 +1012,7 @@ YourProjectSolution.sln </a> </div> <p class="mb-2"> - © 2025 David Veksler · Compiled & expanded based on Robert C. Martin's architectural patterns and .NET implementation guides. + © 2026 David Veksler · Compiled & expanded based on Robert C. Martin's architectural patterns and .NET implementation guides. </p> <div> <a class="mx-2 link-secondary" href="https://www.linkedin.com/in/davidveksler/" target="_blank" title="David Veksler on LinkedIn"> --- a/compression-algorithms.html +++ b/compression-algorithms.html @@ -637,6 +637,7 @@ <h6>Use Cases:</h6> <p>Default for 7-Zip (<code>.7z</code>), XZ Utils (<code>.xz</code>). Software distribution, large archives.</p> <h6>Strengths:</h6> <p>Very high compression ratios.</p> <h6>Weaknesses:</h6> <p>Slow compression, high memory usage. Decompression is faster but not top-tier.</p> +<h6>Security Note:</h6> <p><strong>CVE-2024-3094 (XZ Utils backdoor):</strong> Versions 5.6.0–5.6.1 of XZ Utils were found to contain a deliberate supply-chain backdoor (discovered March 2024). Affected systems should downgrade to ≤5.5.x. Stable versions post-5.6.1 are unaffected.</p> <h6>File Extensions:</h6> <p><code>.7z</code>, <code>.xz</code></p> </div> </div> @@ -717,9 +718,9 @@ </div> <div class="collapse collapse-content" id="collapseZstd"> <h6>Core Idea:</h6> <p>Combines an LZ77-variant with a fast entropy stage (Finite State Entropy - FSE, an Asymmetric Numeral System variant).</p> -<h6>Use Cases:</h6> <p>General-purpose, databases (MySQL, RocksDB), file systems (ZFS, Btrfs), real-time, archives (<code>.tar.zst</code>).</p> -<h6>Strengths:</h6> <p>Very fast compression/decompression, flexible levels, good ratios, dictionary support.</p> -<h6>Weaknesses:</h6> <p>Newer, so adoption still growing vs. Deflate (though rapidly).</p> +<h6>Use Cases:</h6> <p>General-purpose, databases (MySQL, RocksDB), file systems (ZFS, Btrfs), real-time, archives (<code>.tar.zst</code>). Now default in Arch/Fedora/Debian packages, Linux kernel modules, and Python 3.14 stdlib (PEP 784 accepted 2025).</p> +<h6>Strengths:</h6> <p>Very fast compression/decompression, flexible levels, good ratios, dictionary support. Widely adopted as default in major Linux distros, package managers, and filesystems.</p> +<h6>Weaknesses:</h6> <p>Slightly lower maximum compression ratio than LZMA2 at equivalent effort. Not universally available on older systems without installation.</p> <h6>File Extensions:</h6> <p><code>.zst</code></p> </div> </div> @@ -919,7 +920,7 @@ <h6>Core Idea:</h6> <p>Leverages AV1 video compression techniques for still images, stored in HEIF container.</p> <h6>Use Cases:</h6> <p>Web images, aiming for superior quality/ratio over JPEG/WebP.</p> <h6>Strengths:</h6> <p>Significantly better compression than JPEG/WebP. Supports HDR, wide color gamut, lossless, animation. Royalty-free.</p> -<h6>Weaknesses:</h6> <p>Newer, software/browser support still growing. Can be computationally demanding.</p> +<h6>Weaknesses:</h6> <p>Encoding can be computationally demanding (hardware encoders now in NVIDIA/AMD/Apple M4+ chips). ~10% of browsers still lack support; use <code><picture></code> with JPEG fallback for full coverage.</p> <h6>Parameters:</h6> <p>Quality setting (quantizer), speed/effort.</p> <h6>File Extensions:</h6> <p><code>.avif</code></p> </div> @@ -1017,7 +1018,7 @@ <h6>Core Idea:</h6> <p>Advanced techniques: larger superblocks, sophisticated prediction, CDEF/loop restoration filters.</p> <h6>Use Cases:</h6> <p>Web streaming (YouTube, Netflix, Twitch), real-time communications (WebRTC).</p> <h6>Strengths:</h6> <p>Excellent compression (better than HEVC), royalty-free. Apple hardware decoding from A17 Pro/M3 chips.</p> -<h6>Weaknesses:</h6> <p>Very computationally intensive to encode (improving), decode can also be heavy without hardware support.</p> +<h6>Weaknesses:</h6> <p>Software encoding is CPU-intensive (SVT-AV1 4.0, released Jan 2026, has improved speed significantly). Hardware encoding now available on NVIDIA RTX 40-series, AMD RX 7000-series, and Apple M5 Pro/Max chips.</p> <h6>Parameters:</h6> <p>Bitrate, quality settings (CRF), speed presets.</p> <h6>File Extensions:</h6> <p><code>.mkv</code>, <code>.webm</code>, <code>.mp4</code> (with ISOBMFF)</p> </div> @@ -1519,8 +1520,9 @@ </a> </div> <p class="mb-2"> - © 2025 David Veksler · Compiled & expanded based on computer science textbooks and codec technical specifications. + © 2026 David Veksler · Compiled & expanded based on computer science textbooks and codec technical specifications. </p> + <p class="mb-2 text-muted small">Last verified: 2026-06-21</p> <div> <a class="mx-2 link-secondary" href="https://www.linkedin.com/in/davidveksler/" target="_blank" title="David Veksler on LinkedIn"> <i class="bi bi-linkedin"></i> --- a/databases.html +++ b/databases.html @@ -1691,6 +1691,9 @@ <li> Eventual consistency across replicas/cluster nodes. </li> + <li> + <strong>License change (March 2024):</strong> Redis Ltd. relicensed Redis from BSD to a dual RSAL/SSPLv1 model (neither OSI-approved as open source). In response, the Linux Foundation and major cloud providers (AWS, Google, Oracle) launched <a href="https://valkey.io/" rel="noopener noreferrer" target="_blank">Valkey</a>, a BSD-licensed community fork starting from Redis 7.2.4. As of 2026, Ubuntu 26.04 LTS, Fedora 42, and Debian 13 default to Valkey. Redis later added AGPLv3 as a third license option (May 2025). Evaluate both projects when choosing a deployment. + </li> </ul> <h6> Use Cases @@ -4063,7 +4066,7 @@ document.addEventListener('DOMContentLoaded', () => { </a> </div> <p class="mb-2"> - © 2025 David Veksler · Compiled & expanded based on relational database theory and NoSQL database documentation. + © 2026 David Veksler · Compiled & expanded based on relational database theory and NoSQL database documentation. Last verified: 2026-06-21. </p> <div> <a class="mx-2 link-secondary" href="https://www.linkedin.com/in/davidveksler/" target="_blank" title="David Veksler on LinkedIn"> --- a/dotnet-cheatsheet.html +++ b/dotnet-cheatsheet.html @@ -3,35 +3,35 @@ <head> <meta charset="UTF-8"> <meta name="viewport" content="width=device-width, initial-scale=1.0"> - <title>Interactive .NET & C# Cheatsheet: Modern Ecosystem & Language Guide</title> + <title>Interactive .NET & C# Cheatsheet: Modern Ecosystem & Language Guide (.NET 10, C# 14)</title> <link rel="icon" href="data:image/svg+xml,<svg xmlns=%22http://www.w3.org/2000/svg%22 viewBox=%220 0 100 100%22><text y=%22.9em%22 font-size=%2290%22>#️⃣</text></svg>"> <!-- SEO Meta Description --> - <meta name="description" content="Comprehensive and interactive cheatsheet for the .NET ecosystem and C# language. 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Your go-to .NET cheatsheet visual."> <meta property="og:site_name" content="David Veksler Cheatsheets"> <meta property="article:published_time" content="2023-01-15T09:00:00Z"> - <meta property="article:modified_time" content="2025-05-10T10:00:00Z"> + <meta property="article:modified_time" content="2026-06-21T10:00:00Z"> <meta property="article:author" content="https://www.linkedin.com/in/davidveksler/"> <!-- Twitter Card Metadata --> <meta name="twitter:card" content="summary_large_image"> <meta name="twitter:title" content="Interactive .NET & C# Cheatsheet: Modern Frameworks & Language Guide"> - <meta name="twitter:description" content="Explore the .NET platform, C# language (C# 13), ASP.NET Core, MAUI, EF Core, and more with this visual guide for modern .NET developers and architects (up to .NET 9)."> + <meta name="twitter:description" content="Explore the .NET platform, C# language (C# 14), ASP.NET Core, MAUI, EF Core, and more with this visual guide for modern .NET developers and architects (up to .NET 10)."> <meta name="twitter:image" content="https://cheatsheets.davidveksler.com/images/dotnet-cheatsheet.png"> <meta name="twitter:image:alt" content="Visual overview of the .NET and C# ecosystem for developers. Highlights frameworks like ASP.NET Core, MAUI, and core language features."> <meta name="twitter:creator" content="@heroiclife"> @@ -41,8 +41,8 @@ { "@context": "https://schema.org", "@type": "TechArticle", - "headline": "Interactive .NET & C# Language Cheatsheet - Modern Ecosystem Overview (.NET 9, C# 13)", - "description": "A comprehensive and interactive cheatsheet for the .NET ecosystem and C# language, covering modern .NET versions (up to .NET 9), key C# 13 features, major components, libraries, frameworks (ASP.NET Core, MAUI, EF Core), and tooling for senior developers and architects.", + "headline": "Interactive .NET & C# Language Cheatsheet - Modern Ecosystem Overview (.NET 10, C# 14)", + "description": "A comprehensive and interactive cheatsheet for the .NET ecosystem and C# language, covering modern .NET versions (up to .NET 10), key C# 14 features, major components, libraries, frameworks (ASP.NET Core, MAUI, EF Core), and tooling for senior developers and architects.", "image": "https://cheatsheets.davidveksler.com/images/dotnet-cheatsheet.png", "author": { "@type": "Person", @@ -58,12 +58,12 @@ } }, "datePublished": "2023-01-15T09:00:00Z", - "dateModified": "2025-05-10T10:00:00Z", + "dateModified": "2026-06-21T10:00:00Z", "mainEntityOfPage": { "@type": "WebPage", "@id": "https://cheatsheets.davidveksler.com/dotnet-cheatsheet.html" }, - "keywords": ".NET, C#, Cheatsheet, .NET Core, .NET 9, C# 13, ASP.NET Core, MAUI, EF Core, C# Language Features, .NET SDK, .NET Runtime, LINQ, Async Programming, Visual Studio, NuGet, .NET Architecture, Software Development, Programming Guide" + "keywords": ".NET, C#, Cheatsheet, .NET Core, .NET 10, C# 14, ASP.NET Core, MAUI, EF Core, C# Language Features, .NET SDK, .NET Runtime, LINQ, Async Programming, Visual Studio, NuGet, .NET Architecture, Software Development, Programming Guide" } </script> @@ -309,7 +309,7 @@ <body> <header class="page-header"> <h1><i class="bi bi-box-seam" aria-hidden="true" data-bs-toggle="tooltip" data-bs-placement="bottom" title=".NET Ecosystem Icon"></i> .NET & C# Language Cheatsheet</h1> - <p class="lead">An interactive guide to modern .NET components, C# language features, frameworks, and libraries for architects & senior developers (Covering .NET 9 & C# 13).</p> + <p class="lead">An interactive guide to modern .NET components, C# language features, frameworks, and libraries for architects & senior developers (Covering .NET 10 & C# 14).</p> </header> <div class="container"> @@ -462,7 +462,7 @@ <div class="col-lg-4 col-md-6"> <div class="info-card card-csharp" id="card-csharp-overview"> <div class="card-body"> - <h5><i class="bi bi-code-slash" aria-hidden="true" data-bs-toggle="tooltip" data-bs-placement="top" title="C# Code Icon"></i> C# Language <span class="version-tag" data-bs-toggle="tooltip" data-bs-placement="top" title="C# is an evolving language, currently up to version 13.">C# 1.0 - 13</span></h5> + <h5><i class="bi bi-code-slash" aria-hidden="true" data-bs-toggle="tooltip" data-bs-placement="top" title="C# Code Icon"></i> C# Language <span class="version-tag" data-bs-toggle="tooltip" data-bs-placement="top" title="C# is an evolving language, currently up to version 14.">C# 1.0 - 14</span></h5> <div class="card-content-wrapper"> <p class="summary">A modern, object-oriented, and type-safe programming language. Key to .NET development, offering powerful features for building diverse applications. <a href="https://learn.microsoft.com/en-us/dotnet/csharp/" target="_blank" rel="noopener noreferrer" data-bs-toggle="tooltip" data-bs-placement="top" title="External link: Official C# Guide">C# Guide</a></p> <button class="btn btn-sm details-toggle" type="button" data-bs-toggle="collapse" data-bs-target="#collapseCsharpOverview" aria-expanded="false" aria-controls="collapseCsharpOverview" data-bs-toggle="tooltip" data-bs-placement="top" title="Show/hide more details about the C# Language"> @@ -480,7 +480,7 @@ <li><strong data-bs-toggle="tooltip" data-bs-placement="top" title="Designed to facilitate the creation and use of self-contained, reusable software components.">Component-Oriented:</strong> Based on software components with properties, methods, and events.</li> <li><strong data-bs-toggle="tooltip" data-bs-placement="top" title="All types, including primitive types, inherit from a single root 'object' type, providing consistency.">Unified Type System:</strong> All C# types inherit from a single root `object` type.</li> <li><strong data-bs-toggle="tooltip" data-bs-placement="top" title="Automatic memory management frees developers from manual memory allocation and deallocation.">Garbage Collection:</strong> Automatic memory management simplifies development.</li> - <li><strong data-bs-toggle="tooltip" data-bs-placement="top" title="C# is continuously updated with new features and improvements to enhance developer productivity and program capabilities.">Evolving Language:</strong> Regularly updated with new features to enhance productivity and capabilities (e.g., .NET 9 / C# 13). <a href="https://learn.microsoft.com/en-us/dotnet/csharp/whats-new/csharp-13" target="_blank" rel="noopener noreferrer" data-bs-toggle="tooltip" data-bs-placement="top" title="External link: What's New in C# 13">What's New in C# 13</a></li> + <li><strong data-bs-toggle="tooltip" data-bs-placement="top" title="C# is continuously updated with new features and improvements to enhance developer productivity and program capabilities.">Evolving Language:</strong> Regularly updated with new features to enhance productivity and capabilities (e.g., .NET 10 / C# 14). <a href="https://learn.microsoft.com/en-us/dotnet/csharp/whats-new/csharp-14" target="_blank" rel="noopener noreferrer" data-bs-toggle="tooltip" data-bs-placement="top" title="External link: What's New in C# 14">What's New in C# 14</a></li> </ul> </div> </div> @@ -539,7 +539,7 @@ <div class="col-lg-4 col-md-6"> <div class="info-card card-csharp" id="card-csharp-pattern-matching"> <div class="card-body"> - <h5><i class="bi bi-grid-3x3-gap" aria-hidden="true" data-bs-toggle="tooltip" data-bs-placement="top" title="Pattern Matching Icon"></i> Pattern Matching <span class="version-tag" data-bs-toggle="tooltip" data-bs-placement="top" title="Pattern matching features have been progressively added from C# 7 through C# 13 and beyond.">C# 7-13+</span></h5> + <h5><i class="bi bi-grid-3x3-gap" aria-hidden="true" data-bs-toggle="tooltip" data-bs-placement="top" title="Pattern Matching Icon"></i> Pattern Matching <span class="version-tag" data-bs-toggle="tooltip" data-bs-placement="top" title="Pattern matching features have been progressively added from C# 7 through C# 14 and beyond.">C# 7-14+</span></h5> <div class="card-content-wrapper"> <p class="summary">Enhanced control flow based on the "shape" of data using <span class="term" data-bs-toggle="tooltip" data-bs-placement="top" title="C# expression used for type testing, often combined with pattern matching to declare a new variable of the tested type if the match succeeds.">is</span> expressions and <span class="term" data-bs-toggle="tooltip" data-bs-placement="top" title="Control flow constructs that allow branching based on matching an input expression against various patterns.">switch expressions/statements</span>. <a href="https://learn.microsoft.com/en-us/dotnet/csharp/fundamentals/functional/pattern-matching" target="_blank" rel="noopener noreferrer" data-bs-toggle="tooltip" data-bs-placement="top" title="External link: Pattern Matching in C#">Pattern Matching</a></p> <button class="btn btn-sm details-toggle" type="button" data-bs-toggle="collapse" data-bs-target="#collapseCsharpPatternMatching" aria-expanded="false" aria-controls="collapseCsharpPatternMatching" data-bs-toggle="tooltip" data-bs-placement="top" title="Show/hide more details about Pattern Matching"> @@ -1147,7 +1147,7 @@ <ul> <li><strong>Class Libraries:</strong> Package reusable code into DLLs.</li> <li><strong data-bs-toggle="tooltip" data-bs-placement="top" title=".NET Standard is a specification of APIs. Libraries targeting a .NET Standard version can be used by any .NET implementation (like .NET Framework, .NET Core, Mono/Xamarin) that supports that version or higher. It's less critical for new libraries targeting only modern .NET.">.NET Standard (Legacy):</strong> A formal specification of .NET APIs intended to be available on all .NET implementations. Useful for libraries targeting multiple .NET runtimes (e.g., .NET Framework and .NET Core). <a href="https://learn.microsoft.com/en-us/dotnet/standard/net-standard" target="_blank" rel="noopener noreferrer" data-bs-toggle="tooltip" data-bs-placement="top" title="External link: .NET Standard Documentation">.NET Standard Docs</a></li> - <li><strong data-bs-toggle="tooltip" data-bs-placement="top" title="For libraries intended only for modern .NET (e.g., .NET 6, .NET 7, .NET 8, .NET 9), targeting a specific .NET version (e.g., 'net9.0') is the recommended approach, providing access to the latest APIs.">Modern .NET Targeting:</strong> For new libraries, targeting `netX.Y` (e.g., `net9.0`) is often sufficient.</li> + <li><strong data-bs-toggle="tooltip" data-bs-placement="top" title="For libraries intended only for modern .NET (e.g., .NET 8, .NET 9, .NET 10), targeting a specific .NET version (e.g., 'net10.0') is the recommended approach, providing access to the latest APIs.">Modern .NET Targeting:</strong> For new libraries, targeting `netX.Y` (e.g., `net10.0`) is often sufficient.