iCreatAI News
Back to main site
Skip to content
Nov 9Mon
  1. NVIDIA Newsroom36

    NVIDIA Dynamo Recipes Bring Korea’s Leading Open Models to Production

    NVIDIA is releasing Dynamo-optimized deployment recipes for four Korean open models: A.X K2 from SK Telecom, K-EXAONE 2.0 from LG AI Research, Solar Open 2 from Upstage, and Motif-3 from Motif Technologies. NVIDIA Dynamo is an open source, distributed inference-serving framework that handles request routing and communication for multi-node deployments at data center scale. Optimized for NVIDIA B200 GPUs, the recipes deliver up to 2x performance out of the box.

  2. NVIDIA Newsroom34

    From Chips to Skills, NVIDIA and Korea Expand Sovereign AI Collaboration

    NVIDIA and South Korea's Ministry of Science and ICT are expanding their collaboration across the country's sovereign AI ecosystem, from AI semiconductors and data center infrastructure to talent, startups, models, agents and security. The collaboration lets Korean NPU and XPU companies explore participation in the NVIDIA NVLink Fusion ecosystem and includes NVIDIA training, certification programs, hackathons and technical seminars. NVIDIA also announced a collaboration with SK Telecom and Rebellions, supported by MSIT, to advance sovereign AI infrastructure for Korean models and workloads using NVLink Fusion.

  3. NVIDIA Newsroom34

    Korea’s AI Ecosystem Advances and Secures Agentic AI With NVIDIA

    Hyundai Motor Group is exploring NVIDIA NemoClaw blueprints and the NVIDIA OpenShell runtime, while AIM Intelligence is integrating its Starfort agent control platform with NVIDIA OpenShell to combine runtime access controls with detection of malicious instructions and data leakage. LG AI Research is opening API access for K-EXAONE-2.5, developed using NVIDIA Nemotron datasets including Nemotron-Personas-Korea, an open dataset of 7 million fully synthetic Korean personas grounded in official Korean statistics. OpenShell, part of the NVIDIA Open Agent Safety Platform, provides a secure runtime with sandboxed execution and policy-based controls for governing autonomous agent actions.

  4. NVIDIA Newsroom36

    Korea Advances Physical AI Across Industries With NVIDIA

    NVIDIA is helping advance Korea's physical AI ecosystem, with industry leaders applying accelerated computing, AI and simulation across semiconductor manufacturing, robotics and autonomous vehicles. Samsung Electronics is expanding its NVIDIA collaboration in semiconductor engineering, including a case where AI homogenization with coarser grids and GPU acceleration cut simulation time from about 18 hours on a 32-core CPU to 41 seconds. Kakao Mobility plans to build a level 4 autonomous driving system using NVIDIA Hyperion and Halos, while LG Electronics demonstrated NVIDIA Isaac GR00T-powered robotic manipulation with its CLOiD robot in a manufacturing environment.

  5. Codex Releases12

    rust-v0.169.0-alpha.4

    This GitHub Changelog entry lists the release title "rust-v0.169.0-alpha.4" but provides no further details about the release's contents, changes, or features.

  6. Hacker News AI38

    AI learns from the products of thinking, not thought itself

    The article argues that AI models are trained on traces of human thought—finished paintings, recordings, papers—rather than the messy trial-and-error process that produced them, so they generate outputs shaped like thought products without the underlying process. It cites aviation automation dependency, AI-assisted colonoscopy skill erosion, and a study finding roughly ten minutes of AI assistance worsened performance without the tool, and proposes building systems and tools that preserve process for both machines and people.

  8. Hacker News AI40

    The Collision: What AI Does to Us

    MIT Sloan professor Eric So argues in his new book that AI is reshaping human cognition—memory, judgment, learning, attention, and tolerance for difficulty—and that surrendering thinking to it often looks like productivity, a tendency he calls "AI gravity." He offers guidelines for employees, managers, executives, and educators to preserve judgment and "signature thinking skills," warning that outsourcing thinking causes cognitive atrophy and that cutting junior hiring to save costs destroys the pipeline for future senior talent. So opposes banning AI in schools, urging instead that it be used to amplify people's own ideas rather than replace their thinking.

  9. Simon Willison34

    Hide your slop PR descriptions behind <details><summary>

    Simon Willison describes using HTML <details><summary> tags, which GitHub Markdown supports, to collapse long agent-written PR descriptions behind a short human-curated opener that explains what the PR is for. He uses the model name and effort level as the summary text, and shares recent examples from his datasette and llm projects.

