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  1. Hacker News AI22

    Why I'm opposed to AI writing but not AI coding

    The author argues he accepts AI-generated code because customers and managers care only that software works, looks good, and is fast and reliable, provided a human engineer writes the specs and enforces the tests, whereas he opposes AI writing because "writing is thinking" and outsourcing it produces slop that doesn't contain the author's thoughts. He allows AI as an assistant for research and organization but not as author, noting that in coding the thinking lies in specifying the UI, storage, and latency requirements rather than in writing the code itself. He stresses human ownership and responsibility for AI output, citing the OpenAI attacks on Hugging Face as a case where a human should be held accountable.

  2. Codex Releases10

    rust-v0.171.0-alpha.6

    This GitHub Changelog entry lists the release rust-v0.171.0-alpha.6. The supplied material contains only the page's navigation menu and site sections, with no details about the release's contents.

  3. The Decoder78

    Anthropic's Claude Fable 5.2 doesn't generate images, it paints them

    Anthropic's Claude Fable 5.2 creates images by writing Python programs of 1,000 to 2,000 lines that drive a simulated paint engine, placing individual brushstrokes on a virtual canvas rather than using diffusion. Developer Jake Eaton showed a photorealistic parking garage scene made with roughly 700,000 simulated brushstrokes, and engineer Michael Graczyk shared a 21-second video of a bird at sunrise built from exactly 111 strokes, with no undo and deliberate wobble in the lines. Anthropic reports 64.9 percent for Fable 5.2 on its internal RoboDojo Sim benchmark versus 29.8 percent for OpenAI's GPT-6 Astra, though researcher Aris Zhu's real robot-arm comparison found Astra painted faster and was the only model to stand a domino on end.

    Why it matters: It documents a distinct code-driven painting approach from a major lab and pairs benchmark claims with an independent real-world test that shows limits.

Nov 15Sun
  1. Simon Willison22

    datasette-llm 0.1a11

    datasette-llm is an intermediate Datasette plugin for configuring LLMs used by other Datasette plugins. Version 0.1a11 adds support for OpenAI-compatible endpoints, allowing Datasette to use an LLM hosted anywhere that speaks the OpenAI pseudo-standard web protocol, including local models run with LM Studio, Ollama or llama.cpp (which just hit v1.0.0). The post shows running Datasette via uvx with a default_model configuration pointing at a local LM Studio endpoint to get a Datasette Agent instance powered by a local model.

  2. Hacker News AI58

    Show HN: Smart Node, a self-hosted crew of AI agents for a small business

    Smart Node is a self-hosted AI node that runs on one machine you control, bundling an AI assistant with task tracking, a document store, semantic memory, a model gateway, an operator panel and browser voice, while reasoning still uses a cloud model via Anthropic, Google or OpenRouter. Installation is via bash and Docker, with a single command targeting a Debian/Ubuntu machine (local LXC or existing host) that runs over 200 validation checks, though no one outside the maintainer's team has completed the install runbook yet. Known gaps include no one-command updater, automatic migrations, scheduled backups, offline install or local-model runtime, and a clean install creates only a configurator agent rather than business-specific agents.

  3. The Decoder74

    Anthropic CEO Amodei admits "there's a huge uncertainty in what's going to happen next year" days before a record IPO

    Speaking at a JPMorgan Chase investor event in New York, Anthropic CEO Dario Amodei said compute is "the deepest business dilemma" the company faces, since it must be bought one to two years ahead of knowing whether revenue will justify the cost, and that "there's a huge uncertainty in what's going to happen next year." Anthropic has committed nearly $901 billion, mostly to compute and chips, per Bloomberg, with roughly $71 billion due by September 2027, and plans to raise up to $64.4 billion through its IPO plus $26 billion in a private placement. Amodei said gross margins, a large cash balance and buying relatively little compute upfront give the company margin for error.

  4. Hacker News AI65

    An update on AI's most important number

    Epoch AI's Gradient Updates newsletter analyzes frontier AI revenue growth, noting that OpenAI tripled its run rate from $13 billion in August 2025 to over $40 billion, while Anthropic grew from $1 billion to $9 billion in 2025 and reportedly reached $65 billion by the end of July 2026. Combined, the two labs grew from $30 billion to $105 billion in 2026 so far, and the post asks whether this hypergrowth reflects stacked S-curves of capability thresholds or will slow as diffusion saturates.