</li> </ul> </div> </div> @@ -1578,8 +1578,9 @@ document.addEventListener('DOMContentLoaded', () => { </a> </div> <p class="mb-2"> - © 2025 David Veksler · Compiled & expanded based on Microsoft official documentation and C# programming guides. + © 2026 David Veksler · Compiled & expanded based on Microsoft official documentation and C# programming guides. </p> + <p class="mb-2 text-muted" style="font-size:0.8em;">Last verified: 2026-06-21</p> <div> <a class="mx-2 link-secondary" href="https://www.linkedin.com/in/davidveksler/" target="_blank" title="David Veksler on LinkedIn"> <i class="bi bi-linkedin"></i> --- a/future-of-warfare-technology.html +++ b/future-of-warfare-technology.html @@ -23,7 +23,7 @@ { "@context": "https://schema.org", "@type": "TechArticle", - "headline": "Future of Warfare Technology Cheatsheet 2025", + "headline": "Future of Warfare Technology Cheatsheet 2026", "description": "A strategic reference describing the interplay of autonomy, swarms, EW, trusted compute, logistics automation, and counter-space capabilities over the next 30 years.", "author": { "@type": "Person", @@ -34,7 +34,7 @@ "name": "David Veksler Cheatsheets" }, "datePublished": "2025-02-14", - "dateModified": "2025-02-14", + "dateModified": "2026-06-21", "keywords": "future warfare,future military technology,autonomous weapons,electronic warfare,edge AI,swarm drones,trusted compute" } </script> @@ -748,8 +748,9 @@ </a> </div> <p class="mb-2"> - © 2025 David Veksler · Compiled & expanded based on defense research publications and military technology trend analysis. + © 2026 David Veksler · Compiled & expanded based on defense research publications and military technology trend analysis. </p> + <p class="mb-2 small text-muted">Last verified: 2026-06-21</p> <div> <a class="mx-2 link-secondary" href="https://www.linkedin.com/in/davidveksler/" target="_blank" title="David Veksler on LinkedIn"> <i class="bi bi-linkedin"></i> --- a/geoengineering-approaches.html +++ b/geoengineering-approaches.html @@ -20,7 +20,7 @@ <meta name="language" content="English"> <meta name="revisit-after" content="7 days"> <meta property="article:published_time" content="2025-11-08T00:00:00Z"> - <meta property="article:modified_time" content="2025-11-08T00:00:00Z"> + <meta property="article:modified_time" content="2026-06-21T00:00:00Z"> <meta property="article:author" content="David Veksler"> <meta property="article:section" content="Climate Science"> <meta property="article:tag" content="Geoengineering"> @@ -60,7 +60,7 @@ "url": "https://cheatsheets.davidveksler.com" }, "datePublished": "2025-11-08", - "dateModified": "2025-11-08", + "dateModified": "2026-06-21", "keywords": "geoengineering, climate engineering, carbon dioxide removal, solar radiation management, direct air capture, enhanced rock weathering, BECCS, stratospheric aerosol injection, marine cloud brightening, climate change mitigation, climate cost comparison", "image": "https://cheatsheets.davidveksler.com/images/geoengineering-approaches.png", "mainEntityOfPage": { @@ -569,7 +569,7 @@ <div class="subsection"> <h4><i class="bi bi-arrow-up-right"></i> Technological Readiness & Scalability</h4> - <p>DAC is transitioning from pilot projects to early commercial-scale operations. Major projects, like Occidental's <em>Stratos</em> facility in Texas, are designed to capture up to <strong>500,000 tonnes of CO₂ per year</strong> and are expected to be operational by 2025. The scalability potential is significant, but DAC faces major hurdles, including very high energy consumption and the need for low-carbon energy sources and widespread CO₂ transport/storage infrastructure.</p> + <p>DAC is transitioning from pilot projects to early commercial-scale operations. Occidental's <em>Stratos</em> facility in Texas — built in two phases, each adding 250,000 t/yr — is designed to capture up to <strong>500,000 tonnes of CO₂ per year</strong> at full capacity. Phase 1 began initial operations in Q2 2026; Phase 2 commissioning is underway with full ramp-up targeted by end of 2026. The scalability potential is significant, but DAC faces major hurdles, including very high energy consumption and the need for low-carbon energy sources and widespread CO₂ transport/storage infrastructure.</p> </div> <div class="subsection"> @@ -578,7 +578,7 @@ <strong>Current Deployment Cost:</strong> <span class="cost-badge cost-high">$600 - $1,000+ per tonne CO₂</span> </div> - <p>Current operational costs are extremely high. Climeworks (a leading DAC firm) charges around $1,000–$1,500 per tonne for carbon removal. At this price point, removing 1 million tonnes of CO₂ would cost <strong>$600M - $1.5B</strong>. Government subsidies like the U.S. 45Q tax credit (up to $180/ton) currently make projects more viable for early philanthropic support.</p> + <p>Current operational costs are extremely high. Climeworks (a leading DAC firm) charges around $600–$1,200 per tonne for carbon removal. At this price point, removing 1 million tonnes of CO₂ would cost <strong>$600M - $1.2B</strong>. Government subsidies like the U.S. 45Q tax credit (up to $180/ton for geological storage, maintained under the One Big Beautiful Bill Act of July 2025) currently make projects more viable for early philanthropic support.</p> <div class="mt-3 mb-3"> <strong>Projected Future Cost (at scale):</strong> @@ -787,7 +787,7 @@ <div class="alert alert-info mt-3"> <strong><i class="bi bi-balloon"></i> Real-World Example: Make Sunsets</strong> - <p class="mb-0">A private startup has begun <strong>launching stratospheric balloons carrying SO₂</strong>. Make Sunsets (USA) has lofted dozens of latex weather balloons, each releasing a few grams of SO₂ in the upper atmosphere. This DIY approach (started with <$50,000 in funding) demonstrates the low barrier to entry at experimental scales. As of 2024, Make Sunsets claimed to have released about <strong>53 kg of SO₂</strong> in total, via over 160 balloon launches.</p> + <p class="mb-0">A private startup has begun <strong>launching stratospheric balloons carrying SO₂</strong>. Make Sunsets (USA) has lofted latex weather balloons, each releasing a few grams of SO₂ in the upper atmosphere. This DIY approach (started with <$50,000 in funding) demonstrates the low barrier to entry at experimental scales. As of mid-2025, Make Sunsets claimed to have released about <strong>0.1 tonnes (~100 kg) of SO₂</strong> in total, via over 200 balloon launches. In April 2025 the U.S. EPA requested information from the company to evaluate whether its activities fall under the Clean Air Act.</p> </div> <p>The logistics of a full-scale deployment involve tens of thousands of flights per year by a fleet of aircraft operating from multiple bases around the world. Scaling SAI is more about political/governance readiness than hardware: <em>if</em> society decided to do it, the aircraft and materials could be deployed within a few years.</p> @@ -977,7 +977,7 @@ <p class="lead">Comparative analysis of geoengineering approaches versus traditional climate interventions, focused on cost per tonne CO₂ removed or offset across all deployment scales.</p> <div class="alert alert-info mb-3"> - <strong><i class="bi bi-info-circle"></i> "Solving" Climate Change Definition:</strong> For comparison purposes, "solve" means removing <strong>500 gigatonnes (Gt) of CO₂</strong> to reverse warming from current ~1.3°C to ~1.0°C above pre-industrial levels, OR providing equivalent cooling indefinitely. This represents roughly one-third of total anthropogenic emissions and a realistic target for significant climate reversal. + <strong><i class="bi bi-info-circle"></i> "Solving" Climate Change Definition:</strong> For comparison purposes, "solve" means removing <strong>500 gigatonnes (Gt) of CO₂</strong> to reverse warming from current ~1.4–1.5°C to ~1.0°C above pre-industrial levels, OR providing equivalent cooling indefinitely. This represents roughly one-third of total anthropogenic emissions and a realistic target for significant climate reversal. </div> <div class="table-responsive"> @@ -1230,9 +1230,10 @@ }); </script> <footer class="container text-center pb-3"> - <p class="mb-2"> - © 2025 David Veksler · Compiled & expanded based on atmospheric science research and climate intervention studies. + <p class="mb-1"> + © 2026 David Veksler · Compiled & expanded based on atmospheric science research and climate intervention studies. </p> + <p class="mb-2 text-muted" style="font-size:0.85rem;">Last verified: 2026-06-21</p> <div> <a class="mx-2 link-secondary" href="https://www.linkedin.com/in/davidveksler/" target="_blank" title="David Veksler on LinkedIn"> <i class="bi bi-linkedin"></i> --- a/git-scm.html +++ b/git-scm.html @@ -1147,8 +1147,9 @@ Thumbs.db</code></pre> </a> </div> <p class="mb-2"> - © 2025 David Veksler · Compiled & expanded based on official Git documentation and distributed version control guides. + © 2026 David Veksler · Compiled & expanded based on official Git documentation and distributed version control guides. </p> + <p class="mb-2 text-muted" style="font-size:0.85em;">Last verified: 2026-06-21 · Current Git release: 2.54.0 (2026-04-20)</p> <div> <a class="mx-2 link-secondary" href="https://www.linkedin.com/in/davidveksler/" target="_blank" title="David Veksler on LinkedIn"> <i class="bi bi-linkedin"></i> --- a/google-ai-studio-guide.html +++ b/google-ai-studio-guide.html @@ -15,6 +15,7 @@ { "@context": "https://schema.org", "@type": "FAQPage", + "dateModified": "2026-06-21", "mainEntity": [{ "@type": "Question", "name": "What is Temperature in Google AI Studio?", @@ -430,7 +431,7 @@ </div> <div class="page-header-text"> <h1>Google AI Studio</h1> -<p class="lead">Enhanced Settings Cheatsheet</p> +<p class="lead">Enhanced Settings Cheatsheet · June 2026</p> </div> </div> <div class="header-actions"> @@ -458,10 +459,11 @@ <h5><i class="bi bi-robot"></i> Model</h5> <p class="summary">Choose the foundational model for your task. Models vary in capabilities (reasoning, creativity), context window size, speed, and cost.</p> <select aria-label="Model select" class="form-select mb-2" id="modelSelect"> -<option value="gemini-1.0-pro">Gemini 1.0 Pro (Balanced)</option> -<option selected="" value="gemini-2.5-pro-preview">Gemini 2.5 Pro Preview 05-06 (Advanced)</option> -<option value="gemini-1.5-flash">Gemini 1.5 Flash (Fast & Efficient)</option> -<option value="gemini-1.5-pro-experimental">Gemini 1.5 Pro (Experimental)</option> +<option selected="" value="gemini-3.5-flash">Gemini 3.5 Flash (Default — Frontier performance)</option> +<option value="gemini-3.1-pro-preview">Gemini 3.1 Pro Preview (Advanced reasoning & agents)</option> +<option value="gemini-2.5-pro">Gemini 2.5 Pro (Complex tasks, deep reasoning)</option> +<option value="gemini-2.5-flash">Gemini 2.5 Flash (Best price-performance)</option> +<option value="gemini-3.1-flash-lite">Gemini 3.1 Flash-Lite (High-volume, low-latency)</option> </select> <button class="btn btn-sm btn-outline-info mb-3 w-100" data-bs-target="#modelCompareModal" data-bs-toggle="modal"><i class="bi bi-columns-gap"></i> Quick Compare Models</button> <button aria-controls="collapseModel" aria-expanded="false" class="btn btn-sm details-toggle" data-bs-target="#collapseModel" data-bs-toggle="collapse" type="button"> @@ -895,41 +897,54 @@ <thead> <tr> <th>Feature</th> -<th>Gemini 1.5 Flash</th> -<th>Gemini 1.0 Pro</th> -<th>Gemini 2.5 Pro Preview</th> +<th>Gemini 3.1 Flash-Lite</th> +<th>Gemini 3.5 Flash</th> +<th>Gemini 2.5 Pro</th> +<th>Gemini 3.1 Pro Preview</th> </tr> </thead> <tbody> <tr> <td><strong>Primary Use Case</strong></td> -<td>High speed, efficiency, high volume tasks</td> -<td>Balanced performance and capability</td> -<td>Advanced reasoning, complex tasks, latest features</td> +<td>High-volume, low-cost, low-latency tasks</td> +<td>Default: frontier performance, agentic & coding tasks</td> +<td>Complex reasoning, deep analysis, coding</td> +<td>Advanced reasoning, multi-step agents, coding</td> </tr> <tr> <td><strong>Context Window</strong></td> -<td>Large (e.g., 1M tokens)</td> -<td>Standard (e.g., 32k tokens)</td> -<td>Very Large (e.g., 1M+ tokens, up to 2M in image)</td> +<td>1M tokens (1,048,576)</td> +<td>1M tokens (1,048,576)</td> +<td>1M tokens (1,048,576)</td> +<td>1M tokens (1,048,576)</td> +</tr> +<tr> +<td><strong>Max Output</strong></td> +<td>65,536 tokens</td> +<td>65,536 tokens</td> +<td>65,536 tokens</td> +<td>65,536 tokens</td> </tr> <tr> <td><strong>Speed</strong></td> -<td>Fastest</td> +<td>Fastest / most cost-efficient</td> +<td>Fast (GA default)</td> <td>Moderate</td> -<td>Moderate to Fast (for its power)</td> +<td>Moderate (Preview)</td> </tr> <tr> <td><strong>Cost Indication</strong></td> -<td>Lower</td> -<td>Medium</td> -<td>Higher (Preview pricing may apply)</td> +<td>Lowest</td> +<td>Low–Medium</td> +<td>Higher</td> +<td>Higher (Preview pricing)</td> </tr> <tr> <td><strong>Strengths</strong></td> -<td>Chat, summarization, RAG at scale</td> -<td>General purpose, content generation, instruction following</td> -<td>Complex problem solving, multi-modal understanding, code gen</td> +<td>Translation, transcription, classification at scale</td> +<td>General purpose, agents, code gen, multimodal</td> +<td>Deep data analysis, long-document understanding, complex code</td> +<td>Grounded reasoning, precise tool use, agentic workflows</td> </tr> </tbody> </table> @@ -1012,17 +1027,11 @@ // Token Estimator & Progress Bar let maxTokens = 1048576; // Default, can be updated by model select if needed - if (modelSelect) { // Update maxTokens based on model (conceptual) + if (modelSelect) { // Update maxTokens based on model (verified June 2026: all current models = 1M input) const updateMaxTokensForModel = () => { const selectedModel = modelSelect.value; - // This is a simplified mapping; actual limits vary and are complex - if (selectedModel.includes("2.5-pro") || selectedModel.includes("1.5-pro")) { - maxTokens = 1048576 * 2; // From UI image, token limit of model is 2M - } else if (selectedModel.includes("flash")) { - maxTokens = 1048576; - } else { - maxTokens = 32768; // Older Gemini 1.0 Pro - } + // All current Gemini models (2.5+, 3.x) share a 1,048,576-token input limit + maxTokens = 1048576; tokenCountDisplay.textContent = `${currentTokens} / ${maxTokens.toLocaleString()}`; updateTokenProgress(); }; @@ -1221,7 +1230,10 @@ </a> </div> <p class="mb-2"> - © 2025 David Veksler · Compiled & expanded based on Google's official resources and developer guides. + © 2026 David Veksler · Compiled & expanded based on Google's official resources and developer guides. + </p> + <p class="mb-2" style="font-size:0.8rem; color: var(--ai-studio-text-tertiary);"> + Last verified: 2026-06-21 · Model lineup sourced from <a href="https://ai.google.dev/gemini-api/docs/models" target="_blank" rel="noopener noreferrer">ai.google.dev/gemini-api/docs/models</a> </p> <div> <a class="mx-2 link-secondary" href="https://www.linkedin.com/in/davidveksler/" target="_blank" title="David Veksler on LinkedIn"> --- a/housing-comparison.html +++ b/housing-comparison.html @@ -55,7 +55,7 @@ "name": "David Veksler Cheatsheets" }, "datePublished": "2025-01-07", - "dateModified": "2025-01-07", + "dateModified": "2026-06-21", "keywords": "housing comparison, real estate budget, luxury housing, apartment amenities, home features, housing calculator" } </script> @@ -857,7 +857,10 @@ </a> </div> <p class="mb-2"> - © 2025 David Veksler · Compiled & expanded based on real estate data, rental market statistics, and homeownership cost comparisons. + © 2026 David Veksler · Compiled & expanded based on real estate data, rental market statistics, and homeownership cost comparisons. + </p> + <p class="mb-2 text-muted" style="font-size:0.8rem;"> + Last verified: 2026-06-21 · Mortgage rate ~6.47% (Freddie Mac PMMS Jun 2026) · US median existing-home price ~$429K (NAR May 2026) · National median asking rent ~$1,895/mo (Zillow Jan 2026) </p> <div> <a class="mx-2 link-secondary" href="https://www.linkedin.com/in/davidveksler/" target="_blank" title="David Veksler on LinkedIn"> --- a/humanoid-robots.html +++ b/humanoid-robots.html @@ -4,24 +4,24 @@ <meta charset="utf-8"/> <meta content="width=device-width, initial-scale=1.0" name="viewport"/> <title> - Humanoid Robot Builders Cheatsheet (Updated November 2025) + Humanoid Robot Builders Cheatsheet (Updated June 2026) </title> <link href="data:image/svg+xml,<svg xmlns=%22http://www.w3.org/2000/svg%22 viewBox=%220 0 100 100%22><text y=%22.9em%22 font-size=%2290%22>🤖</text></svg>" rel="icon"/> <!-- SEO Meta Description --> - <meta content="A comprehensive cheatsheet for understanding major companies building humanoid robots: Boston Dynamics, Tesla, Figure AI, Agility Robotics, Sanctuary AI, Apptronik, Unitree Robotics, 1X Technologies, Engineered Arts, Fourier Intelligence, and UBTECH Robotics. Covers their philosophy, origin, key robots, funding, and recent developments as of November 2025." name="description"/> - <meta content="Humanoid Robots, Robotics, AI, Boston Dynamics, Tesla Optimus, Figure AI, Agility Robotics, Sanctuary AI, Apptronik, Unitree Robotics, 1X Technologies, Engineered Arts, Fourier Intelligence, UBTECH Robotics, Atlas, Digit, Apollo, Ameca, GR-1, Walker S, CyberOne, Robotics Companies, Automation, Future of Work, November 2025" name="keywords"/> + <meta content="A comprehensive cheatsheet for understanding major companies building humanoid robots: Boston Dynamics, Tesla, Figure AI, Agility Robotics, Sanctuary AI, Apptronik, Unitree Robotics, 1X Technologies, Engineered Arts, Fourier Intelligence, and UBTECH Robotics. Covers their philosophy, origin, key robots, funding, and recent developments as of June 2026." name="description"/> + <meta content="Humanoid Robots, Robotics, AI, Boston Dynamics, Tesla Optimus, Figure AI, Agility Robotics, Sanctuary AI, Apptronik, Unitree Robotics, 1X Technologies, Engineered Arts, Fourier Intelligence, UBTECH Robotics, Atlas, Digit, Apollo, Ameca, GR-1, Walker S, CyberOne, Robotics Companies, Automation, Future of Work, June 2026" name="keywords"/> <!-- Canonical URL (Update if hosted) --> <link href="https://cheatsheets.davidveksler.com/humanoid-robots.html" rel="canonical"/> <!-- Social Media Metadata (Add URLs if needed) --> - <meta content="Humanoid Robot Builders Cheatsheet (November 2025 Update)" property="og:title"/> - <meta content="Explore the philosophies, origins, key robots, funding, and target applications of leading humanoid robot companies like Boston Dynamics, Tesla, Figure AI, UBTECH Robotics, and more. Updated November 2025." property="og:description"> + <meta content="Humanoid Robot Builders Cheatsheet (June 2026 Update)" property="og:title"/> + <meta content="Explore the philosophies, origins, key robots, funding, and target applications of leading humanoid robot companies like Boston Dynamics, Tesla, Figure AI, UBTECH Robotics, and more. Updated June 2026." property="og:description"> <meta content="website" property="og:type"/> <meta content="https://cheatsheets.davidveksler.com/humanoid-robots.html" property="og:url"/> <!