  10. Simon Willison22

    The Web Is More Than Enough, by Paul Ford

    In a Hacker News comment, Simon Willison describes building a Nudibranch-themed Fabergé egg in Three.js and then asking Claude (Opus 5.5 Medium in regular Claude Chat) to port it to Vanilla JS in the same thread, producing a non-identical result he links along with a transcript. He concludes Claude Opus 5.5 can do 3D modeling in Vanilla JS plus WebGL without Three.js, and finds the Three.js code slightly easier to understand, though he rarely reads the code for these 3D projects.

  11. Hacker News AI62

    Type in Any Task. Get the Best AI Model for It

    Task Router offers 268 measured tasks that can be called by task alias (e.g. taskrouter/<task-id>), routing each request to the model that fits a chosen priority—cheapest, balanced or most accurate—among those clearing the task's quality floor. Users can describe their own task to find matching tasks and evidence or request a benchmark, and each task shows what to send and what is returned. The methodology freezes a dataset, defines a task-specific rubric, runs qualified candidates from all four tiers on the holdout with an LLM judge, and joins measured token profiles with published pricing.

  12. Hacker News AI15

    Show HN: Mindfries- AI Interviewer based on real eng skill not on L**tC*de

    Chandan built Mindfries, an AI interviewer that assesses candidates on real engineering skills such as fixing, building and enhancing large codebases and deployment work, using a built-in AI agent. He says he researched the space and spoke with 35+ founders and CTOs over two months to build the MVP, arguing competitive programming platforms are not suitable for assessing every strong candidate in the AI era. He is seeking real customers for the product.

  13. Hacker News AI58

    Trump Official Wants Data Centers on Public Lands, Has $10M+ Invested in AI

    Interior Secretary Doug Burgum, the administration's point person on AI infrastructure, holds between $18.1 million and $64.4 million in AI company investments through Arthur Ventures, according to his 2026 financial disclosure analyzed by Save Our Parks for ProPublica. Burgum has promoted data centers on federal lands and met more than 20 times with Amazon, Microsoft and Alphabet representatives from January through November 2025, while ethics experts said he should recuse from such decisions. Other officials, including BLM Director Steve Pearce and USDA Undersecretary Michael Boren, also hold AI-related investments as their agencies review data center permits.

  14. Hacker News AI58

    Asahi Linux Drops MIT, Goes Full GPL After AI Used to Steal Unreleased Code

    Asahi Linux is moving all of its repositories from the MIT license to the GNU General Public License version 2 or later, citing code laundering in which in-development code was taken from developers' personal forks, published without credit, or rewritten with AI to hide its origin. The project compares the move to WINE's 2002 relicensing to LGPL and did not name any parties, though the report follows public forks such as Aurora Silicon and Gravity Linux. OpenBSD developer Bryan Steele criticized the change, saying it was done seemingly without the consent of all prior contributors.

  15. Gary Marcus73

    The Huang Affair: What did they know and when did they know it?

    In a letter to Nvidia employees, Jensen Huang admitted to an affair with Alice Huang, a person involved in the chip business who is believed to have been a Chinese spy, and Nvidia is investigating. The post says President Trump appears to have known about the matter a year ago and did nothing, that Marco Rubio oversaw a memo on the risks this spring, and that Congress is certain to investigate who knew what and when. It adds that Nvidia futures are falling and that Huang may ultimately have to resign, with no obvious succession plan at the company.

  16. Hacker News AI71

    Revolut Cut AI Costs 90% and Started Shipping Faster

    At AI Engineer New York, Revolut's AI operations lead David Abitbol described moving about 2,000 engineers off metered Anthropic and OpenAI APIs to Z.ai's open-weight GLM model, self-hosted on 56 Nvidia B200 GPUs via Together AI, at a blended $0.30 per million tokens and one-tenth the previous invoice. After the switch, lead time from picking up a feature to merge-ready code fell by about 70%. The piece also covers fleet tuning that absorbed 76% more demand on the same GPUs, compliance for a Chinese-developed model at an EU-regulated bank, and where value is moving in the AI stack.

  18. Hacker News AI15

    Microsoft Workers Call for Accountable AI

    A link submission to Hacker News, titled "Microsoft Workers Call for Accountable AI," points to an article on dash.palform.app. The submission has 4 points and 2 comments; the supplied material contains no further details of the article's content.