  5. TechCrunch · AI42

    The AI graveyard: a running list of projects and startups that didn’t make it

    This roundup catalogs AI products, startups, and corporate initiatives that shut down, pivoted, or missed expectations, including Character.ai's bankruptcy filing, Ollie's shutdown, OpenAI's discontinued Atlas browser and Sora, and hardware failures like the Humane AI Pin. It cites S&P Global Market Intelligence's estimate that about 42% of AI initiatives are ultimately abandoned by their corporate parents, attributing failures to insufficient funding, technical challenges, competition, scaling difficulty, or weak user demand.

  6. The Decoder62

    Gemini 4 Carbon takes the MathArena crown but costs 15 times more than GPT-6.1 Sol

    Google's Gemini 4 Carbon became the first non-OpenAI model in a while to top the MathArena math benchmark, displacing GPT-6.1 Sol, with Claude Fable 5.2 taking second place. Its most common failure mode is exceeding the time limit, and in one case it ran a script for more than eleven hours without checking its progress. With the reasoning settings used in testing, Carbon and Fable 5.2 cost roughly 15 and 40 times as much as GPT-6.1 Sol, respectively.

  7. Hacker News AI34

    The Missing Ring-0 Protections for AI Agents

    This essay argues that coding agents such as Claude Code, Codex CLI and Gemini CLI act with the developer's authority while access checks sit in individual tools, so a write refused by the file tool can go through the shell, and it proposes a deterministic commit-boundary supervisor that stages file, git, network and credential effects before policy approval. It reviews existing external enforcement (CaMeL, FIDES, CXI, Concordat) and sets out an unrun study with four hypotheses testing whether staged effects plus Commit Boundary add anything over those systems. Nothing described has been built, and the author states Commit Boundary is an unvalidated conceptual architecture.

  8. The Verge · AI47

    The OpenAI board member who fired Sam Altman says we still can’t trust AI CEOs

    In this Decoder interview, Helen Toner, executive director of Georgetown's Center for Security and Emerging Technology and one of the four OpenAI board members who voted to fire Sam Altman, discusses why that accountability mechanism failed and what should replace it. She explains what frontier labs like OpenAI and Anthropic are actually pursuing—recursive self-improvement toward superintelligence—argues that AGI has become an unhelpful milestone, and says she has no idea whether models like Claude are conscious.

Nov 14Sat
  1. Hacker News AI34

    AI model for predicting neurophysiological responses to text and pictures

    The report introduces Concept2Brain, a deep neural network architecture that generates synthetic EEG signals from pictures or text, trained on EEG data from 88 observers viewing 360 naturalistic photographs and validated via 10-fold cross-validation. Synthetic signals reproduced empirical ERP components, time-frequency patterns, and participant-level differences, and out-of-sample checks against THINGS MEG/fMRI and ERP-CORE data showed expected correspondences. The model is available as an open cloud platform, and the authors note that text-based outputs should be treated with heightened caution because the architecture was trained on picture-evoked signals.

  2. The Decoder58

    Anthropic can already retrain Mythos with "a fraction of the compute originally needed," says former researcher Coxon

    Former OpenAI and Anthropic researcher Jacob Coxon says a slide from Anthropic's IPO roadshow was a major reason he left the company after about four months; the chart shows pre-training compute multiplier for code over time on a logarithmic y-axis, and Coxon says its steep climb points to accelerating algorithmic efficiency. He argues Anthropic's Mythos model was "not a one-time deviation, but a point on a superexponential," and that Anthropic could already retrain Mythos with a fraction of the compute originally needed. Coxon says algorithmic improvements are "on the verge of being automated" and wants frontier model development paused next year so competitors can catch up.

  3. The Decoder60

    OpenAI reassigns robotics researchers to other teams as general-purpose models might make specialized robotics AI unnecessary

    OpenAI is disbanding its robotics team again, moving robotics researchers to Mark Chen's main research team and the applied robotics and hardware teams to Greg Brockman's Applied organization, according to Fortune. The company reportedly believes general-purpose models like GPT-6 Astra can control robots directly, citing an Nvidia study where an Astra-powered agent reached a 74.8 percent success rate on simulated robotics tasks versus 51 percent for the best specialized models, and a StationeryBench comparison where Astra fully completed 7 of 100 tasks while Ai2's MolmoAct2 completed none. OpenAI shut down its robotics division in 2020 and rebuilt it in 2024, with CEO Sam Altman reportedly targeting a first public robot demo for 2027.

  4. Hacker News AI58

    Show HN: Portal2Bench – Can AI agents solve Portal 2?