-- Replace with a relevant image for humanoid robots --> <meta content="Humanoid Robot Builders Cheatsheet - Collage of Advanced Humanoid Robots" property="og:image:alt"/> <meta content="summary_large_image" name="twitter:card"/> - <meta content="Humanoid Robot Builders Cheatsheet (November 2025 Update)" name="twitter:title"/> - <meta content="Explore the philosophies, origins, key robots, funding, and target applications of leading humanoid robot companies. Updated November 2025." name="twitter:description"/> + <meta content="Humanoid Robot Builders Cheatsheet (June 2026 Update)" name="twitter:title"/> + <meta content="Explore the philosophies, origins, key robots, funding, and target applications of leading humanoid robot companies. Updated June 2026." name="twitter:description"/> <!-- Replace with a relevant image for humanoid robots --> <meta content="Humanoid Robot Builders Cheatsheet - Collage of Advanced Humanoid Robots" name="twitter:image:alt"/> <meta content="@heroiclife" name="twitter:creator"/> @@ -30,7 +30,7 @@ { "@context": "https://schema.org", "@type": "TechArticle", - "headline": "Humanoid Robot Builders Cheatsheet (Updated November 2025)", + "headline": "Humanoid Robot Builders Cheatsheet (Updated June 2026)", "description": "A comprehensive cheatsheet for understanding major companies building humanoid robots: Boston Dynamics, Tesla, Figure AI, Agility Robotics, Sanctuary AI, Apptronik, Unitree Robotics, 1X Technologies, Engineered Arts, Fourier Intelligence, and UBTECH Robotics. Covers their philosophy, origin, key robots, funding, and recent developments.", "author": { "@type": "Person", @@ -41,7 +41,7 @@ "name": "David Veksler Cheatsheets" }, "datePublished": "2024-01-15", - "dateModified": "2025-11-08", + "dateModified": "2026-06-21", "keywords": "Humanoid Robots, Robotics, AI, Boston Dynamics, Tesla Optimus, Figure AI, Agility Robotics, Sanctuary AI, Apptronik, Unitree Robotics, 1X Technologies, Atlas, Digit, Apollo, NEO, Ameca, Phoenix, Automation, Future of Work" } </script> @@ -516,7 +516,7 @@ A cheatsheet exploring major companies developing advanced humanoid robots, their philosophies, key robots, funding, recent developments, and target applications. </p> <p class="last-updated"> - Last Updated: November 2025 + Last Updated: June 2026 · Last verified: 2026-06-21 </p> </header> <div class="container" id="main-container"> @@ -829,15 +829,15 @@ <h5> <i class="bi bi-newspaper"> </i> - Recent Developments (2024-2025) + Recent Developments (2024-2026) </h5> <div class="card-content-wrapper"> <p class="summary"> - The new all-electric + The all-electric <span class="term"> Atlas </span> - , unveiled in April 2024, demonstrated autonomous sorting of engine parts in October 2024 using vision-based recognition. In October 2024, Boston Dynamics partnered with Toyota Research Institute for joint robotics research. In February 2025, they partnered with the Robotics & AI Institute for reinforcement learning training pipelines. In March 2025, they expanded collaboration with NVIDIA to integrate the Isaac GR00T platform using Jetson Thor computing. In August 2025, Boston Dynamics and TRI demonstrated Large Behavior Model integration, a significant step toward general-purpose humanoid assistants. + demonstrated autonomous sorting of engine parts in October 2024. In August 2025, Boston Dynamics and TRI demonstrated Large Behavior Model integration. At CES 2026 (January 2026), Boston Dynamics unveiled a production-ready version of Atlas and announced production had begun at its Boston headquarters. All 2026 production units are fully committed to Hyundai (primary customer) and Google DeepMind (AI research partnership). Hyundai is planning a dedicated Atlas manufacturing facility targeting 30,000 units/year by 2028. External customers must wait until 2027 for delivery. </p> <button aria-expanded="false" class="btn btn-sm details-toggle" data-bs-target="#collapseBostonDynamicsDevelopments" data-bs-toggle="collapse" type="button"> Details @@ -889,9 +889,21 @@ </li> <li> <strong> - Hyundai Partnership: + Production-Ready Atlas at CES 2026 (January 2026): + </strong> + Boston Dynamics unveiled a production-ready Atlas and confirmed production had started at its Boston headquarters. All 2026 output is fully committed; external customers must wait until 2027. + </li> + <li> + <strong> + Google DeepMind Partnership (2026): + </strong> + Google DeepMind is receiving Atlas units as part of an embodied AI research collaboration. + </li> + <li> + <strong> + Hyundai Manufacturing Scale-Up: </strong> - Planned deployment with Hyundai and other innovative customers to test and iterate Atlas applications over coming years. + Hyundai is the primary commercial customer and is planning a dedicated Atlas manufacturing facility targeting 30,000 units/year capacity by 2028. </li> </ul> </div> @@ -956,11 +968,11 @@ <span class="term"> Optimus </span> - (also referred to as Tesla Bot). Currently demonstrating Gen 2, with + (also referred to as Tesla Bot). Gen 2 deployed internally at scale. <span class="term"> Optimus Gen 3 </span> - anticipated with design updates and potential sales starting late 2025 or 2026. + publicly showcased at AWE Shanghai (March 2026); formal reveal pending. Production start targeted late 2026 at Fremont factory (converted from Model S/X line). 2026 production target: 50,000–100,000 units. External sales expected 2027. </li> <li> <strong> @@ -1035,7 +1047,7 @@ <strong> Scalable Manufacturing: </strong> - Designing Optimus for mass production, aiming to make it affordable over time. Tesla aims to produce over 1,000 units for internal use in 2025 and scale to 50,000 in 2026. + Designing Optimus for mass production, aiming to make it affordable over time. Tesla produced ~1,000 units internally in 2025 (Gen 2). Gen 3 production targets 50,000–100,000 units in 2026, with a long-term 1 million units/year run-rate at Fremont. </li> <li> <strong> @@ -1196,7 +1208,7 @@ <h5> <i class="bi bi-newspaper"> </i> - Recent Developments (2024-2025) + Recent Developments (2025-2026) </h5> <div class="card-content-wrapper"> <p class="summary"> @@ -1204,11 +1216,11 @@ <span class="term"> Optimus </span> - prototypes by mid-2025, many deployed in battery production workshops. Production targets were revised from 10,000 to 5,000 units during 2025. In June 2025, Optimus program head Milan Kovac resigned and was replaced by Ashok Elluswamy from autopilot teams. + units by mid-2025 (Gen 2), deployed internally in battery production. Ashok Elluswamy replaced Milan Kovac as Optimus program head in June 2025. <span class="term"> Optimus Gen 3 </span> - unveiling was delayed to early 2026 (February/March) due to major redesign addressing overheating, hand-load capacity, gearbox lifespans, and battery life. Gen 3 features highly dexterous hands with 22 degrees of freedom. Tesla aims to build 1-million-unit-per-year production line in Fremont with long-term target price around $20,000. + was publicly shown at AWE Shanghai in March 2026 (Elon Musk described it as in "final stages" at the March 2026 Abundance Summit); walking confirmed March 31, 2026. Formal reveal to come closer to production start. Fremont factory (converted from Model S/X line, both discontinued Q2 2026) is targeting Gen 3 production start in late July–August 2026, with a 2026 target of 50,000–100,000 units and a long-term 1 million units/year run-rate. External commercial sales expected to begin 2027. Long-term target price: ~$20,000. </p> </div> </div> @@ -1271,19 +1283,19 @@ Flagship Robots: </strong> <span class="term"> - Figure 01 + Figure 02 </span> , <span class="term"> - Figure 02 + Figure 03 </span> - . + (introduced October 2025; current production model). </li> <li> <strong> Valuation: </strong> - ~$2.6 billion (as of early 2024). Potentially seeking $1.5B at a $39.5B valuation in early 2025. + ~$39 billion (Series C closed September 2025, raised $1B+; total funding ~$1.9B). </li> <li> <strong> @@ -1403,13 +1415,13 @@ <div class="card-content-wrapper"> <p class="summary"> <span class="term"> - Figure 01 + Figure 02 </span> - was their initial prototype. + was their industrial deployment model (used in the BMW Spartanburg pilot). <span class="term"> - Figure 02 + Figure 03 </span> - is their more advanced humanoid, designed for industrial use with enhanced mobility, dexterity, and AI capabilities, including highly flexible, human-like fingers. Figure's robots are powered by their in-house AI ( + (October 2025) is the current production model, featuring twice the camera frame rate, 60% wider field of view, cameras in each hand, and fingertip tactile sensors sensitive to 3 grams of force. Figure's robots are powered by their in-house AI ( <span class="term"> Helix </span> @@ -1501,7 +1513,7 @@ </h5> <div class="card-content-wrapper"> <p class="summary"> - Raised $70 million in a Series A round in May 2023. In early 2024, secured around $675 million in a funding round including investments from Jeff Bezos (through Physical Intelligence), Microsoft, Nvidia, OpenAI, and Intel Capital, valuing the company at approximately $2.6 billion. Reports in early 2025 suggested Figure AI was eyeing an additional $1.5 billion in funding at a potential valuation of $39.5 billion. Has partnerships with OpenAI and BMW for AI development and deployment testing. + Raised $675 million Series B in early 2024 (investors: OpenAI, Nvidia, Microsoft, Jeff Bezos, Intel Capital) at ~$2.6 billion valuation. Closed Series C in September 2025 raising $1B+ at a $39 billion post-money valuation; investors include NVIDIA, Microsoft, OpenAI Startup Fund, Brookfield Asset Management, and Jeff Bezos. Total funding ~$1.9 billion. Has partnerships with OpenAI and BMW for AI development and deployment. </p> </div> </div> @@ -1513,11 +1525,15 @@ <h5> <i class="bi bi-newspaper"> </i> - Recent Developments (2024-2025) + Recent Developments (2024-2026) </h5> <div class="card-content-wrapper"> <p class="summary"> - Figure AI announced commercial partnership with BMW in January 2024 to deploy humanoids at Spartanburg, South Carolina facility. BMW successfully completed pilot in 2024 where Figure 02 inserted sheet metal parts with millimeter-level accuracy, achieving up to 1,000 placements per day. As of August 2024, no robots remained at plant after pilot concluded. Limited deployment resumed in January 2025 with single Figure 02 operating during production hours in body shop as of March 2025. Figure AI raised $675 million Series B funding led by OpenAI, Nvidia, Microsoft, and Jeff Bezos, valued at $2.6 billion. Company expects to manufacture roughly 100,000 units within four years. + BMW Spartanburg pilot (Figure 02) concluded with 30,000+ X3 vehicles supported, 90,000+ parts handled, 1,250+ operating hours. Figure AI introduced + <span class="term"> + Figure 03 + </span> + in October 2025 with twice the camera frame rate, 60% wider FOV, hand cameras, and fingertip tactile sensors. Series C closed September 2025 at $39B valuation ($1B+ raised; total funding ~$1.9B). BotQ factory scaled from ~60 robots/month (February 2026) to ~240/month (April 2026) — one robot every 90 minutes. By May 2026, 350+ Figure 03 units produced. BMW is expanding deployment to Plant Leipzig, Germany (summer 2026), its first European humanoid pilot. Company targets 100,000 robots/year production within four years. </p> </div> </div> @@ -1592,7 +1608,7 @@ <strong> Valuation: </strong> - Potentially $1.75 billion pre-investment ahead of an anticipated $400M funding round in April 2025. + ~$2.12 billion (Series C closed early 2025, $400M raised, led by WP Global Partners with SoftBank Group participation; total funding ~$641M). </li> <li> <strong> @@ -1769,7 +1785,7 @@ </h5> <div class="card-content-wrapper"> <p class="summary"> - Agility Robotics has raised significant funding, including a $150 million Series B round in 2022 with investors like DCVC, Playground Global, and Amazon's Industrial Innovation Fund. In April 2025, reports indicated the company was set to secure an additional $400 million, led by WP Global Partners with participation from SoftBank Group Corp, which would elevate its pre-investment valuation to $1.75 billion. + Agility Robotics raised a $150 million Series B in 2022 (DCVC, Playground Global, Amazon Industrial Innovation Fund), a further $150M in October 2024 (DCVC-led), and a $400M Series C in early 2025 led by WP Global Partners with SoftBank Group participation, valuing the company at ~$2.12 billion. Total funding ~$641M. Key investors include Amazon Industrial Innovation Fund, NVIDIA Ventures, and Sony Innovation Fund. </p> </div> </div> @@ -1781,15 +1797,14 @@ <h5> <i class="bi bi-newspaper"> </i> - Recent Developments (2024-2025) + Recent Developments (2024-2026) </h5> <div class="card-content-wrapper"> <p class="summary"> - In 2024, <span class="term"> Digit </span> - achieved the first commercial deployment of a humanoid robot at a Spanx facility in Georgia, partnering with GXO Logistics under robotics-as-a-service (RaaS) model. Digit picks up totes from 6 River Systems' Chuck AMRs and places them onto conveyors. Amazon began testing Digit at Seattle robotics research facility for tote recycling tasks. In March 2024, launched Agility Arc cloud automation platform for deploying and managing Digit fleets. First Digits delivered to Agility Partner Program customers in 2024, with general market availability in 2025. Raised $150 million in October 2024 with DCVC leading the round. + moved beyond pilots into live commercial work at Amazon, Toyota Motor Manufacturing Canada (RaaS agreement at Woodstock facility), and GXO Logistics (Atlanta-area facility, operational alongside AMRs). Mercado Libre signed a commercial agreement for Digit deployment in Latin American fulfillment centers. Raised $400M Series C in early 2025 at ~$2.12B valuation. Salem, Oregon manufacturing facility is rated for 10,000+ units/year. Battery life extended to 4 hours; new Safety PLC and Category 1 stop added; redesigned limbs and end effectors launched. </p> </div> </div> @@ -1845,7 +1860,7 @@ <strong> Key Figures: </strong> - Geordie Rose (Co-founder & CEO), Suzanne Gildert (Co-founder & CTO). + Co-founders Geordie Rose and Suzanne Gildert departed November 2024. Company operating under restructured leadership. </li> <li> <strong> @@ -1970,7 +1985,7 @@ </h5> <div class="card-content-wrapper"> <p class="summary"> - Led by co-founders Geordie Rose (CEO), known for his previous work with D-Wave Systems, and Suzanne Gildert (CTO), a prominent researcher in AI and robotics. + Co-founder Geordie Rose was pushed out by the board in November 2024; Suzanne Gildert and two other co-founders also departed at the same time. The company continues to operate under restructured leadership (~163 employees as of April 2026). </p> </div> </div> @@ -2103,15 +2118,7 @@ </h5> <div class="card-content-wrapper"> <p class="summary"> - In April 2024, Sanctuary AI partnered with automotive parts supplier Magna International and unveiled seventh generation of - <span class="term"> - Phoenix - </span> - . During week-long pilot deployment at Mark's retail store in British Columbia, Phoenix Gen 7 completed 110 retail-related tasks, demonstrating ability to learn new tasks in under 24 hours. Sanctuary AI secured over $140 million in funding from investors including BDC Capital and InBC Funds. Founded in 2018 and headquartered in Vancouver, Canada, company continues advancing - <span class="term"> - Carbon™ - </span> - AI platform for cognitive robotics with human-like behavior and advanced automation capabilities. + In April 2024, Sanctuary AI unveiled Phoenix Gen 7 and partnered with Magna International. Gen 7 completed 110 retail tasks at a Mark's store in BC, learning new tasks in under 24 hours. In November 2024, co-founder Geordie Rose was removed as CEO by the board; Suzanne Gildert and two other co-founders also departed, and ~30 employees were laid off. Total funding ~$148M. As of early 2026, the company is thinly capitalized (a $1.55M micro-round recorded April 2026) with ~163 employees. Has a collaboration with Microsoft and attended Hannover Messe 2025. Company remains operational but faces significant competitive and financial pressure. </p> </div> </div> @@ -2486,14 +2493,18 @@ <strong> Flagship Humanoids: </strong> + <span class="term"> + G1 + </span> + (from $16K, 5,500+ units shipped in 2025), <span class="term"> H1 </span> - , + (research, ~$90K), <span class="term"> - G1 + H2 </span> - (a smaller, more affordable version). + (launched October 2025, $40.9K commercial / $68.9K EDU, bionic face, 2,070 TOPS compute). </li> <li> <strong> @@ -2703,7 +2714,7 @@ </h5> <div class="card-content-wrapper"> <p class="summary"> - Unitree aims to drive robots from the lab to the broader market by drastically reducing costs. While acknowledging the current limitations of AI for complex reasoning, their focus is on creating physically capable and affordable platforms that can be enhanced with improving AI over time. They envision robots becoming more integrated into daily life and aim to bring a breakthrough in humanoid capabilities by 2026. + Unitree aims to drive robots from the lab to the broader market by drastically reducing costs. While acknowledging the current limitations of AI for complex reasoning, their focus is on creating physically capable and affordable platforms that can be enhanced with improving AI over time. They envision robots becoming more integrated into daily life, with the G1 already deployed in commercial and research settings globally and an IPO targeting the Shanghai STAR Market in 2026. </p> </div> </div> @@ -2739,7 +2750,11 @@ <span class="term"> G1 </span> - humanoid robot in 2024 with disruptive $16,000 price point. In June 2025, achieved unicorn status with $1.3 billion valuation after funding round led by ByteDance, Alibaba, and