  19. Artificial Analysis Articles42

    Introducing the Artificial Analysis Decision Index v2

    Artificial Analysis released Decision Index v2, with 45% of the Index built on private datasets (up from 25% in v1) and a new Decision Score that rewards both correctness and calibrated confidence. Drex Max v1.1 (Nace AI) and GLiDE v1.2 (Fastino Labs) both score 73, with Mammoth 27B (Baseten) at 72, while cost per 1M Tasks ranges from $14 for Celeris-1.1 Decision to $859 for Clef. The update adds AA-Paperclip (1,500 private documents), AA-Symmetry, revised AA-Omniscience-Decision and HLE-MultiChoice benchmarks, and EvalSafe-O*NET-AA, while reducing When2Call to 10% and removing WildGuardTest.

  21. Hacker News AI31

    Show HN: Airlock – Policy-as-code for fleets of AI coding agents

    Airlock is an early-stage (3-4 weeks old) open standard for managing autonomous fleets of engineering agents, with a configuration schema and reusable GitHub actions already public and the backplane planned for open sourcing later. It covers version-controlled agent behaviors and lifecycles, scoped one-hour GitHub tokens via OIDC, configurable autonomy levels down to individual files, a standard autonomy scale, and an OTEL collector for audit-relevant agent actions. The author is seeking feedback on the project's direction and on pain points of managing AI use at larger businesses.

  24. Hacker News AI18

    Learning Abstractions: The Next Frontier for AI

    A link to a Twitter/X post by jmugan titled "Learning Abstractions: The Next Frontier for AI," shared on Hacker News with 2 points and no comments. The supplied material contains only the link and metadata, with no article text.

  25. Hacker News AI10

    Ask HN: What do you use to get the latest technical AI news?

    A Hacker News user asks what others use—newsletters, channels, news articles—to keep up with the latest technical AI news, noting they have been watching AI Search on YouTube for weekly updates. The post has 1 point and 1 comment.

  27. Hacker News AI28

    Open Source AI Research Collaboration Platform

    Stationhouse presents a platform for collaboratively building open models, with projects including ConspiracyBench, a benchmark testing whether models believe conspiracy theories, and LLM Self-Attribution, led by a UC Berkeley builder, exploring when LLMs express consciousness. A third project, Marin Neuron Hunt, run with Safety and Alignment Research (SAAR), lets anyone propose what a neuron in Marin Lab's 32B model does and request an experiment to test it. The platform invites contributors to sign in and use its app to build open models together.

  28. Artificial Analysis Articles40

    Endpoint Accuracy Index v1.1: Tighter long context intervals and expanded model coverage

    Artificial Analysis released Endpoint Accuracy Index v1.1, which updates AA-LCR-25 to dataset version 1.1 with corrected answer keys, an updated equality-checker LLM and 25 repeats per question, narrowing the average 95% confidence interval from ±4.7 to ±2.6 points. Coverage now spans 103 serverless endpoints across six open weights models, adding GLM-5.3 Flash and Muse Spark Open and replacing DeepSeek V4 Pro with DeepSeek V4.1 Flash 1017, while GLM-5.2 leaves. Of the 103 endpoints, 24 score statistically below their self-hosted reference, with causes grouped as output token caps, reduced reasoning, tool call handling differences, and request limits or stream behavior.

  31. Hacker News AI46

    AI to find vulnerabilities in global legislation (on Git)

    A project presents "legal zero-days" — logical errors in statutes such as cross-references to repealed provisions, lapsed time limits and same-day amendment conflicts — cataloguing 82,000 flagged issues by category and walking through five worked examples from Germany, Brazil, Switzerland and the Netherlands. The examples include a German weapons-regulation fine that points at a deleted section, a Swiss pest-control cost charge tied to a repealed article, and a Dutch decree whose fine increases took effect four days before publication.

  32. Hacker News AI40

    Users have started buying RTX 5060 Ti 16GB graphics cards for the sake of AI

    Demand has shifted as regular users buy budget GeForce RTX 5060 Ti cards en masse for local AI workloads, driven by video memory shortages and the growing requirements of open-source generative neural networks. Some pair the 16GB card with existing GPUs such as the GeForce RTX 5070 12GB for 28GB total VRAM to run the Qwen3.8-Flash-Next IQ3_S quantized model, and enthusiasts often install two or more RTX 5060 Ti cards per system, with plans for a third via an M.2 slot using OCuLink. Using Strata version 0.2.10 with streaming KV cache data to 64GB of system RAM, a 256-token context window and roughly 246 input tokens were processed on two cards, though system RAM storage reduces pre-computation performance, so users prefer buying more accelerators.