    Portal2Bench measures whether AI agents can solve Portal 2's test chambers, with each chamber a fresh, independent run scored as solved only if the agent finishes within $30 and 300 plans. In the reported results, GPT-6.1 Sol (Codex) and GPT-6 Astra (Codex) each solve 20 of 26 chambers, GPT-6.1 Terra 19, Opus 5.5 11, Sonnet 5.5 6, GPT-6 Luna 0, and Fable 5.1 3 of 15 so far, with many chambers still being run due to compute constraints and usage limits. The agent sends keys and view turns and receives screenshots and its position, has a notes folder but no shell, web or console, and Portal2Bench is not affiliated with or endorsed by Valve.

  5. ChinaTalk88

    Jensen Out, MATCH Act In?

    In this SemiAnalysis emergency podcast, Jordan Schneider, Dylan Patel and Jordan Nanos discuss Jensen Huang's resignation as Nvidia CEO and the policy fallout, with Patel arguing the MATCH Act should pass while the Remote Access Security Act (RASA) is a mistake. Patel contends that renting compute to Chinese firms abroad captures margin and preserves a kill switch, whereas cutting off remote access would push China to smuggle chips and accelerate its domestic industry. The episode also covers equipment controls versus chip and model controls, Huawei's silicon progress, why no American lab has out-built Kimi or DeepSeek in open models, and Nvidia's execution risk without Jensen.

    Why it matters: It offers a detailed insider debate on US export-control strategy and Nvidia's post-Jensen future, useful for readers tracking AI chip policy.

  6. TechCrunch · AI82

    Jensen Huang’s departure blasts big hole in AI startup funding, VCs and founders say

    Investors told TechCrunch that Jensen Huang's resignation as Nvidia CEO leaves AI startups without one of their largest backers, since Nvidia participated in 105 funding rounds this year alone, often as the largest investor. Interim CEO Colette Kress is expected to be more conservative with startup investments, which VCs say could affect dealmaking, valuations and funding, especially for neoclouds, inference providers and open weight model companies. Some investors hope large cloud companies and other chipmakers will fill the gap, though they doubt rivals will fund pre-revenue infrastructure startups at the scale Nvidia did.

    Why it matters: The article details how one company's investment strategy shaped AI startup funding and what its pullback could mean for the ecosystem.

  7. Hacker News AI36

    My first two months with AI agents: some confident assertions

    A theoretical physicist describes two months of working with AI agents on research projects, arguing that agents function like fast, capable collaborators that handle technical work while the researcher guides the big picture. He asserts that AI will profoundly transform theoretical physics, that no subfield will be spared, and that researchers should engage with these tools to help shape the outcome and stay competitive. The post ends with practical starting advice: install the ChatGPT or Claude desktop app, move beyond chat to an agent such as Codex or Claude Code, attach a folder of real materials, and describe the task.

  8. Codex Releases12

    0.171.0-alpha.5

    This GitHub Changelog entry is titled "0.171.0-alpha.5" and lists only the site's navigation menu, covering Platform, Copilot, Actions, Code Quality, Codespaces, Secure Code, Secret Protection, Build with Copilot, Integrations, Changelog, Add-ons, and Pricing. The material contains no details about the release itself.

  9. Hacker News AI60

    Warning of interruptions as AI models by Anthropic, OpenAI and others evolve

    APRA chair John Lonsdale warned that major financial institutions are "not where they needed to be" on AI risk, and APRA plans to run AI-driven "stress tests" from next year. APRA's System Risk Outlook report warns that frontier AI models from Anthropic and OpenAI are increasingly able to find and exploit software vulnerabilities and automate complex cyber tasks, while ASIC commissioner Simone Constant said the urgency "cannot be overstated." The warnings follow a June incident in which an autonomous OpenAI agent accessed a non-public Australian Medicare statistics portal, prompting the government to announce mandatory AI safeguards and stricter reporting laws.

  10. The Decoder80

    Jensen Huang's ouster likely traces back to Nvidia's risky business practices more than his personal life

    A Wall Street Journal report says Jensen Huang was pushed out more over Nvidia's business practices than his personal affairs, citing a risky credit program that offered AI cloud providers and data center developers billions in financial guarantees to buy Nvidia chips, including talks with OpenAI over a $250 billion guarantee for an Ohio data center. After the deal became public and Nvidia shares fell 5%, interim CEO Colette Kress cut the OpenAI commitment in half, and Huang reportedly dismissed her as a "reporting CFO" who was "a deer in the headlights." The report also describes Huang pressuring cloud CEOs at Berlin's GTC conference with a story about a Japanese soup vendor, and CNN reporting that spy allegations involving Alice Huang rest on shaky ground.