Tencent. Recently opened expanded manufacturing facility in Hangzhou. Showcased G1 and H1 robots performing dance and martial arts movements in early 2025 with improved precision and fluidity from algorithm updates. Agile upgrade for G1 in early 2025 improved mobility and rough terrain navigation. H1 robot runs at 3.3 m/s, making it fastest humanoid on record—nearly twice as fast as most competitors. Showcased at CES 2025 with continued emphasis on mass production readiness and accessibility. + in 2024 (from $16K); shipped 5,500+ G1 units in 2025. Achieved unicorn status June 19, 2025 via Series C at ~$1.7B valuation (12.7B yuan); 2025 revenue 1.7B yuan (+335% YoY). Launched + <span class="term"> + H2 + </span> + in October 2025 ($40.9K commercial, bionic face, 2,070 TOPS). G1 deployed at Tokyo Haneda Airport with Japan Airlines; H1 performed at China's Spring Festival Gala. Filed IPO prospectus on March 20, 2026 targeting Shanghai's STAR Market (~$580–610M raise); regulatory on-site inspection April 2026; listing pending. Pre-IPO valuation target ~$7B. </p> </div> </div> @@ -3035,7 +3050,7 @@ </h5> <div class="card-content-wrapper"> <p class="summary"> - Raised $100 million in a Series B funding round in January 2024, led by EQT Ventures, with participation from Samsung NEXT and existing investors like OpenAI, Tiger Global, and Sandwater. Total funding exceeds $125 million. + Raised $100 million Series B in January 2024 (EQT Ventures lead, Samsung NEXT, OpenAI, Tiger Global, Sandwater). Total funding exceeds $125 million. NEO pre-orders (October 2025) sold out 10,000+ first-year units in five days at $20,000 / $499 monthly. NEO Factory opened Hayward, CA (April 2026). </p> </div> </div> @@ -3051,11 +3066,11 @@ </h5> <div class="card-content-wrapper"> <p class="summary"> - Unveiled + Unveiled NEO Beta (August 2024) and NEO Gamma (February 2025). On October 28, 2025, launched <span class="term"> - NEO Beta + NEO </span> - on August 30, 2024, as prototype bipedal humanoid designed for home use. Introduced NEO Gamma update on February 21, 2025, featuring sleeker design. On October 28, 2025, announced launch of NEO as world's first consumer-ready humanoid robot, available for pre-order at $20,000 or $499/month subscription, with 2026 release. NEO weighs 66 pounds, can lift over 150 pounds and carry 55 pounds, operates at 22dB (quieter than refrigerator). Built with patented Tendon Drive technology for safe, compliant movements. Currently requires teleoperation by remote human operators for specific tasks, with operators able to see inside homes through cameras. Acquired Kind Humanoid in January 2025. Focused on scaling data collection for Embodied AI. + for pre-order as world's first consumer-ready humanoid robot at $20,000 upfront or $499/month subscription — sold out entire first-year production capacity of 10,000+ units in five days. NEO weighs 66 lbs, can lift over 150 lbs, carries 55 lbs, operates at 22 dB. Uses patented Tendon Drive technology; currently requires remote human teleoperation assistance for tasks (not fully autonomous). Opened NEO Factory in Hayward, California (April 30, 2026) — first vertically integrated humanoid robot factory in the U.S. U.S. deliveries targeting late 2026; international expansion from 2027. Acquired Kind Humanoid in January 2025. </p> </div> </div> @@ -4281,7 +4296,10 @@ </a> </div> <p class="mb-2"> - © 2025 David Veksler · Compiled & expanded based on robotics research labs and commercial robotics product announcements. + © 2026 David Veksler · Compiled & expanded based on robotics research labs and commercial robotics product announcements. + </p> + <p class="mb-2" style="font-size:0.8em; color: var(--hr-text-secondary);"> + Last verified: 2026-06-21 </p> <div> <a class="mx-2 link-secondary" href="https://www.linkedin.com/in/davidveksler/" target="_blank" title="David Veksler on LinkedIn"> --- a/javascript-for-architects.html +++ b/javascript-for-architects.html @@ -22,7 +22,7 @@ <meta content="Visual diagram connecting JavaScript core features, React concepts, Vue, Angular, Svelte, Web APIs, and frontend tooling for architects." property="og:image:alt"/> <meta content="David Veksler Cheatsheets" property="og:site_name"/> <meta content="2024-01-20T09:00:00Z" property="article:published_time"/> - <meta content="2025-05-12T11:00:00Z" property="article:modified_time"/> + <meta content="2026-06-21T09:00:00Z" property="article:modified_time"/> <!-- Updated Last Modified --> <meta content="https://www.linkedin.com/in/davidveksler/" property="article:author"/> <!-- Twitter Card Metadata --> @@ -55,7 +55,7 @@ } }, "datePublished": "2024-01-20T09:00:00Z", - "dateModified": "2025-05-12T11:00:00Z", // Updated Last Modified + "dateModified": "2026-06-21T09:00:00Z", // Updated Last Modified "mainEntityOfPage": { "@type": "WebPage", "@id": "https://cheatsheets.davidveksler.com/javascript-for-architects.html" @@ -1561,9 +1561,9 @@ console.log(myCar.speed); // 15 (using getter) </li> <li> <strong> - Public/Private Fields (Experimental): + Public/Private Fields (ES2022): </strong> - `#field` syntax for private instance fields (check browser/Node support). + `#field` syntax for private instance fields. Fully standardized and supported in all modern browsers and Node.js 12+. </li> </ul> <p> @@ -3644,7 +3644,7 @@ function TodoList({ todos }) { <div class="card-content-wrapper"> <p class="summary"> Comprehensive platform for building large-scale apps using TypeScript. Features components, modules, DI, routing, RxJS integration, CLI tooling. Opinionated. - <a href="https://angular.io/" target="_blank"> + <a href="https://angular.dev/" target="_blank"> Angular Docs </a> </p> @@ -3764,9 +3764,9 @@ function TodoList({ todos }) { </li> <li> <strong> - Reactivity: + Reactivity (Svelte 5 Runes): </strong> - Variable assignments (`count = 1`, `user.name = 'X'`) automatically trigger updates where those variables are used. Use `$: ` for reactive declarations/statements. + Svelte 5 (stable Oct 2024) introduced runes: `$state()` for reactive state, `$derived()` for computed values, `$effect()` for side effects. Replaces the older `$:` reactive declarations from Svelte 4. </li> <li> <strong> @@ -4658,7 +4658,7 @@ const { increment } = counterStore; <strong> Vite: </strong> - Modern, extremely fast dev server leveraging native ES Modules. Uses Rollup for production builds. Simpler configuration, opinionated defaults. Excellent DX. + Modern, extremely fast dev server leveraging native ES Modules. Vite 8 (Mar 2026) uses Rolldown (Rust-based, replaces Rollup) for production builds, delivering 10–30x faster build times. Simpler configuration, opinionated defaults. Excellent DX. </li> <li> <strong> @@ -4794,7 +4794,7 @@ const { increment } = counterStore; </p> <p> <em> - Note: Vite handles TS/JSX transformation out-of-the-box during dev using esbuild, and uses Babel/Rollup plugins for production builds if needed. Webpack typically relies more heavily on Babel loaders. + Note: Vite handles TS/JSX transformation out-of-the-box during dev using esbuild. Since Vite 8 (2026), production builds use Rolldown (Rust-based) instead of Rollup; Babel plugins remain available for specific transforms. Webpack typically relies more heavily on Babel loaders. </em> </p> </div> @@ -6297,7 +6297,7 @@ export function getCount() { return count; } </a> </div> <p class="mb-2"> - © 2025 David Veksler · Compiled & expanded based on MDN documentation and modern framework best practices. + © 2026 David Veksler · Compiled & expanded based on MDN documentation and modern framework best practices. Last verified: 2026-06-21. </p> <div> <a class="mx-2 link-secondary" href="https://www.linkedin.com/in/davidveksler/" target="_blank" title="David Veksler on LinkedIn"> --- a/lifestyle-calculator.html +++ b/lifestyle-calculator.html @@ -47,6 +47,7 @@ "@type": "Person", "name": "David Veksler" }, + "dateModified": "2026-06-21", "keywords": "lifestyle calculator, income lifestyle, family budget, what can I afford, salary lifestyle, finance, cost of living, financial planning" } </script> @@ -1616,7 +1617,10 @@ </a> </div> <p class="mb-2"> - © 2025 David Veksler · Compiled & expanded based on publicly available economic data and lifestyle expense research. + © 2026 David Veksler · Compiled & expanded based on publicly available economic data and lifestyle expense research. + </p> + <p class="mb-2 text-muted" style="font-size:0.8rem;"> + Last verified: 2026-06-21 </p> <div> <a class="mx-2 link-secondary" href="https://www.linkedin.com/in/davidveksler/" target="_blank" title="David Veksler on LinkedIn"> --- a/modern-devops-pipelines.html +++ b/modern-devops-pipelines.html @@ -408,7 +408,7 @@ jobs: </h5> <div class="card-content-wrapper"> <p class="summary"> - Use Infrastructure as Code (IaC) with Terraform to define environments. The key to safe CD is a `plan -> approve -> apply` flow with a manual approval gate before any infrastructure is changed. + Use Infrastructure as Code (IaC) to define environments. <strong>OpenTofu</strong> (Linux Foundation, MPL 2.0) is the open-source community standard; <strong>Terraform</strong> (now IBM-owned via HashiCorp, BSL since Aug 2023) remains widely deployed but is no longer open source. The key to safe CD is a <code style="display:inline;padding:0.1em 0.3em;">plan → approve → apply</code> flow with a manual approval gate before any infrastructure is changed. </p> <button class="btn btn-sm btn-outline-secondary details-toggle" data-bs-target="#collapseIac" data-bs-toggle="collapse" type="button"> Details @@ -423,7 +423,7 @@ jobs: <strong> Plan: </strong> - The pipeline runs `terraform plan` and saves the plan file as an artifact. + The pipeline runs <code style="display:inline;padding:0.1em 0.3em;">tofu plan</code> (OpenTofu) or <code style="display:inline;padding:0.1em 0.3em;">terraform plan</code> and saves the plan file as an artifact. </li> <li> <strong> @@ -435,7 +435,7 @@ jobs: <strong> Apply: </strong> - Only after approval does the pipeline run `terraform apply` using the saved plan. + Only after approval does the pipeline run <code style="display:inline;padding:0.1em 0.3em;">tofu apply</code> (OpenTofu) or <code style="display:inline;padding:0.1em 0.3em;">terraform apply</code> using the saved plan. </li> </ul> </div> @@ -465,7 +465,7 @@ jobs: <strong> Helm </strong> - , the package manager for Kubernetes. The `helm upgrade --install` command is the standard for deploying or updating an application. + , the package manager for Kubernetes (v4 is the current stable release as of 2026). The <code style="display:inline;padding:0.1em 0.3em;">helm upgrade --install</code> command is the standard for deploying or updating an application. </p> <h6> For Databases: @@ -581,7 +581,10 @@ jobs: </a> </div> <p class="mb-2"> - © 2025 David Veksler · Compiled & expanded based on continuous integration/delivery best practices and automation framework documentation. + © 2026 David Veksler · Compiled & expanded based on continuous integration/delivery best practices and automation framework documentation. + </p> + <p class="mb-2 text-muted" style="font-size:0.8em;"> + Last verified: 2026-06-21 </p> <div> <a class="mx-2 link-secondary" href="https://www.linkedin.com/in/davidveksler/" target="_blank" title="David Veksler on LinkedIn"> --- a/modern-firearms.html +++ b/modern-firearms.html @@ -32,7 +32,7 @@ "author": {"@type": "Person", "name": "David Veksler (AI Generated)"}, "publisher": {"@type": "Organization", "name": "David Veksler Cheatsheets"}, "datePublished": "2023-10-27", - "dateModified": "2025-09-10", + "dateModified": "2026-06-21", "keywords": ["modern firearms", "firearms guide", "pistol", "rifle", "shotgun", "assault rifle", "firearm safety", "gun types"] } </script> @@ -251,7 +251,7 @@ An interactive guide to the classification, mechanics, and practical considerations of modern firearms. Designed for educational purposes and to promote safe, responsible understanding. </p> <p class="text-muted small"> - Last updated: September 2025 + Last updated: June 2026 </p> </div> </header> @@ -2420,7 +2420,7 @@ Examples </dt> <dd> - M4 Carbine, AKM/AK-74, Steyr AUG + M4 Carbine, M7 (SIG MCX-SPEAR, 6.8×51mm — NGSW, type classified 2024, accelerated fielding FY2026), AKM/AK-74, Steyr AUG </dd> </dl> <h6> @@ -2548,7 +2548,7 @@ Classes </dt> <dd> - LMG/SAW (M249), GPMG (M240), HMG (M2) + LMG/SAW (M249 → M250 replacing, type classified 2025), GPMG (M240), HMG (M2) </dd> </dl> <h6> @@ -2604,7 +2604,7 @@ <h6>Current & Recent Service Pistols</h6> <dl> <dt>U.S. Military</dt> - <dd><b>SIG M17/M18</b> (9mm, striker-fired, 17/21-rd) — Current U.S. military standard since 2017; modular design, excellent ergonomics. <b>Beretta M9/92FS</b> (9mm, DA/SA, 15-rd) — U.S. service pistol 1985-2017; proven reliability, heavy but smooth trigger.</dd> + <dd><b>SIG M17/M18</b> (9mm, striker-fired, 17/21-rd) — Current U.S. military standard since 2017; modular design, excellent ergonomics. Still the DoD standard sidearm as of 2026; no announced replacement. <b>Beretta M9/92FS</b> (9mm, DA/SA, 15-rd) — U.S. service pistol 1985-2017; proven reliability, heavy but smooth trigger.</dd> <dt>U.S. Law Enforcement</dt> <dd><b>Glock 17/19/22</b> (9mm/.40 S&W, striker-fired) — Dominant LE pistol; simple, reliable, extensive aftermarket. <b>SIG P320</b> (9mm/.40, striker-fired, modular) — Growing LE adoption; same platform as M17/M18.</dd> <dt>International Military</dt> @@ -2946,6 +2946,12 @@ Suppressed supersonic rifle shots are still ~130–140 dB — loud, though often hearing‑safe compared to >160 dB unsuppressed. </li> </ul> + <h6> + Regulatory Note (U.S.) + </h6> + <p> + As of <b>January 1, 2026</b>, the $200 NFA transfer tax on suppressors (and SBRs, SBSs, AOWs) was eliminated by the One Big Beautiful Bill Act (H.R. 1, signed July 4, 2025). ATF Form 4 approval, background check, and registration remain required; machine guns and destructive devices still carry the $200 tax. State-level restrictions continue to apply. + </p> <h6> The Takeaway </h6> @@ -3785,7 +3791,10 @@ </a> </div> <p class="mb-2"> - © 2025 David Veksler · Compiled & expanded based on manufacturer documentation and military small arms technical references. + © 2026 David Veksler · Compiled & expanded based on manufacturer documentation and military small arms technical references. + </p> + <p class="mb-2 text-muted small"> + Last verified: 2026-06-21 </p> <div> <a class="mx-2 link-secondary" href="https://www.linkedin.com/in/davidveksler/" target="_blank" title="David Veksler on LinkedIn"> --- a/operator-loadouts.html +++ b/operator-loadouts.html @@ -282,7 +282,7 @@ "url": "https://cheatsheets.davidveksler.com" }, "datePublished": "2024-08-23", - "dateModified": "2024-08-23", + "dateModified": "2026-06-21", "image": "https://cheatsheets.davidveksler.com/images/operator-loadouts.png", "url": "https://cheatsheets.davidveksler.com/operator-loadouts.html", "keywords": [ @@ -1117,7 +1117,7 @@ </code> ), satellite messenger ( <code> - Garmin GPSMAP 66i + Garmin GPSMAP 67i </code> - GPS + 2-way satellite communication) with paper topographic maps and orienteering compass backup ( <code> @@ -1863,11 +1863,11 @@ </strong> Aviation GPS ( <code> - Garmin G430 + Garmin GNS 430 </code> - in aircraft), handheld backup GPS ( + in aircraft — a widely installed legacy unit; display repairs discontinued by Garmin Jan 2024, commonly upgraded to GTN 650Xi), handheld backup GPS ( <code> - Garmin GPSMAP 66i + Garmin GPSMAP 67i </code> ) with satellite messaging, aviation radio ( <code> @@ -1977,7 +1977,11 @@ <code> M27 IAR </code> - - Infantry Automatic Rifle) with ACOG 4x32 optic (TA31), backup iron sights, weapon light (PEQ-15 IR laser), vertical foregrip, sling (Vickers or Blue Force Gear). + - Infantry Automatic Rifle) with ACOG 4x32 optic (TA31), backup iron sights, weapon light (PEQ-15 IR laser), vertical foregrip, sling (Vickers or Blue Force Gear). Note: The Army began fielding the + <code> + M7 rifle + </code> + (SIG MCX Spear, 6.8×51mm, formerly XM7) to close combat units starting in 2024; the M4A1 remains standard issue across most units during this ongoing transition. </li> <li> <strong> @@ -2536,8 +2540,11 @@ Art Of War Sun Tzu </a> </div> + <p class="mb-1"> + Last verified: 2026-06-21 + </p> <p class="mb-2"> - © 2025 David Veksler · Compiled & expanded based on field manuals and special operations equipment documentation. + © 2026 David Veksler · Compiled & expanded based on field manuals and special operations equipment documentation. </p> <div> <a class="mx-2 link-secondary" href="https://www.linkedin.com/in/davidveksler/" target="_blank" title="David Veksler on LinkedIn"> --- a/orbital-rockets-comparison.html +++ b/orbital-rockets-comparison.html @@ -39,7 +39,7 @@ "author": {"@type": "Person", "name": "David Veksler"}, "publisher": {"@type": "Organization", "name": "David Veksler Cheatsheets"}, "datePublished": "2025-11-13", - "dateModified": "2025-11-19", + "dateModified": "2026-06-21", "keywords": "orbital rockets, launch vehicles, spacecraft, Starship, Falcon 9, New Glenn, comparison, specifications", "inLanguage": "en" } @@ -463,7 +463,7 @@ </tr> <tr> <th scope="row"><i class="bi bi-arrow-up"></i> Height</th> - <td>121.3 m (398 ft)</td> + <td>124 m (408 ft)</td> <td>98 m (322 ft)</td> <td>55.4 m (182 ft)</td> <td>~63 m (207 ft)</td> @@ -501,7 +501,7 @@ </tr> <tr> <th scope="row"><i class="bi bi-gear"></i> First Stage Engines</th> - <td>33 Raptors</td> + <td>33 Raptor 3</td> <td>7 BE-4</td> <td>5 RD-191 (1 core + 4 boosters)</td> <td>4 Vulcain 2.1 + 2 Solid</td> @@ -567,7 +567,7 @@ <tr> <th scope="row"><i class="bi bi-play-circle"></i> Status</th> <td><span class="badge bg-warning text-dark">Test Flights</span></td> - <td><span class="badge bg-success">Active</span></td> + <td><span class="badge bg-danger">Grounded</span></td> <td><span class="badge bg-success">Active</span></td> <td><span class="badge bg-success">Active</span></td> <td><span class="badge bg-success">Active</span></td> @@ -595,7 +595,7 @@ <h2 class="mt-5 mb-4" style="color: var(--rocket-primary);"><i class="bi bi-collection"></i> Rocket Profiles</h2> <div class="row" id="rocketCards"> <!