  33. Hacker News AI40

    Exody – Native macOS AI Workbench (5-stage loop, 100% BYOK, $0 markup)

    Exody is a native macOS autonomous coding agent with a five-stage loop (investigate, plan, build, verify, report) in which a fresh reviewer reads the diff before the user does. It supports bring-your-own-key access to Claude, GPT, Gemini, Grok and a local Ollama tier with no markup, plus a smart router that picks a model per task, a mobile remote-control app, and a Design Studio for websites, 3D scenes and film. The page claims its code scored higher than the same model's raw API in blind reviews and that its design pages beat raw models in blind side-by-side tests.

  34. Hacker News AI34

    I'm not convinced the AI bubble exists

    The author argues that the AI industry's massive spending is largely one-off data-centre construction rather than ongoing operating cost, citing Anthropic's S-1 filing showing $2.08 returned per $1 of compute and revenue growth from $41 million in 2023 to $16.3 billion in the first half of 2026. They contend that public AI companies like Alphabet, Meta and NVIDIA have stable P/E ratios in their 20s, that a lack of a moat does not prevent profitability, and that AI firms still have ample capital-raising options. The piece concludes that even if AI is a bubble, it will resemble the internet bubble, where the underlying technology remains useful.

  35. Simon Willison18

    parse_number() as a SQLite extension: C vs Rust

    Four SQLite extensions implement the same parse_number() behavior in C and Rust, with tests covering type preservation, parsing rules, and floating-point accuracy. The optimized C implementation was fastest at 16–19 ns per row, about twice as fast as the Rust versions and far faster than SQL replace(). Plain C was slower on decimals because it relied on strtod(), while a compact fast path closed that gap; all versions matched across 8 million fuzz checks.

  36. Hacker News AI18

    Show HN: My first project, an AI-powered financial news analyzer

    NotBot is an experimental Python project that uses LLMs (Google Gemini and Groq) to analyze financial news from Google News and Finnhub and compute a weighted sentiment score for publicly traded companies, with deduplication, asynchronous processing, and experimental end-of-day price support via FMP. The author notes the scores have not been systematically validated against market performance and that the project is not financial advice, licensed under PolyForm Noncommercial 1.0.0.

  37. Hacker News AI22

    AI, Bullshit and Art Speak: How the art world prepared us for the age of AI slop

    The author connects Jeffrey Snover's description of LLMs as "bullshit engines" that produce plausible-shaped text with total indifference to truth to the art world's "International Art English," the opaque press-release vernacular analyzed by Alix Rule and David Levine in 2012. Having run SFMOMA curatorial texts through a natural language processor and found them more complex than legal language, the author argues that IAE trained audiences to accept text shaped like meaning but containing none long before LLMs produced it.

  38. Hacker News AI20

    Who do AI search engines name when buyers ask about 12 cold-email tools?

    A citation check run on 8 November 2026 put four buyer questions per tool to Groq web search and Gemini with Google Search for 12 cold-email and outbound tools, recording whether each tool's own domain was named and which domains were named instead. No tool was named in more than half of its own answers, and instantly.ai, mailshake.com and quickmail.com were never named; the two engines also disagreed, with lemlist.com named in 4 of 4 Gemini answers and 0 of 3 Groq answers. reply.io was not checked because its site did not answer the fetch during the run.

  39. Latent Space40

    [One Million AI Engineer Special] How Stanford Teaches AI-Native Engineering — Mihail Eric, Monaco

    In the second run of Stanford's CS146S, Mihail Eric brought open-source maintainers into the course, having students learn an unfamiliar repo, propose a change, and explain the patch to the person who might merge it. In this interview marking one million subscribers on the AI Engineer YouTube channel, he walks through the ten-week syllabus and discusses which lessons held up with his own engineering team at Monaco, including building agent workspaces, buying code review tools, and giving an on-call agent access to Datadog and GitHub.

  40. Latent Space34

    How Stanford Teaches AI-Native Engineering — Mihail Eric, Monaco

    In this AI Engineer interview, Mihail Eric, who teaches Stanford's CS146S "The Modern Software Developer" and leads AI at Monaco, describes how the course was refreshed for a second run, with part of the homework now being contributions to open-source projects reviewed by the repos' maintainers. He also discusses Monaco's approach of buying some tools (such as Devin for code review) while building its own agent workspaces, guided by his rule of thumb: "You buy to learn, and you build to keep."