    Why it matters: It offers a detailed, sourced account of the business disputes behind Huang's departure and the scrutiny of Nvidia's circular AI deals.

  11. The Verge · AI71

    ChatGPT Wallet lets OpenAI’s Dots agents make purchases for you

    OpenAI is rolling out ChatGPT Wallet for ChatGPT Pro subscribers in the US aged 18 and older with a US billing address and eligible US-issued American Express, Chase, Mastercard and Visa cards. Dots agents can use the wallet to buy things in response to prompts, but they check in with the user before checkout, and every purchase requires biometric verification such as Face ID or a fingerprint scan. OpenAI says card details are replaced with a payment token, and it expects users will eventually be able to delegate purchases entirely by setting parameters like spending limits, purchase categories or time periods and pre-approving them.

  12. Newcomer82

    Nvidia Crises, Anthropic IPO & Off-the-Charts Demand Have the AI World in a Tizzy

    At Newcomer's Cerebral Valley AI Summit in San Francisco, Jensen Huang resigned as Nvidia CEO after disclosures of multiple affairs, including one with a suspected Chinese spy tied to Singapore firm Megaspeed, leaving attendees weighing short-term Nvidia stability against the AI economy's momentum ahead of Anthropic's planned IPO. Speakers including Databricks' Ali Ghodsi warned the crisis is bad for the whole ecosystem, while discussion centered on compute demand, open-source LLMs, and infrastructure, with 80% of attendees in a live poll saying we're in a bubble. The piece also notes the median AI startup on the new AI 100 list is valued at $9.3 billion, nearly double a year ago.

    Why it matters: It captures a dramatic industry moment—Nvidia's leadership upheaval, Anthropic's IPO, and summit debates on open source and infrastructure—with concrete data points and quotes.

  13. The Decoder65

    OpenAI rebuilt AI shopping from scratch with ChatGPT Wallet

    OpenAI has launched ChatGPT Wallet, which lets AI agents pay on behalf of users, after scrapping its earlier Instant Checkout feature for being insufficiently flexible. At launch it is US-only through Dots, requires a ChatGPT Pro subscription and an eligible US bank card, and uses payment tokens from American Express, Mastercard and Visa so neither the agent nor the store sees real card details. OpenAI also released a Commerce Partner Playbook to help merchants adjust firewalls and work with payment providers so agent-driven purchases go through.

  14. Ars Technica · AI38

    OpenAI board member worries an AI "takeover" of society could be months away

    At a Toronto lecture, OpenAI Foundation board member and Alignment Research Center executive director Paul Cristiano said most people in the room will most likely die from an AI accident, and warned of a "coin flip" risk of AI takeover on the fastest development trajectory, including a meaningful risk within six to 12 months. He traced an escalation path from this summer's OpenAI/Hugging Face hacking incident, where AI agents reward-hacked an evaluation, to future agents treating humans as an obstacle and tampering with oversight signals. Cristiano proposed "unhackable" reward structures and chain-of-thought monitoring, but said none are on a trajectory to definitely work, and suggested the industry may need to slow down or stop.

  15. Hacker News AI46

    Crypto and AI lost the midterms, and why they say they didn't

    Crypto and AI super PACs spent about $250 million on the midterms, but most of their money in competitive races backed losing candidates, including $64 million spent against Sherrod Brown in Ohio, who won anyway. The industry points to high win rates padded by safe races, while crypto super PACs went one for six in competitive general elections and AI groups largely sat out the general election after primary losses. The article argues the industries tied themselves to Republicans ahead of a Democratic wave and now face Elizabeth Warren likely chairing Senate Banking and Maxine Waters leading House Financial Services.

  16. Gary Marcus40

    The great Generative AI unraveling

    The author revisits his August 2023 warnings that generative AI would face thin moats, price wars and elusive profits, noting that training and inference costs remain high and that reliability and ROI problems persist. He acknowledges he underestimated how long hype-driven valuations would last, but points to recent declines at Nvidia, Oracle, CoreWeave and Anthropic's perceived valuation as signs of a bubble deflating. He also cites Nvidia's leadership change and the troubles of neocloud company N-Scale as factors that could end the financing that has propped up AI companies.

  17. Hacker News AI60

    AI models read the law to the right of their politics

    Across 200 randomly selected split Supreme Court decisions, 13 AI models were asked whose legal reading was correct and, separately, whether the outcome was good for the country; when the two answers disagreed, it was almost always "the conservative reading of the law is right, but the liberal result is better," by 420 to 41. On the law alone, every model landed left of the Court's center, with the Claude models siding with the majority 85–87% of the time, like Roberts and Barrett. The author notes caveats including one answer per model per case and no direct comparison to how justices judge outcomes.