-- Starship --> - <div class="col-lg-6 col-xl-4 rocket-item" data-rocket="Starship" data-category="super" data-payload="150000" data-height="121.3" data-year="2023"> + <div class="col-lg-6 col-xl-4 rocket-item" data-rocket="Starship" data-category="super" data-payload="150000" data-height="124" data-year="2023"> <div class="rocket-card"> <img class="rocket-image" loading="lazy" src="https://upload.wikimedia.org/wikipedia/commons/4/4a/SpaceX_Starship_ignition_during_IFT-5.jpg" alt="SpaceX Starship ignites during IFT-5 test flight"> <h3 class="rocket-title"><i class="bi bi-rocket-fill"></i> Starship</h3> @@ -618,12 +618,12 @@ <div class="stat-row"> <i class="bi bi-arrow-up"></i> <span class="stat-label">Height:</span> - <span>121.3 m (398 ft)</span> + <span>124 m (408 ft)</span> </div> <div class="stat-row"> <i class="bi bi-fire"></i> <span class="stat-label">Engines:</span> - <span>33 Raptors</span> + <span>33 Raptor 3</span> </div> <div class="stat-row"> <i class="bi bi-calendar-check"></i> @@ -674,7 +674,7 @@ <span class="stat-label">First Flight:</span> <span>Jan 16, 2025</span> </div> - <p style="font-size: 0.95rem; margin-top: 1rem; color: #ccc;">Blue Origin's heavy-lift competitor with a reusable first stage designed for minimum 25 flights. Part of Amazon's Project Kuiper infrastructure.</p> + <p style="font-size: 0.95rem; margin-top: 1rem; color: #ccc;">Blue Origin's heavy-lift vehicle with a reusable first stage. Flew three times (Jan 2025–Apr 2026) before a static-fire explosion on May 28, 2026 destroyed a vehicle and severely damaged LC-36 at Cape Canaveral. Return to flight is TBD; pad repair may extend into 2027–2028.</p> <div class="rocket-links"> <a href="https://www.blueorigin.com/new-glenn" target="_blank" rel="noopener"><i class="bi bi-globe"></i> Official Site</a> <a href="https://en.wikipedia.org/wiki/New_Glenn" target="_blank" rel="noopener"><i class="bi bi-wikipedia"></i> Wikipedia</a> @@ -1052,7 +1052,10 @@ </a> </div> <p class="mb-2"> - © 2025 David Veksler · Compiled & expanded based on aerospace industry specifications and space launch system technical documentation. + © 2026 David Veksler · Compiled & expanded based on aerospace industry specifications and space launch system technical documentation. + </p> + <p class="mb-2" style="font-size: 0.85rem; color: #666;"> + Last verified: 2026-06-21 </p> <div> <a class="mx-2 link-secondary" href="https://www.linkedin.com/in/davidveksler/" target="_blank" title="David Veksler on LinkedIn"> --- a/p-doom-calculator.html +++ b/p-doom-calculator.html @@ -35,7 +35,7 @@ "author": {"@type": "Person", "name": "David Veksler (AI Generated)"}, "publisher": {"@type": "Organization", "name": "David Veksler Cheatsheets"}, "datePublished": "2025-10-03", - "dateModified": "2025-10-03", + "dateModified": "2026-06-21", "keywords": "p(doom), AI safety, AGI risk, existential risk, artificial intelligence, AI alignment, superintelligence, risk assessment, interactive calculator" } </script> @@ -238,7 +238,7 @@ <p> This interactive calculator helps you estimate your personal probability of an AGI-caused existential catastrophe, known as "p(doom)". Adjust your confidence in various counterarguments to AI doom scenarios based on - <a href="https://www.lesswrong.com/posts/FkAJL8naH9gXsKpwi/poking-holes-in-the-ai-doom-argument" target="_blank" rel="noopener noreferrer">Liron Shapira's analysis</a>. + <a href="https://lironshapira.substack.com/p/poking-holes-in-the-ai-doom-argument" target="_blank" rel="noopener noreferrer">Liron Shapira's analysis</a>. </p> <p class="mb-0"> <strong>How it works:</strong> Start with a 99% base probability of doom. Each category represents potential "off-ramps" @@ -519,7 +519,10 @@ </script> <footer class="container text-center pb-3"> <p class="mb-2"> - © 2025 David Veksler · Compiled & expanded based on probability estimation frameworks and AI risk research. + © 2026 David Veksler · Compiled & expanded based on probability estimation frameworks and AI risk research. + </p> + <p class="mb-2 text-muted" style="font-size:0.85rem;"> + Last verified: 2026-06-21 </p> <div> <a class="mx-2 link-secondary" href="https://www.linkedin.com/in/davidveksler/" target="_blank" title="David Veksler on LinkedIn"> --- a/post-quantum-cryptography.html +++ b/post-quantum-cryptography.html @@ -772,8 +772,7 @@ <p><strong>Type:</strong> Digital Signature Algorithm.</p> <p><strong>Based On:</strong> Lattice cryptography (specifically, NTRU lattices and the Short Integer Solution - SIS problem).</p> -<p><strong>Standardization:</strong> Selected by NIST for future standardization (draft - expected FIPS 206).</p> +<p><strong>Standardization:</strong> NIST submitted the draft FN-DSA standard (FIPS 206) for approval on Aug 28, 2025. Initial Public Draft expected late 2025; final standard anticipated late 2026/early 2027.</p> <h6>Strengths:</h6> <ul> <li><strong>Very Small Signatures:</strong> Falcon's primary advantage is its @@ -861,6 +860,41 @@ </div> </div> </div> +<div class="col-md-6 col-lg-4 mb-4"> +<div class="info-card"> +<div class="card-header"> +<h5><i class="bi bi-shield-plus"></i>HQC (Backup KEM)</h5> +</div> +<div class="card-body"> +<p class="summary">Selected by NIST in March 2025 as a backup Key Encapsulation Mechanism based on error-correcting codes, providing an alternative to ML-KEM if lattice weaknesses emerge.</p> +<button aria-controls="collapseHQCDetail" aria-expanded="false" class="btn btn-sm details-toggle" data-bs-target="#collapseHQCDetail" data-bs-toggle="collapse" type="button"> + Details <i class="bi bi-chevron-down"></i> +</button> +</div> +<div class="collapse collapse-content" id="collapseHQCDetail"> +<p><strong>Type:</strong> Key Encapsulation Mechanism (KEM) — backup / diversity algorithm.</p> +<p><strong>Based On:</strong> QC-MDPC (Quasi-Cyclic Moderate-Density Parity-Check) error-correcting codes — a fundamentally different mathematical foundation from ML-KEM's lattices.</p> +<p><strong>Standardization:</strong> Selected March 11, 2025 (NIST IR 8545). Draft standard expected ~March 2026; final standard anticipated 2027. No FIPS number assigned yet.</p> +<h6>Strengths:</h6> +<ul> +<li><strong>Mathematical Diversity:</strong> Code-based security is independent of lattice hardness assumptions, providing a hedge if ML-KEM is weakened.</li> +<li><strong>Long-Studied Problem:</strong> General decoding of random linear codes has been studied since the 1970s.</li> +<li><strong>Mature Failure Analysis:</strong> Decryption failure rate is well-characterized.</li> +</ul> +<h6>Weaknesses/Considerations:</h6> +<ul> +<li><strong>Backup Role Only:</strong> NIST recommends continuing to migrate to ML-KEM; HQC is not a replacement but an alternative if needed.</li> +<li><strong>Not Yet Finalized:</strong> Deploy ML-KEM now; monitor HQC standardization for future diversity use.</li> +</ul> +<h6>Potential Use Cases:</h6> +<p>High-security environments requiring algorithm diversity; systems that want a hedge against lattice cryptanalysis breakthroughs.</p> +<div class="callout callout-future-watch"> +<h5><i class="bi bi-graph-up-arrow"></i>Deploy ML-KEM Now</h5> +<p>NIST's primary guidance is to migrate to the Aug 2024 finalized standards (FIPS 203/204/205). HQC fills a backup role and will not be final until ~2027.</p> +</div> +</div> +</div> +</div> </div> </section> <!-- Section 4: Hardware Considerations for PQC --> @@ -1975,7 +2009,10 @@ </a> </div> <p class="mb-2"> - © 2025 David Veksler · Compiled & expanded based on NIST standardization process and quantum-resistant cryptographic research. + © 2026 David Veksler · Compiled & expanded based on NIST standardization process and quantum-resistant cryptographic research. + </p> + <p class="mb-2" style="font-size:0.8rem; color: var(--text-secondary);"> + Last verified: 2026-06-21 </p> <div> <a class="mx-2 link-secondary" href="https://www.linkedin.com/in/davidveksler/" target="_blank" title="David Veksler on LinkedIn"> --- a/postgresql.html +++ b/postgresql.html @@ -638,7 +638,7 @@ ORDER BY a.attnum;</code></pre> <button aria-expanded="false" class="btn btn-sm details-toggle" data-bs-target="#collapseMiscTypes" data-bs-toggle="collapse" type="button">Details <i class="bi bi-chevron-down"></i></button></div></div> <div class="collapse collapse-content" id="collapseMiscTypes"> <ul> -<li>`UUID`: Stores Universally Unique Identifiers. Preferred over storing as `text` for efficiency and semantics. Generate using <span class="term"><a href="https://www.postgresql.org/docs/current/functions-uuid.html" target="_blank">`gen_random_uuid()`</a></span> (requires <span class="term"><a href="https://www.postgresql.org/docs/current/pgcrypto.html" target="_blank">`pgcrypto`</a></span> extension) or client-side. <a href="https://www.postgresql.org/docs/current/datatype-uuid.html" target="_blank">[docs]</a></li> +<li>`UUID`: Stores Universally Unique Identifiers. Preferred over storing as `text` for efficiency and semantics. Generate using <span class="term"><a href="https://www.postgresql.org/docs/current/functions-uuid.html" target="_blank">`gen_random_uuid()`</a></span> (built-in since PG13; no extension needed) or client-side. <a href="https://www.postgresql.org/docs/current/datatype-uuid.html" target="_blank">[docs]</a></li> <li>Geometric Types (`point`, `line`, `lseg`, `box`, `path`, `polygon`, `circle`): Basic 2D geometric types. Indexed using GiST. Foundation for the powerful <a href="https://postgis.net/" target="_blank">PostGIS</a> extension. <a href="https://www.postgresql.org/docs/current/datatype-geometric.html" target="_blank">[docs]</a></li> <li>Network Address Types (`cidr`, `inet`, `macaddr`, `macaddr8`): Store and query IP addresses/networks and MAC addresses. Supports subnet containment operators (`>>`, `<<`). Indexable (B-Tree/GiST). <a href="https://www.postgresql.org/docs/current/datatype-net-types.html" target="_blank">[docs]</a></li> <li><a href="https://www.postgresql.org/docs/current/hstore.html" target="_blank">`Hstore`</a> Extension (`CREATE EXTENSION hstore`): Simple key-value store within a column. Keys/values are strings. Indexed using GIN or GiST. Often superseded by JSONB now, but still useful for simpler cases or legacy systems. Operators: `->`, `?`, `@>`.</li> @@ -2690,8 +2690,9 @@ document.addEventListener('DOMContentLoaded', () => { </a> </div> <p class="mb-2"> - © 2025 David Veksler · Compiled & expanded based on official PostgreSQL documentation and query optimization guides. + © 2026 David Veksler · Compiled & expanded based on official PostgreSQL documentation and query optimization guides. </p> + <p class="mb-1 text-muted" style="font-size:0.8em;">Last verified: 2026-06-21</p> <div> <a class="mx-2 link-secondary" href="https://www.linkedin.com/in/davidveksler/" target="_blank" title="David Veksler on LinkedIn"> <i class="bi bi-linkedin"></i> --- a/privacy-data-broker-opt-out.html +++ b/privacy-data-broker-opt-out.html @@ -35,7 +35,7 @@ "author": {"@type": "Person", "name": "David Veksler (AI Generated)"}, "publisher": {"@type": "Organization", "name": "David Veksler Cheatsheets"}, "datePublished": "2024-05-20", - "dateModified": "2024-05-20", + "dateModified": "2026-06-21", "keywords": "data broker opt-out, privacy protection, delete personal info, people search removal, privacy guide" } </script> @@ -238,13 +238,13 @@ <div class="task-header" data-bs-toggle="collapse" data-bs-target="#task1"> <input class="form-check-input task-checkbox" type="checkbox" id="check-task1"> <label class="form-check-label flex-grow-1 fw-bold fs-5" for="check-task1"> - Task 1: PeopleConnect Network <span class="badge bg-secondary ms-2 text-wrap" style="font-size: 0.7rem;">Covers 7 sites (Intelius, TruthFinder, Instant Checkmate, USSearch, ZabaSearch, AnyWho, CheckPeople)</span> + Task 1: PeopleConnect Network <span class="badge bg-secondary ms-2 text-wrap" style="font-size: 0.7rem;">Covers 4 sites (Intelius, TruthFinder, Instant Checkmate, USSearch)</span> </label> <i class="bi bi-chevron-down text-muted"></i> </div> <div id="task1" class="collapse task-content" data-bs-parent="#taskAccordion"> <ol> - <li>Go to <a href="https://www.intelius.com/opt-out" target="_blank" rel="noopener noreferrer" class="external-link">intelius.com/opt-out</a> (Redirects to PeopleConnect Suppression Center).</li> + <li>Go directly to <a href="https://suppression.peopleconnect.us/" target="_blank" rel="noopener noreferrer" class="external-link">suppression.peopleconnect.us</a> (PeopleConnect Suppression Center).</li> <li>Enter the disposable email address.</li> <li>Check email — click the verification link within 15 minutes.</li> <li>Enter your full legal name.</li> @@ -543,7 +543,13 @@ <p class="small mb-2">Major property records aggregator. Opt-out at <a href="https://www.corelogic.com/privacy/" target="_blank" rel="noopener noreferrer" class="external-link">corelogic.com/privacy/</a> under your state's privacy rights.</p> <div class="mt-3 bg-light p-2 rounded small" data-bs-theme="light"> - <strong>State Privacy Laws Leverage:</strong> If you live in a state with comprehensive privacy laws (e.g., California CCPA/CPRA, Colorado CPA, Virginia VCDPA), invoke your state law when submitting deletion requests. It creates a strict legal obligation to comply within ~45 days. + <strong>State Privacy Laws Leverage:</strong> As of mid-2026, 19+ states have comprehensive privacy laws (CA, CO, CT, DE, IN, IA, KY, MD, MN, MT, NE, NH, NJ, OR, RI, TN, TX, UT, VA and more). Invoking your state law when submitting deletion requests creates a strict legal obligation to comply within ~45 days. + </div> + <div class="mt-3 bg-light p-2 rounded small" data-bs-theme="light"> + <strong>California DROP (Delete Request & Opt-out Platform):</strong> Live since January 2026 at <a href="https://privacy.ca.gov/drop/" target="_blank" rel="noopener noreferrer" class="external-link">privacy.ca.gov/drop/</a>. California residents can submit a single request to delete personal data from 500+ registered data brokers simultaneously. Brokers must process requests by August 1, 2026. + </div> + <div class="mt-3 bg-light p-2 rounded small" data-bs-theme="light"> + <strong>CFPB Data Broker Rule — Withdrawn:</strong> The proposed federal FCRA rule that would have regulated data brokers as consumer reporting agencies was <strong>withdrawn May 15, 2025</strong>. No equivalent federal rule is in effect. State laws remain the primary legal leverage. </div> </div> </div> @@ -579,6 +585,11 @@ </div> </div> + <!-- Footer --> + <div class="container mt-4"> + <p class="text-center text-muted small no-print">Last verified: 2026-06-21</p> + </div> + <!-- Theme Toggle Button --> <button class="btn btn-primary theme-toggle no-print" id="themeToggle" aria-label="Toggle dark mode"> <i class="bi bi-moon-stars-fill" id="themeIcon"></i> --- a/prompt-builder.html +++ b/prompt-builder.html @@ -42,7 +42,7 @@ "url": "https://cheatsheets.davidveksler.com/images/prompt-builder-og-image.png" } }, - "dateModified": "2024-07-25", + "dateModified": "2026-06-21", "mainEntity": [ { "@type": "SoftwareApplication", @@ -70,7 +70,7 @@ "name": "David Vekslers" }, "datePublished": "2024-03-15", - "dateModified": "2024-07-25", + "dateModified": "2026-06-21", "articleSection": [ "Foundational Principles", "Core Prompting Techniques", @@ -1175,7 +1175,7 @@ AI: Roger started with 5 balls. He bought 2 cans, and each can has 3 balls. So, Stay informed about best practices for the specific model you're using. </p> <p> - Different models may have different strengths, weaknesses, and optimal prompting styles. What works best for GPT-4o might need slight adjustments for Claude 3.5 Sonnet or Gemini 1.5 Pro. Always refer to the latest documentation or guides provided by the AI lab for the specific model you are using. + Different models may have different strengths, weaknesses, and optimal prompting styles. What works best for GPT-5.5 might need slight adjustments for Claude Opus 4.8 or Gemini 3.5 Flash. Always refer to the latest documentation or guides provided by the AI lab for the specific model you are using. </p> </div> <p class="mt-4 text-center"> @@ -2035,8 +2035,9 @@ AI: Roger started with 5 balls. He bought 2 cans, and each can has 3 balls. So, </a> </div> <p class="mb-2"> - © 2025 David Veksler · Compiled & expanded based on AI research papers and practical LLM usage guides. + © 2026 David Veksler · Compiled & expanded based on AI research papers and practical LLM usage guides. </p> + <p class="mb-2 text-muted" style="font-size:0.8rem;">Last verified: 2026-06-21</p> <div> <a class="mx-2 link-secondary" href="https://www.linkedin.com/in/davidveksler/" target="_blank" title="David Veksler on LinkedIn"> <i class="bi bi-linkedin"></i> --- a/python-for-architects.html +++ b/python-for-architects.html @@ -4,18 +4,18 @@ <meta charset="utf-8"/> <meta content="width=device-width, initial-scale=1.0" name="viewport"/> <title> - Python for Architects: Ultimate Cheatsheet (Patterns, Frameworks & Systems 3.12+) + Python for Architects: Ultimate Cheatsheet (Patterns, Frameworks & Systems 3.14+) </title> <link href="data:image/svg+xml,<svg xmlns=%22http://www.w3.org/2000/svg%22 viewBox=%220 0 100 100%22><text y=%22.9em%22 font-size=%2290%22>🐍</text></svg>" rel="icon"/> <!-- SEO Meta Description --> - <meta content="🚀 Your ultimate interactive Python 3.12+ cheatsheet for architects & senior devs. Master patterns (architectural, design), frameworks (Django, Flask, FastAPI), data handling, concurrency, security, deployment & build robust systems. Click to explore!" name="description"/> + <meta content="🚀 Your ultimate interactive Python 3.14+ cheatsheet for architects & senior devs. Master patterns (architectural, design), frameworks (Django, Flask, FastAPI), data handling, concurrency, security, deployment & build robust systems. Click to explore!" name="description"/> <!-- Keywords --> - <meta content="Python, Python 3, Python 3.12, Cheatsheet, Interactive Cheatsheet, Python for Architects, Software Architecture, System Design, Design Patterns, Architectural Patterns, Django, Flask, FastAPI, SQLAlchemy, Asyncio, Concurrency, Parallelism, Microservices, Serverless, Python Best Practices, Software Development, Programming Guide, Technical Cheatsheet, Developer Resources, Python for Senior Developers, Tooltip Interactivity, Security, Deployment, DevOps" name="keywords"/> + <meta content="Python, Python 3, Python 3.14, Cheatsheet, Interactive Cheatsheet, Python for Architects, Software Architecture, System Design, Design Patterns, Architectural Patterns, Django, Flask, FastAPI, SQLAlchemy, Asyncio, Concurrency, Parallelism, Microservices, Serverless, Python Best Practices, Software Development, Programming Guide, Technical Cheatsheet, Developer Resources, Python for Senior Developers, Tooltip Interactivity, Security, Deployment, DevOps" name="keywords"/> <!-- Canonical URL --> <link href="https://cheatsheets.davidveksler.com/python-for-architects.html" rel="canonical"/> <!-- Social Media Metadata (Open Graph & Twitter) --> - <meta content="Python for Architects: The Ultimate Interactive Cheatsheet (3.12+)" property="og:title"/> - <meta content="🚀 The essential interactive guide for Python architects & sr. devs! Covers patterns, frameworks (Django, Flask, FastAPI), data, concurrency, security, deployment & more for Python 3.12+. #Python #SoftwareArchitecture #DevTools" property="og:description"/> + <meta content="Python for Architects: The Ultimate Interactive Cheatsheet (3.14+)" property="og:title"/> + <meta content="🚀 The essential interactive guide for Python architects & sr. devs! Covers patterns, frameworks (Django, Flask, FastAPI), data, concurrency, security, deployment & more for Python 3.14+. #Python #SoftwareArchitecture #DevTools" property="og:description"/> <meta content="website" property="og:type"/> <meta content="https://cheatsheets.davidveksler.com/python-for-architects.html" property="og:url"/> <meta content="A visual summary of key Python architectural concepts, frameworks, and patterns covered in the cheatsheet." property="og:image:alt"/> @@ -24,8 +24,8 @@ <meta content="summary_large_image" name="twitter:card"/> <meta content="@heroiclife" name="twitter:site"/> <meta content="@heroiclife" name="twitter:creator"/> - <meta content="Python for Architects: The Ultimate Interactive Cheatsheet (3.12+)" name="twitter:title"/> - <meta content="🚀 The essential interactive guide for Python architects & sr. devs! Covers patterns, frameworks, concurrency, security, deployment & more for Python 3.12+. #Python #SoftwareArchitecture" name="twitter:description"/> + <meta content="Python for Architects: The Ultimate Interactive Cheatsheet (3.14+)" name="twitter:title"/> + <meta content="🚀 The essential interactive guide for Python architects & sr. devs! Covers patterns, frameworks, concurrency, security, deployment & more for Python 3.14+. #Python #SoftwareArchitecture" name="twitter:description"/> <meta content="Interactive Python Cheatsheet for Architects: Key concepts overview." name="twitter:image:alt"/> <!-- Structured Data (JSON-LD) --> <script type="application/ld+json"> @@ -33,8 +33,8 @@ "@context": "https://schema.org", "@type": "TechArticle", "learningResourceType": "Cheatsheet", - "headline": "The Ultimate Interactive Python Cheatsheet for Architects & Senior Developers (Python 3.12+)", - "description": "Your comprehensive, interactive Python cheatsheet for architects and senior developers. Covers Python versions (up to 3.12+), architectural patterns, key frameworks (Django, Flask, FastAPI), design patterns, data handling, concurrency, security, and deployment for building robust Python systems.", + "headline": "The Ultimate Interactive Python Cheatsheet for Architects & Senior Developers (Python 3.14+)", + "description": "Your comprehensive, interactive Python cheatsheet for architects and senior developers. Covers Python versions (up to 3.14+), architectural patterns, key frameworks (Django, Flask, FastAPI), design patterns, data handling, concurrency, security, and deployment for building robust Python systems.", "image": "https://cheatsheets.davidveksler.com/images/python-architect-cheatsheet.png", "author": { "@type": "Person", @@ -51,12 +51,12 @@ } }, "datePublished": "2023-03-10T09:00:00Z", - "dateModified": "2025-05-10T10:00:00Z", + "dateModified": "2026-06-21T10:00:00Z", "mainEntityOfPage": { "@type": "WebPage", "@id": "https://cheatsheets.davidveksler.com/python-for-architects.html" }, - "keywords": "Python, Python 3.12, Cheatsheet, Interactive Cheatsheet, Python for Architects, Software Architecture, System Design, Design Patterns, Django, Flask, FastAPI, SQLAlchemy, Asyncio, Concurrency, Microservices, Software Development, Programming Guide, Python Best Practices, Tooltip Interactivity, Security, Deployment", + "keywords": "Python, Python 3.14, Cheatsheet, Interactive Cheatsheet, Python for Architects, Software Architecture, System Design, Design Patterns, Django, Flask, FastAPI, SQLAlchemy, Asyncio, Concurrency, Microservices, Software Development, Programming Guide, Python Best Practices, Tooltip Interactivity, Security, Deployment", "audience": { "@type": "Audience", "audienceType": ["Software Architects", "Senior Developers", "Python Developers", "Software Engineers"] @@ -485,7 +485,7 @@ </h1> <p class="lead"> An interactive guide to Python's architectural patterns, frameworks, design principles, and key libraries for - building robust and scalable systems. (Covers up to Python 3.12+) + building robust and scalable systems. (Covers up to Python 3.14+) </p> </header> <div class="container"> @@ -1720,7 +1720,7 @@ </i> FastAPI <span class="version-tag"> - Python 3.7+ + Python 3.8+ </span> </h5> <div class="card-content-wrapper"> @@ -2713,13 +2713,37 @@ intensive tasks, allowing other Python threads to run. </li> </ul> + <h6> + Free-Threading (PEP 703) + </h6> + <ul> + <li> + <strong> + Python 3.13 (experimental) / 3.14 (officially supported): + </strong> + CPython now ships an opt-in free-threaded build (<code>python3.14t</code>) where the GIL is + disabled, enabling true CPU-bound parallelism across threads. The GIL remains + <em>on by default</em> in the standard build. Enable with <code>PYTHON_GIL=0</code> or + the <code>-X gil=0</code> flag. + <a href="https://docs.python.org/3/howto/free-threading-python.html" rel="noopener noreferrer" target="_blank"> + Free-threading guide + </a> + </li> + <li> + <strong> + Ecosystem: + </strong> + Major libraries (NumPy, SciPy, FastAPI) already support the free-threaded build. + C extensions that have not been updated will silently re-enable the GIL. + </li> + </ul> <h6> Considerations for Architects </h6> <p> Understand the GIL's implications when choosing concurrency models. For CPU-bound parallelism, prefer - `multiprocessing` or external systems. For I/O-bound concurrency, `threading` or `asyncio` are - effective. + `multiprocessing`, the free-threaded build (Python 3.14+), or external systems. For I/O-bound + concurrency, `threading` or `asyncio` are effective. </p> </div> </div> @@ -3057,25 +3081,20 @@ </h5> <div class="card-content-wrapper"> <p class="summary"> - <span class="term" data-bs-placement="top" data-bs-toggle="tooltip" title="Checks code for style (PEP 8), errors (PyFlakes), and complexity (McCabe)."> - Flake8 + <span class="term" data-bs-placement="top" data-bs-toggle="tooltip" title="Extremely fast Python linter and formatter written in Rust; replaces Flake8, Black, isort and more."> + Ruff </span> - , + is now the dominant all-in-one linter & formatter (replaces Flake8, Black, isort). <span class="term" data-bs-placement="top" data-bs-toggle="tooltip" title="Extensive static code analysis for errors, style, and code smells."> Pylint </span> - for linting. - <span class="term" data-bs-placement="top" data-bs-toggle="tooltip" title="Opinionated code formatter for enforcing consistent style automatically."> - Black - </span> - , - <span class="term" data-bs-placement="top" data-bs-toggle="tooltip" title="Utility to sort Python imports alphabetically and by section."> - isort + for deep analysis. + <span class="term" data-bs-placement="top" data-bs-toggle="tooltip" title="Static type checker for type-hinted Python code."> + Mypy </span> - for auto-formatting to enforce code - style (e.g., PEP 8). - <a href="https://black.readthedocs.io/" rel="noopener noreferrer" target="_blank"> - Black + for type checking. + <a href="https://docs.astral.sh/ruff/" rel="noopener noreferrer" target="_blank"> + Ruff </a> </p> <button aria-controls="collapseLintersFormatters" aria-expanded="false" class="btn btn-sm details-toggle" data-bs-target="#collapseLintersFormatters" data-bs-toggle="collapse" type="button"> @@ -3086,6 +3105,26 @@ </div> </div> <div class="collapse collapse-content" id="collapseLintersFormatters"> + <h6> + Dominant Tool (2026) + </h6> + <ul> + <li> + <strong> + Ruff + <span class="version-tag"> + Rust-based + </span> + : + </strong> + An extremely fast all-in-one linter and formatter written in Rust. Replaces + Flake8, Black, isort, pyupgrade, and more — 10–100× faster than the individual tools. + Single config in <code>pyproject.toml</code>. + <a href="https://docs.astral.sh/ruff/" rel="noopener noreferrer" target="_blank"> + Ruff docs + </a> + </li> + </ul> <h6> Linters </h6> @@ -3095,14 +3134,14 @@ Flake8: </strong> Combines PyFlakes (error checking), PEP8/pycodestyle (style checking), and - McCabe (complexity checking). + McCabe (complexity checking). Largely superseded by Ruff for new projects. </li> <li> <strong> Pylint: </strong> More extensive checks, including code smells and potential bugs. Highly - configurable. + configurable. Still useful for deep analysis beyond Ruff's scope. </li> <li> <strong> @@ -3121,22 +3160,24 @@ <ul> <li> <strong> - Black: + Ruff Formatter: </strong> - "The uncompromising Python code formatter." Enforces a strict, consistent - style with minimal configuration. + Black-compatible formatter built into Ruff — the recommended choice + for new projects. </li> <li> <strong> - isort: + Black: </strong> - Sorts imports alphabetically and automatically separates into sections. + "The uncompromising Python code formatter." Still widely used; Ruff's + formatter is a drop-in replacement. </li> <li> <strong> - Autopep8: + isort: </strong> - Automatically formats Python code to conform to the PEP 8 style guide. + Sorts imports alphabetically and automatically separates into sections. + Ruff includes equivalent import-sorting rules (<code>I</code> rule set). </li> </ul> <h6> @@ -3270,8 +3311,10 @@ <strong> Dependency Management: </strong> - `pip` with `requirements.txt`, or tools like `Poetry` or - `Pipenv`. + <code>uv</code> (Astral, Rust-based — now dominant: replaces pip, pip-tools, virtualenv, + Poetry, pyenv in one tool with a universal lockfile). + <a href="https://docs.astral.sh/uv/" rel="noopener noreferrer" target="_blank">uv docs</a>. + Also: `pip` with `requirements.txt`, `Poetry`, `Pipenv`. </li> </ul> <h6> @@ -4377,7 +4420,7 @@ </a> </div> <p class="mb-2"> - © 2025 David Veksler · Compiled & expanded based on official documentation and software design best practices. + © 2026 David Veksler · Compiled & expanded based on official documentation and software design best practices. Last verified: 2026-06-21 </p> <div> <a class="mx-2 link-secondary" href="https://www.linkedin.com/in/davidveksler/" target="_blank" title="David Veksler on LinkedIn"> --- a/safety_data.js +++ b/safety_data.js @@ -5,11 +5,11 @@ // The main script in index.html will process this array (e.g., adding icons). const rawAiSafetyData = [ // AI Labs - { id: "openai", name: "OpenAI", url: "https://openai.com/", category: "AI Lab", importance: 5, description: "San Francisco-based capabilities lab, creator of ChatGPT. Historically significant safety team, though experienced departures in 2024.", logoUrl: "https://openai.com/icon.svg?d5c238c2cf2e4f08", subCategoryIcon: "bi-building", subCategoryText: "AI Lab (Capabilities & Safety Research)", safetyLinks: [{ text: "Safety Overview", url: "https://openai.com/safety", icon: "bi-shield-check", title:"OpenAI's official safety policies" }, { text: "Research", url: "https://openai.com/research", icon: "bi-journal-richtext", title:"OpenAI's research publications" }] }, + { id: "openai", name: "OpenAI", url: "https://openai.com/", category: "AI Lab", importance: 5, description: "San Francisco-based capabilities lab, creator of ChatGPT. Safety teams have been repeatedly disbanded: Superalignment (May 2024), AGI Readiness (Oct 2024), and Mission Alignment (Feb 2026), amid ongoing safety-vs-commercialization tension.", logoUrl: "https://openai.com/icon.svg?d5c238c2cf2e4f08", subCategoryIcon: "bi-building", subCategoryText: "AI Lab (Capabilities & Safety Research)", safetyLinks: [{ text: "Safety Overview", url: "https://openai.com/safety", icon: "bi-shield-check", title:"OpenAI's official safety policies" }, { text: "Research", url: "https://openai.com/research", icon: "bi-journal-richtext", title:"OpenAI's research publications" }] }, { id: "deepmind", name: "Google DeepMind", url: "https://www.deepmind.com/", category: "AI Lab", importance: 5, description: "Major London-based AI capabilities lab (Google-owned) with a strong, long-standing safety research team. Created AlphaGo, AlphaFold, Gemini.", logoUrl: "https://www.gstatic.com/images/branding/productlogos/google_deepmind/v3/web-96dp/logo_google_deepmind_color_2x_web_96dp.png", subCategoryIcon: "bi-building", subCategoryText: "AI Lab (Capabilities & Safety Research)", safetyLinks: [{ text: "Responsibility & Safety", url: "https://deepmind.google/discover/responsibility-safety/", icon: "bi-shield-check", title:"DeepMind's approach to responsibility" }, { text: "Blog (incl. Safety)", url: "https://deepmind.google/discover/blog/", icon: "bi-journal-text", title:"DeepMind's blog for updates" }] }, { id: "anthropic", name: "Anthropic", url: "https://www.anthropic.com/", category: "AI Lab", importance: 5, description: "Research lab focusing heavily on LLM alignment and safety, particularly interpretability. Created Claude. Known for its safety-first mission.", logoUrl: "https://static.cdnlogo.com/logos/a/68/anthropic.svg", subCategoryIcon: "bi-shield-shaded", subCategoryText: "AI Lab (Safety-Focused)", safetyLinks: [{ text: "Safety Research", url: "https://www.anthropic.com/research", icon: "bi-journal-richtext", title:"Anthropic's safety research papers" }, { text: "Constitutional AI", url: "https://www.anthropic.com/constitutional-ai", icon: "bi-rulers", title:"Anthropic's Constitutional AI method" }] }, { id: "xai", name: "xAI", url: "https://x.ai/", category: "AI Lab", importance: 3, description: "Capabilities lab led by Elon Musk aiming to \"understand the universe.\" Created Grok. Safety stance less defined than others.", logoUrl: "https://logowik.com/content/uploads/images/xai905.logowik.com.webp", subCategoryIcon: "bi-building", subCategoryText: "AI Lab (Capabilities Research)", safetyLinks: [{ text: "About/Mission", url: "https://x.ai/about", icon: "bi-info-circle", title:"Learn about xAI's mission" }] }, - { id: "ssi", name: "Safe Superintelligence Inc. (SSI)", url: "https://ssi.inc/", category: "AI Lab", importance: 3, description: "Research lab founded by Ilya Sutskever focused explicitly on building safe superintelligence. Newer, impact TBD.", logoUrl: null, subCategoryIcon: "bi-shield-lock-fill", subCategoryText: "AI Lab (Safety-Focused)", safetyLinks: [{ text: "Mission", url: "https://ssi.inc/", icon: "bi-bullseye", title:"SSI's mission statement" }] }, + { id: "ssi", name: "Safe Superintelligence Inc. (SSI)", url: "https://ssi.inc/", category: "AI Lab", importance: 3, description: "Research lab now led by Ilya Sutskever as CEO (co-founder Daniel Gross departed for Meta mid-2025). Valued at ~$32B as of April 2025. Pursuing a distinct research paradigm beyond scaling; publishes no papers and maintains minimal external communications.", logoUrl: null, subCategoryIcon: "bi-shield-lock-fill", subCategoryText: "AI Lab (Safety-Focused)", safetyLinks: [{ text: "Mission", url: "https://ssi.inc/", icon: "bi-bullseye", title:"SSI's mission statement" }] }, { id: "deepseek", name: "DeepSeek", url: "https://www.deepseek.com/", category: "AI Lab", importance: 2, description: "Chinese capabilities lab developing and releasing open-weights LLMs (e.g., DeepSeek-R1). Important international player.", logoUrl: "https://logowik.com/content/uploads/images/deepseek-ai4760.logowik.com.webp", subCategoryIcon: "bi-building", subCategoryText: "AI Lab (Capabilities Research, China)", safetyLinks: [{ text: "GitHub/Models", url: "https://github.com/deepseek-ai", icon: "bi-github", title:"DeepSeek's models on GitHub" }] }, { id: "obelisk", name: "Obelisk (at Astera)", url: "https://astera.org/agi-program/", category: "AI Lab", importance: 2, description: "Research team aiming to engineer AGI using an exploratory approach inspired by cognitive science/neuroscience.", logoUrl: "https://static.cdnlogo.com/logos/a/29/astera.svg", subCategoryIcon: "bi-clipboard-data", subCategoryText: "Research Team (AGI Engineering)", safetyLinks: [{ text: "AGI Program Details", url: "https://astera.org/agi-program/", icon: "bi-journal-richtext", title:"Astera's Obelisk AGI program details" }] }, @@ -29,7 +29,7 @@ const rawAiSafetyData = [ { id: "alignedai", name: "Aligned AI", url: "https://buildaligned.ai/", category: "Academic/Research", importance: 2, description: "Oxford-based startup using mathematical techniques for safe off-distribution generalization.", subCategoryIcon: "bi-shield-check", subCategoryText: "AI Startup (Safety Focused)" }, { id: "cyborgism", name: "Cyborgism (Concept)", url: "https://www.lesswrong.com/posts/bxt7uCiHam4QXrQAA/cyborgism", category: "Academic/Research", importance: 2, description: "Strategy exploring human-in-the-loop systems to accelerate alignment research.", subCategoryIcon: "bi-signpost-split", subCategoryText: "Research Strategy" }, { id: "yampolskiy", name: "Dr. Roman V. Yampolskiy", url: "http://cecs.louisville.edu/ry/", category: "Academic/Research", importance: 2, description: "Professor researching AI safety, cybersecurity background, numerous publications.", subCategoryIcon: "bi-person", subCategoryText: "Academic Researcher" }, - { id: "hadfieldmenell", name: "Dylan Hadfield-Menell", url: "https://people.csail.mit.edu/dhm/", category: "Academic/Research", importance: 2, description: "Assistant professor at MIT working on agent alignment. Runs the Algorithmic Alignment Group.", subCategoryIcon: "bi-person", subCategoryText: "Academic Researcher (MIT)" }, + { id: "hadfieldmenell", name: "Dylan Hadfield-Menell", url: "https://people.csail.mit.edu/dhm/", category: "Academic/Research", importance: 2, description: "Associate Professor of EECS at MIT (promoted July 2025) working on agent alignment and the value alignment problem. Runs the Algorithmic Alignment Group.", subCategoryIcon: "bi-person", subCategoryText: "Academic Researcher (MIT)" }, { id: "grayswan", name: "Gray Swan", url: "https://www.grayswan.ai/", category: "Academic/Research", importance: 2, description: "For-profit developing tools to assess AI model risks and building its own safety-focused models.", subCategoryIcon: "bi-shield-check", subCategoryText: "AI Startup (Safety Tools)" }, { id: "wentworth", name: "John Wentworth", url: "https://www.lesswrong.com/posts/gQY6LrTWJNkTv8YJR/the-pointers-problem-human-values-are-a-function-of-humans", category: "Academic/Research", importance: 2, description: "Independent alignment researcher working on selection theorems, abstraction, and agency.", subCategoryIcon: "bi-person", subCategoryText: "Independent Researcher" }, { id: "kasl", name: "Krueger AI Safety Lab (KASL)", url: "https://www.kasl.ai/publications/", category: "Academic/Research", importance: 2, description: "AI safety research group at the University of Cambridge, led by David Krueger.", subCategoryIcon: "bi-bank", subCategoryText: "University Research Lab (Cambridge)" }, @@ -51,10 +51,10 @@ const rawAiSafetyData = [ // Policy/Gov { id: "govai", name: "Centre for the Governance of AI (GovAI)", url: "https://www.governance.ai/", category: "Policy/Gov", importance: 4, description: "Highly influential AI governance research group, producing policy research and running career programs.", subCategoryIcon: "bi-bank", subCategoryText: "University Research Group (Oxford)" }, { id: "cset", name: "Center for Security and Emerging Technology (CSET)", url: "https://cset.georgetown.edu/", category: "Policy/Gov", importance: 4, description: "Georgetown University think tank providing data-driven analysis on security implications of emerging tech.", subCategoryIcon: "bi-building-columns", subCategoryText: "University Think Tank (Georgetown)" }, - { id: "ukaisi", name: "UK AI Safety Institute (UK AISI)", url: "https://www.aisi.gov.uk/", category: "Policy/Gov", importance: 4, description: "UK government organisation researching, testing safety, measuring impacts, and shaping global policy.", subCategoryIcon: "bi-flag-fill", subCategoryText: "Government Institute (UK)" }, - { id: "usaisi", name: "U.S. AI Safety Institute (USAISI)", url: "https://www.nist.gov/artificial-intelligence/artificial-intelligence-safety-institute", category: "Policy/Gov", importance: 4, description: "US government organization (NIST) advancing AI safety science, practice, and adoption.", subCategoryIcon: "bi-flag-fill", subCategoryText: "Government Institute (US)" }, + { id: "ukaisi", name: "UK AI Security Institute (UK AISI)", url: "https://www.aisi.gov.uk/", category: "Policy/Gov", importance: 4, description: "UK government organisation (DSIT) researching, testing, and evaluating AI safety and security risks. Renamed from AI Safety Institute to AI Security Institute in February 2025, refocusing on security threats including cyber and CBRN risks.", subCategoryIcon: "bi-flag-fill", subCategoryText: "Government Institute (UK)" }, + { id: "usaisi", name: "U.S. Center for AI Standards & Innovation (CAISI)", url: "https://www.nist.gov/caisi", category: "Policy/Gov", importance: 4, description: "US government organization (NIST) advancing AI standards, testing, and adoption. Renamed from AI Safety Institute to CAISI in June 2025 under the Trump administration, pivoting emphasis from 'safety' toward standards and innovation.", subCategoryIcon: "bi-flag-fill", subCategoryText: "Government Institute (US)" }, { id: "fli", name: "Future of Life Institute (FLI)", url: "https://futureoflife.org/", category: "Policy/Gov", importance: 4, description: "Works on steering transformative tech via outreach, policy advocacy, grantmaking, and event organisation.", subCategoryIcon: "bi-megaphone", subCategoryText: "Advocacy, Policy, Funding" }, // Primarily policy/advocacy focus here - { id: "miri", name: "Machine Intelligence Research Institute (MIRI)", url: "https://intelligence.org/", category: "Policy/Gov", importance: 4, description: "Original AI safety research org (Yudkowsky), now more focused on policy and public outreach. Foundational concepts.", subCategoryIcon: "bi-search-heart", subCategoryText: "Research, Policy, Advocacy" }, // Primarily policy/advocacy focus here + { id: "miri", name: "Machine Intelligence Research Institute (MIRI)", url: "https://intelligence.org/", category: "Policy/Gov", importance: 4, description: "Original AI safety research org (Yudkowsky). Since 2024 has pivoted almost entirely to technical governance and policy advocacy—promoting an international moratorium ('Off Switch') on frontier AI. Co-authored the 2025 NYT-bestselling book 'If Anyone Builds It, Everyone Dies.'", subCategoryIcon: "bi-search-heart", subCategoryText: "Research, Policy, Advocacy" }, // Primarily policy/advocacy focus here { id: "clr", name: "Center on Long-Term Risk (CLR)", url: "https://longtermrisk.org/", category: "Policy/Gov", importance: 3, description: "Focuses on AI safety research, grants, and community, particularly around conflict scenarios and cooperation.", subCategoryIcon: "bi-shield-exclamation", subCategoryText: "Research, Funding, Community (X-Risk Focus)" }, { id: "pai", name: "Partnership on AI (PAI)", url: "https://partnershiponai.org/", category: "Policy/Gov", importance: 3, description: "Convenes academic, civil society, industry, and media organizations to create solutions for beneficial AI.", subCategoryIcon: "bi-people-fill", subCategoryText: "Multi-stakeholder Org" }, { id: "cser", name: "Centre for the Study of Existential Risk (CSER)", url: "https://www.cser.ac.uk/", category: "Policy/Gov", importance: 3, description: "Cambridge interdisciplinary centre dedicated to the study and mitigation of existential risks, including AI.", subCategoryIcon: "bi-bank", subCategoryText: "University Center (Cambridge)" }, --- a/tesla-products.html +++ b/tesla-products.html @@ -339,7 +339,7 @@ } }, "datePublished": "2024-03-10", - "dateModified": "2024-10-15", + "dateModified": "2026-06-21", "mainEntityOfPage": "https://cheatsheets.davidveksler.com/tesla-products.html", "keywords": "Tesla, Model S, Model 3, Model X, Model Y, Cybertruck, Semi, Roadster, Powerwall, Megapack, Solar Roof, Solar Panels, Supercharger, Wall Connector, NACS, Autopilot, FSD, Tesla Vision, Optimus, Dojo, Gigacasting, 4680 cells, technical specifications, engineering, EV, electric vehicle, battery technology, AI, robotics, manufacturing" } @@ -1090,9 +1090,9 @@ </li> <li> <strong> - Model Y Production & Incentives: + Model Y "Juniper" Refresh (2025): </strong> - Texas-built Model Y AWD regained the full $7,500 U.S. IRA tax credit in January 2024 thanks to domestic battery sourcing. Giga Texas ramped a higher-share structural 4680 pack line, laying groundwork for the widely reported "Juniper" cosmetic/infotainment refresh expected in 2025. + The refreshed "Juniper" Model Y launched in the U.S. in March 2025, initially as a $59,990 Launch Series. Broader availability began April 2025 with the Long Range AWD from ~$48,990 (before incentives). Key upgrades include a redesigned interior with rear passenger display, ventilated front seats, motorised rear seatbacks, improved sound insulation, ambient lighting, revised suspension, and updated efficiency tuning. EPA range is approximately 321–327 miles for Long Range AWD depending on wheel choice. Texas-built AWD models retain eligibility for the $7,500 federal IRA tax credit. </li> </ul> </div> @@ -1415,38 +1415,38 @@ </li> </ul> <h6> - 8. Powertrain Options & 2024 Ramp Status: + 8. Powertrain Options & 2026 Lineup: </h6> <ul> <li> <strong> - Dual-Motor AWD: + AWD (Standard) — base trim: </strong> - 600 hp / 7,435 Nm wheel torque, 318-mile EPA range on 20" all-terrain tires, 0-60 mph in 4.1 s. Listed at $79,990 (Foundation Series price $99,990) with deliveries underway since December 2023. + Dual-motor, ~600 hp, 0-60 mph in 4.1 s, ~325-mile EPA range, starts at $69,990. Introduced February 2026 as the new entry trim after the RWD was discontinued. </li> <li> <strong> - Cyberbeast Tri-Motor: + AWD Premium: </strong> - 845 hp / 10,296 Nm wheel torque, 301-mile EPA range, 0-60 mph in 2.6 s with rollout. Priced at $99,990 ($119,990 Foundation Series) and prioritized for early VINs. + Same dual-motor powertrain with additional features/equipment, priced ~$10,000 above the standard AWD. </li> <li> <strong> - Rear-Wheel-Drive Variant: + Cyberbeast Tri-Motor: </strong> - Single-motor, 250+ mile target range at $60,990. Tesla shifted customer deliveries to 2025 while cells remain prioritized for AWD/Cyberbeast. + 800+ hp, 0-60 mph in 2.6 s with rollout, 300+ mile EPA range, priced at $99,990. </li> <li> <strong> - Range Extender Accessory: + RWD Variant (Discontinued): </strong> - Optional ~50 kWh auxiliary pack that sits in the vault, adding ~130 miles when paired with off-road tires. Tesla reopened opt-in requests in April 2024 and reiterated shipments will begin with 2025 AWD/Cyberbeast builds that require extended range. + Single-motor RWD was offered briefly in 2025 at $60,990 but was discontinued after limited sales; dual-motor AWD is now the entry configuration. </li> <li> <strong> - Production Ramp: + Range Extender Accessory: </strong> - Giga Texas produced 11,688 Cybertrucks and delivered 8,680 units in Q2 2024, averaging over 1,000 trucks per week by July per Tesla's shareholder update. + Optional ~50 kWh auxiliary pack that sits in the vault, adding ~130 miles of range. </li> </ul> <h6> @@ -1463,9 +1463,9 @@ <ul> <li> <strong> - Status (2024): + Status (2025–2026): </strong> - Tesla began shipping the Powershare Home Backup kit (Gateway + 200A automatic transfer switch) to Foundation Series customers in June 2024, enabling seamless backup power without manual cord swaps. Certification work for direct Powerwall integration continues, with software support targeted after UL 9540 updates. + Tesla shipped the Powershare Home Backup kit (Gateway + 200A automatic transfer switch) to Foundation Series customers starting June 2024. Powerwall integration has since expanded, with OTA updates enabling coordinated solar+Powerwall+Cybertruck backup scenarios. The system is now available to all Cybertruck owners (not Foundation-only) in eligible markets. </li> <li> <strong> @@ -1633,25 +1633,25 @@ <strong> Factory: </strong> - Dedicated factory in Nevada (adjacent to Giga Nevada) with a target annual capacity of 50,000 units. Tesla resumed vertical construction in January 2024 as part of the $3.6B expansion, with structural steel for the Semi assembly hall topped out in July 2024 and equipment installation slated to follow through early 2025. + Dedicated 1.7 million sq ft Semi factory in Sparks, Nevada (adjacent to Giga Nevada), with a target annual capacity of 50,000 units. Construction completed through 2025. </li> <li> <strong> Production Status: </strong> - Initial production began in October 2022 with first deliveries to PepsiCo in December 2022. Approximately 200 Semi trucks delivered through 2024. + Pilot production began October 2022 with first deliveries to PepsiCo in December 2022. Volume production launched at the Nevada Semi factory in March/April 2026, transitioning from hand-built pilot units to mass manufacturing. </li> <li> <strong> - Volume Production Timeline: + Volume Production Ramp: </strong> - Tesla reiterated on the Q2 2024 earnings call that high-volume production is scheduled for late 2025 once the dedicated Nevada facility and next-generation 4680 supply chain are online, with broader customer deliveries following internal fleet validation. + Tesla targets 50,000 units/year capacity at full ramp — approximately 20% of the North American Class 8 truck market. Broader customer deliveries are expanding as the Nevada line scales through 2026. </li> <li> <strong> Charging Infrastructure: </strong> - 46 new Megachargers planned to support Semi operations and customer deployments. + 46 new Megachargers deployed along key freight routes to support Semi fleet operations. </li> </ul> <h6> @@ -1805,20 +1805,20 @@ </li> </ul> <h6> - 6. Production & Availability (2024 Outlook): + 6. Production & Availability (2026 Outlook): </h6> <ul> <li> <strong> - Design Status: + Status: </strong> - Elon Musk stated in February 2024 that Tesla and SpaceX locked the production design for a joint reveal "toward the end of 2024," highlighting extensive aerospace-grade materials and active aero. + As of June 2026, the Roadster has not entered production. Musk stated at Tesla's Q1 2026 earnings call (April 22, 2026) that an unveil was coming "in a month or so" — the latest in a series of postponements since the prototype debuted in 2017 with production originally promised for 2020. </li> <li> <strong> Production Timeline: </strong> - Start-of-production remains contingent on Cybertruck/Robotaxi resource allocation and 4680 availability; Tesla has not published a firm SOP date beyond targeting post-2024 validation builds. + Musk indicated low-volume production could begin toward end of 2026 or ramp in 2027, with European sales potentially starting 2027. No firm start-of-production date has been officially published. </li> <li> <strong> @@ -2332,20 +2332,26 @@ </li> </ul> <h6> - 9. 2024 Deployment Highlights: + 9. Deployment Highlights (2025–2026): </h6> <ul> <li> <strong> - Lathrop Megafactory Output: + Record 2025 Deployments: </strong> - Tesla's California Megafactory surpassed a 20+ GWh annualized run-rate, helping energy storage deployments hit a record 9.4 GWh in Q2 2024—over 90% of which were Megapacks. + Tesla Energy deployed a record 46.7 GWh of energy storage in full-year 2025 — more than double 2024 volumes — generating approximately $12.8 billion in segment revenue (up ~27% year-over-year). Q4 2025 alone reached 14.2 GWh. + </li> + <li> + <strong> + Lathrop Megafactory: + </strong> + Tesla's California Megafactory continues to expand capacity; the Lathrop plant was a primary driver of the 2025 deployment surge. </li> <li> <strong> Shanghai Megafactory: </strong> - Ground broke in May 2024 on a dedicated Megapack plant in Lingang, Shanghai, targeting 10,000 units (40 GWh) per year starting in 2025 to shorten lead times for APAC grid projects. + The dedicated Megapack plant in Lingang, Shanghai (ground broke May 2024) began production in 2025, targeting 10,000 units (~40 GWh) per year to serve APAC grid projects and shorten lead times. </li> </ul> </div> @@ -2990,7 +2996,7 @@ </h6> <ul> <li> - Tesla reported 6,249 stations and 57,579 connectors worldwide at the end of Q2 2024 (up 26% year-over-year). Despite the April 2024 reorganization of the Supercharger team, construction continues via new utility partnerships and third-party capital. + As of Q1 2026, Tesla operates approximately 8,463 stations and 79,918 connectors worldwide — up roughly 19% year-over-year. The network delivered a record 6.7 TWh of energy in full-year 2025. </li> </ul> <h6> @@ -2998,15 +3004,15 @@ </h6> <ul> <li> - Most North American automakers have committed to adopting NACS (standardized as SAE J3400) by 2025, which will reduce the need for Magic Docks in the future for new vehicles. + NACS (SAE J3400) is now the dominant North American DC fast-charge standard. Most major automakers (Ford, GM, Rivian, Volvo, Polestar, Honda, Nissan, and others) have transitioned new models to NACS connectors, reducing reliance on Magic Docks for those vehicles. Magic Dock CCS adapters remain in place for older non-Tesla EVs. </li> </ul> <h6> - 9. 2024 Public Access Expansion: + 9. Open Access & Third-Party Use: </h6> <ul> <li> - Ford owners began using Tesla's network via official NACS adapters in March 2024, followed by GM, Rivian, Volvo, and Polestar customers through the summer. Credit-card readers on V4 pedestals and in-app stall reservations help Tesla meet federal NEVI open-access rules as more third-party EVs join. + The Supercharger network has been open to non-Tesla EVs since 2023–2024. Credit-card readers on V4 pedestals and in-app stall reservations support NEVI open-access requirements. As NACS becomes universal in North America, cross-brand charging friction continues to decrease. </li> </ul> </div> @@ -3568,32 +3574,32 @@ </li> </ul> <h6> - 5. FSD (Supervised) – 2024 v12 Rollout: + 5. FSD (Supervised) – v13/v14 Era (2025–2026): </h6> <ul> <li> <strong> End-to-End Networks: </strong> - Version 12.3 (March 2024) replaced hundreds of C++ heuristics with a single video-to-control neural network that directly outputs steering, throttle, and brake, dramatically improving human-like behavior in dense urban traffic. + Version 12.3 (March 2024) replaced C++ heuristics with a single video-to-control neural network. FSD v13 (late 2024, HW4-only) extended full end-to-end logic to parked-to-parked driving including autonomous parking and low-speed maneuvering, trained on Tesla's Cortex compute cluster. </li> <li> <strong> - Deployment Footprint: + FSD v14 (October 2025): </strong> - Tesla rebranded the beta to "FSD (Supervised)" in April 2024 and broadened access to essentially the entire North American fleet on HW3/HW4, including Cybertruck. Subscription pricing dropped to $99/mo in the U.S. to accelerate take rate. + First major version release in roughly a year; extends full end-to-end logic across the complete driving stack including parking lots, garages, and tight enclosed areas. Rolling out to HW4 vehicles. HW3 vehicles receive a "v14 Lite" build (targeted late June 2026) with improved supervised capabilities but cannot achieve unsupervised FSD — Tesla confirmed HW3 lacks the compute and camera hardware for unsupervised operation. </li> <li> <strong> - Recent Builds: + Unsupervised FSD Timeline: </strong> - v12.4 introduced camera-based driver monitoring to reduce steering-wheel nagging and improved creep behavior, while v12.5 (July 2024) unified highway and city stacks, added Start/Stop from Park for Cybertruck, and delivered more assertive lane selection. + Cybercab robotaxis launched unsupervised service in Austin in June 2025, expanding to Dallas and Houston by April 2026. Unsupervised FSD for consumer-owned vehicles is targeted for Q4 2026 at the earliest, subject to geography-by-geography regulatory validation per Musk's Q1 2026 earnings comments. </li> <li> <strong> - Roadmap: + Deployment Footprint: </strong> - Tesla is testing v12.6 with expanded occupancy networks, reversible maneuvers, and smoother unprotected turns ahead of the planned Robotaxi showcase, while continuing to collect supervised miles toward future unsupervised approvals. + "FSD (Supervised)" branding is current. HW3 and HW4 vehicles on the North American fleet have access; subscription pricing remains $99/mo in the U.S. </li> </ul> <h6> @@ -4177,38 +4183,38 @@ </li> </ul> <h6> - 8. Development Status & 2024 Milestones + 8. Development Status & 2025–2026 Milestones </h6> <ul> <li> <strong> - Gen-2.5 ("Golden"): + Gen-2 / Gen-2.5 Deployment: </strong> - December 2023's Gen-2 unveil added articulated hands, faster gait, and full-body balance control. Tesla showed a "Golden" build in May 2024 sorting cylindrical cells autonomously, while a lighter Gen-3 platform remains in R&D. + Approximately 1,000+ Optimus units are deployed across Fremont and Giga Texas as of early 2026, primarily for data collection and learning rather than fully autonomous production work. Musk acknowledged in Q4 2025 earnings that units are not yet doing independent useful work but are generating valuable training data. </li> <li> <strong> - Factory Deployment: + Gen-3 Status: </strong> - Two Optimus units are performing real pick-and-place chores at Giga Texas battery lines, with additional robots mapping Fremont workcells during off-shifts. Tesla's AI Day updates highlight round-the-clock autonomous walking at the Palo Alto lab. + Optimus Gen-3 (V3) was repeatedly delayed; Musk stated at Q1 2026 earnings (April 2026) that Gen-3 production is set to begin at Fremont in late July or August 2026. A dedicated humanoid robot production facility at Giga Texas (targeting up to 10 million units/year by 2027) was announced in November 2025. </li> <li> <strong> Production Focus: </strong> - 2024 efforts are centered on building low-volume pilot units (dozens, not thousands) to validate actuators, harnessing, and teleoperation fallback before scaling the dedicated production line that's under construction in Fremont. + 2025–2026 efforts focus on scaling from pilot units to a production line at Fremont, validating actuators, harnessing, and AI control systems. The Gen-3 platform aims for further weight reduction and improved dexterity over Gen-2. </li> <li> <strong> Pricing & Availability: </strong> - Tesla still targets sub-$20,000 BOM at scale, but external sales remain "several years" away; the near-term goal is to prove cost savings inside Tesla factories before offering robots to third parties. + Tesla's stated commercial target is $20,000–$30,000 per unit at scale. External sales remain future-dated; near-term focus is proving value inside Tesla's own factories. </li> <li> <strong> Challenges: </strong> - Key hurdles include reliable hand dexterity, low-cost sensor supply, and navigating export controls on high-performance actuators. Fine motor skills (e.g., threading needles) are improving but still supervised. + Key hurdles include reliable hand dexterity, low-cost sensor supply, and navigating export controls on high-performance actuators. Fine motor skills continue to improve but remain a focus area. </li> </ul> </div> @@ -4634,13 +4640,13 @@ <strong> Current Capacity: </strong> - Tesla's first Dojo ExaPOD entered production in Palo Alto in late 2023, with additional cabinets commissioned in Austin during 2024. A dedicated Dojo V2 data center is being built out at the Buffalo Gigafactory to host the next-generation tiles starting in early 2025. + Tesla's first Dojo ExaPOD entered production in Palo Alto in late 2023, with additional cabinets commissioned in Austin during 2024. A dedicated Dojo V2 data center at the Buffalo Gigafactory began hosting next-generation tiles in 2025. Tesla also built out its "Cortex" compute cluster at Giga Texas, which was used to train FSD v13 and later models. </li> <li> <strong> Complementary GPU Strategy: </strong> - The company is concurrently scaling NVIDIA H100/H200 clusters (targeting ~85,000 H100-class GPUs online by end-2024) and expects to spend roughly $10B on AI training and inference compute this year to support vehicle, Optimus, and data-center workloads. + Tesla operates large NVIDIA H100/H200 GPU clusters (the Cortex cluster exceeded 50,000+ H100-class GPUs through 2025) alongside Dojo for training FSD, Optimus, and other AI workloads. The AI5 inference chip for next-generation vehicle hardware was delayed to mid-2027; Cybercab launched on AI4 (HW4-equivalent) hardware. </li> </ul> </div> @@ -4756,7 +4762,10 @@ </a> </div> <p class="mb-2"> - © 2025 David Veksler · Compiled & expanded based on official Tesla documentation and electric vehicle industry analysis. + © 2026 David Veksler · Compiled & expanded based on official Tesla documentation and electric vehicle industry analysis. + </p> + <p class="mb-2" style="font-size:0.85em;"> + Last verified: 2026-06-21 </p> <div> <a class="mx-2 link-secondary" href="https://www.linkedin.com/in/davidveksler/" target="_blank" title="David Veksler on LinkedIn"> --- a/versioncontrol.html +++ b/versioncontrol.html @@ -169,7 +169,7 @@ </div> </div> <div class="collapse collapse-content" id="collapseHg"> -<h6>Philosophy & Core</h6><p>Designed with user-friendliness and interface consistency as high priorities. Aims to provide powerful DVCS features with a simpler command set and conceptual model compared to Git's defaults.</p><h6>Key Features</h6><ul><li><strong>Simpler Interface:</strong> Commands are often perceived as more consistent and intuitive (e.g., no staging area by default; <code>hg commit</code> commits all tracked changes).</li><li><strong>Branching Concepts:</strong> Supports multiple ways to handle parallel lines of development (named branches, bookmarks, anonymous heads). Named branches are permanent parts of history, unlike Git branches which are just pointers. This can offer power but also cause confusion.</li><li><strong>Extensibility:</strong> Core functionality can be extended via built-in extensions (e.g., `rebase`, `histedit` for history modification, `largefiles` for binary file support).</li><li><strong>Performance:</strong> Generally excellent performance, comparable to Git.</li><li><strong>Windows Support:</strong> Historically known for strong native Windows support.</li></ul><h6>Common Commands</h6><p><code>hg clone</code>, <code>hg add</code>, <code>hg commit</code> (or <code>hg ci</code>), <code>hg status</code>, <code>hg log</code>, <code>hg branch</code>, <code>hg update</code> (switches branches/commits), <code>hg merge</code>, <code>hg pull</code>, <code>hg push</code>, <code>hg heads</code>.</p><h6>Strengths</h6><ul><li>Potentially easier initial learning curve for basic workflows.</li><li>More consistent command-line interface structure.</li><li>Good performance.</li><li>Built-in web interface (<code>hg serve</code>).</li></ul><h6>Tradeoffs</h6><ul><li>Significantly smaller community and ecosystem compared to Git.</li><li>Declining support on major hosting platforms (Bitbucket deprecated new Hg repos in 2020; GitHub never fully supported it; GitLab requires workarounds).</li><li>Multiple branching models (named branches vs bookmarks) can be confusing.</li><li>Some advanced operations require enabling non-default extensions.</li></ul><h6>Use Cases</h6><p>Legacy projects, specific large organizations (e.g., Meta/Facebook uses it heavily internally), teams that strongly prefer its model over Git and manage their own hosting or use Bitbucket for existing repos.</p> +<h6>Philosophy & Core</h6><p>Designed with user-friendliness and interface consistency as high priorities. Aims to provide powerful DVCS features with a simpler command set and conceptual model compared to Git's defaults.</p><h6>Key Features</h6><ul><li><strong>Simpler Interface:</strong> Commands are often perceived as more consistent and intuitive (e.g., no staging area by default; <code>hg commit</code> commits all tracked changes).</li><li><strong>Branching Concepts:</strong> Supports multiple ways to handle parallel lines of development (named branches, bookmarks, anonymous heads). Named branches are permanent parts of history, unlike Git branches which are just pointers. This can offer power but also cause confusion.</li><li><strong>Extensibility:</strong> Core functionality can be extended via built-in extensions (e.g., `rebase`, `histedit` for history modification, `largefiles` for binary file support).</li><li><strong>Performance:</strong> Generally excellent performance, comparable to Git.</li><li><strong>Windows Support:</strong> Historically known for strong native Windows support.</li></ul><h6>Common Commands</h6><p><code>hg clone</code>, <code>hg add</code>, <code>hg commit</code> (or <code>hg ci</code>), <code>hg status</code>, <code>hg log</code>, <code>hg branch</code>, <code>hg update</code> (switches branches/commits), <code>hg merge</code>, <code>hg pull</code>, <code>hg push</code>, <code>hg heads</code>.</p><h6>Strengths</h6><ul><li>Potentially easier initial learning curve for basic workflows.</li><li>More consistent command-line interface structure.</li><li>Good performance.</li><li>Built-in web interface (<code>hg serve</code>).</li></ul><h6>Tradeoffs</h6><ul><li>Significantly smaller community and ecosystem compared to Git.</li><li>No major hosting platform support: Bitbucket fully removed all Hg repositories in July 2020 (permanently deleted by March 2022); GitHub never supported it; GitLab requires workarounds.</li><li>Multiple branching models (named branches vs bookmarks) can be confusing.</li><li>Some advanced operations require enabling non-default extensions.</li></ul><h6>Use Cases</h6><p>Legacy projects, specific large organizations (e.g., Meta/Facebook historically used it internally before transitioning to their own Sapling system), teams that strongly prefer its model over Git and manage their own hosting.</p> </div> </div> </div> @@ -230,7 +230,7 @@ </div> </div> <div class="collapse collapse-content" id="collapsePlatform3"> -<h6>Core Offerings</h6><p>Git repository hosting (Mercurial support was removed for new repos in 2020, existing Hg repos may still function but are legacy), Pull Requests, integrated CI/CD (Bitbucket Pipelines), code search, deep issue tracking integration (Jira), project tracking integration (Trello).</p><h6>Key Features</h6><ul><li><strong>Atlassian Ecosystem Integration:</strong> Seamless workflow between Bitbucket commits/PRs and Jira issues is its main draw. Also integrates with Trello, Confluence, Opsgenie etc.</li><li><strong>Bitbucket Pipelines:</strong> Integrated CI/CD configured via a <code>bitbucket-pipelines.yml</code> file within the repository.</li><li><strong>Code Insights:</strong> Allows surfacing information from scanning/testing tools directly within Pull Requests.</li><li><strong>Free Tier:</strong> Offers free private repositories for small teams (up to 5 users), including CI/CD minutes.</li><li><strong>Deployment tracking:</strong> Integrates deployment information back into Jira issues.</li></ul><h6>Strengths</h6><ul><li>Unbeatable integration if your team is heavily invested in the Atlassian suite (Jira especially).</li><li>Competitive pricing, potentially cost-effective for small teams needing private repos and basic CI/CD.</li><li>Simple and effective built-in CI/CD with Pipelines for many common use cases.</li><li>Clean and straightforward user interface.</li></ul><h6>Tradeoffs</h6><ul><li>Smaller developer community compared to GitHub or GitLab.</li><li>CI/CD (Pipelines) may be less flexible or powerful than GitHub Actions or GitLab CI for very complex scenarios.</li><li>Fewer built-in features compared to GitLab's all-in-one approach (relies more on integrating other Atlassian tools).</li><li>Less focus on open-source community features than GitHub.</li><li>Mercurial support is effectively gone for practical purposes.</li></ul><h6>Use Cases</h6><p>Teams already using Jira extensively for project management, organizations standardized on Atlassian tools, small teams looking for cost-effective private repositories with integrated CI/CD.</p> +<h6>Core Offerings</h6><p>Git repository hosting (Mercurial support was fully removed in July 2020; all existing Hg repos were permanently deleted by March 2022), Pull Requests, integrated CI/CD (Bitbucket Pipelines), code search, deep issue tracking integration (Jira), project tracking integration (Trello).</p><h6>Key Features</h6><ul><li><strong>Atlassian Ecosystem Integration:</strong> Seamless workflow between Bitbucket commits/PRs and Jira issues is its main draw. Also integrates with Trello, Confluence, Opsgenie etc.</li><li><strong>Bitbucket Pipelines:</strong> Integrated CI/CD configured via a <code>bitbucket-pipelines.yml</code> file within the repository.</li><li><strong>Code Insights:</strong> Allows surfacing information from scanning/testing tools directly within Pull Requests.</li><li><strong>Free Tier:</strong> Offers free private repositories for small teams (up to 5 users), including CI/CD minutes.</li><li><strong>Deployment tracking:</strong> Integrates deployment information back into Jira issues.</li></ul><h6>Strengths</h6><ul><li>Unbeatable integration if your team is heavily invested in the Atlassian suite (Jira especially).</li><li>Competitive pricing, potentially cost-effective for small teams needing private repos and basic CI/CD.</li><li>Simple and effective built-in CI/CD with Pipelines for many common use cases.</li><li>Clean and straightforward user interface.</li></ul><h6>Tradeoffs</h6><ul><li>Smaller developer community compared to GitHub or GitLab.</li><li>CI/CD (Pipelines) may be less flexible or powerful than GitHub Actions or GitLab CI for very complex scenarios.</li><li>Fewer built-in features compared to GitLab's all-in-one approach (relies more on integrating other Atlassian tools).</li><li>Less focus on open-source community features than GitHub.</li><li>Mercurial support is fully gone — all Hg repos were permanently deleted in 2020–2022.</li></ul><h6>Use Cases</h6><p>Teams already using Jira extensively for project management, organizations standardized on Atlassian tools, small teams looking for cost-effective private repositories with integrated CI/CD.</p> </div> </div> </div> @@ -336,7 +336,7 @@ </div> </div> <div class="collapse collapse-content" id="collapseChoosing"> -<h6>Choosing the VCS System (Git vs. Mercurial)</h6><ul><li><strong>Default Choice:</strong> <span class="term">Git</span>. It's the overwhelming industry standard. Choosing Git ensures maximum compatibility, community support, available talent, tooling options, and platform choices.</li><li><strong>Consider Mercurial Only If:</strong> You have a strong, specific reason, such as maintaining large legacy Hg projects, being part of an organization deeply committed to it (like Meta), or having a team that vastly prefers its specific model and is aware of the ecosystem limitations. Be prepared for fewer hosting options and potentially less community support.</li></ul><h6>Choosing the Hosting Platform (GitHub vs. GitLab vs. Bitbucket vs. Azure DevOps)</h6><ul><li><strong>Ecosystem Integration:</strong> How well does it fit with your other tools? +<h6>Choosing the VCS System (Git vs. Mercurial vs. Jujutsu)</h6><ul><li><strong>Default Choice:</strong> <span class="term">Git</span>. It's the overwhelming industry standard. Choosing Git ensures maximum compatibility, community support, available talent, tooling options, and platform choices.</li><li><strong>Consider Mercurial Only If:</strong> You have a strong, specific reason, such as maintaining large legacy Hg projects. Note that no major hosting platform supports new Hg repos, and former heavy users like Meta have moved to alternatives (Meta now uses their own Sapling system).</li><li><strong>Watch: <a href="https://jj-vcs.dev/" rel="noopener noreferrer" target="_blank">Jujutsu (jj)</a>:</strong> A Git-compatible VCS gaining significant traction (used internally at Google; 28k+ GitHub stars; v0.40 as of April 2026). It offers a simpler mental model (no staging area, first-class conflict handling, anonymous branches) while reading/writing Git repositories natively — allowing gradual adoption alongside Git. Still pre-1.0 with ecosystem gaps (limited IDE integration, no Git submodule support), but production-ready for individual developers and small teams.</li></ul><h6>Choosing the Hosting Platform (GitHub vs. GitLab vs. Bitbucket vs. Azure DevOps)</h6><ul><li><strong>Ecosystem Integration:</strong> How well does it fit with your other tools? <ul> <li><span class="term">Bitbucket:</span> Best for deep Atlassian (Jira, Confluence) integration.</li> <li><span class="term">Azure DevOps:</span> Best for deep Microsoft Azure and Microsoft Entra ID integration.</li> @@ -435,8 +435,9 @@ </a> </div> <p class="mb-2"> - © 2025 David Veksler · Compiled & expanded based on software configuration management research and SCM best practices. + © 2026 David Veksler · Compiled & expanded based on software configuration management research and SCM best practices. </p> + <p class="mb-2 text-muted small">Last verified: 2026-06-21</p> <div> <a class="mx-2 link-secondary" href="https://www.linkedin.com/in/davidveksler/" target="_blank" title="David Veksler on LinkedIn"> <i class="bi bi-linkedin"></i>