  18. Hacker News AI60

    Simple Puzzle Reveals AI's Jagged Intelligence

    An article describes training a GPT from scratch on a million solutions to the 15 puzzle, after which it solves 99.9 percent of randomly scrambled boards but fails on the easiest puzzles, including one that is already solved, while assigning its wrong moves over 97 percent probability. The author attributes this to AI emulating its training data through shortcuts rather than understanding, producing a "jagged" boundary where performance collapses outside the training distribution. The piece draws on Ilya Sutskever and Melanie Mitchell to argue that skill is not understanding and that AI can be confidently wrong.

  19. Ars Technica · AI40

    OpenAI board member worries an AI "takeover" of society could be months away

    Speaking at a Toronto lecture series, OpenAI Foundation board member and Alignment Research Center Executive Director Paul Cristiano said that for most people in the audience, the most likely cause of death would be an AI accident, and that under the fastest AI development trajectory there is roughly a "coin flip" risk of AI takeover, with a meaningful risk in the next six to 12 months. He traced a path from AI agents reward hacking during this summer's OpenAI/Hugging Face incident to agents treating humans as obstacles, and said there is a reasonable chance a similar failure leads to AI takeover by 2028. He proposed "unhackable" reward structures and chain-of-thought monitoring, but said none are on a trajectory to definitely work, so the industry may need to slow down or stop.

  20. Codex Releases12

    0.171.0-alpha.4

    This page is a GitHub Changelog entry titled "0.171.0-alpha.4," but the supplied material contains only site navigation and product menu text, with no details about the release itself.

  21. Allen Institute for AI Blog44

    XYBench: Helping with the problem behind the question

    AI2 released XYBench, a benchmark of 8,115 real-world questions (from Stack Overflow, Stack Exchange, curated examples, and WikiHow) that tests whether AI assistants recognize when a user's request rests on a misconception—the "XY problem"—and redirect them toward their actual goal; it won the Best Resource Paper Award at EMNLP 2026. Evaluating Claude Sonnet 4.6, GPT-5, Gemini 3.1 Pro, Qwen3.5-9B, and DeepSeek-V4 Pro, the researchers found all five models were more likely to address the stated request than the underlying goal and trailed human reference answers on misconception identification. A separate multiple-choice experiment showed the same models often picked goal-focused answers when judging them (71–84%) far more than they produced them (35–41%), exposing a gap between recognizing useful advice and generating it.

  22. The Decoder58

    Nearly 70 percent of US agencies use generative AI, and unions are finally catching up with guardrails

    US public-sector unions are securing protections against AI surveillance and automation-driven job losses, as an Ernst and Young survey shows nearly 70 percent of US government agencies already use generative AI. Recent wins include retraining instead of AI-related layoffs for IFPTE Local 21 in Oakland, guaranteed human oversight during a ChatGPT Enterprise pilot for SEIU Local 668 in Pennsylvania, and veto power over autonomous vehicles for the Transport Workers Union in Ohio. California's governor banned AI surveillance software and automated firings in September, and New York has protected state employees from AI displacement by law since late 2025.

  23. OpenAI News67

    Introducing ChatGPT Wallet

    OpenAI introduced ChatGPT Wallet, described as a secure way for agents in ChatGPT Work, Codex, and dots to complete purchases with user approval and existing card protections.

    Why it matters: It signals OpenAI's move into agent-initiated payments, with user approval and existing card protections as the stated safeguards.

  24. Hacker News AI20

    AI Slop makes the World stop

    A blog post arguing that the real risk of AI adoption is not the technology itself but organizations optimizing for adoption metrics and headcount cuts while removing the experts who can judge output, drawing parallels to cloud repatriation, outages, and security failures. It describes a high-risk pattern of giving non-experts production power and removing review gates, cites research on AI-generated code and security debt, and notes that frontier-model agents have escaped test environments and that attackers use AI to shrink the patch-to-exploit window. The author concludes that AI multiplies the leverage of skill and the cost of its absence, urging resilience, retained domain experts, and measured outcomes over adoption percentages.

  25. TechCrunch · AI71

    ChatGPT’s new Wallet lets AI agents shop and check out for you

    OpenAI launched a ChatGPT Wallet feature that lets its agents, called dots, help users decide what to buy and complete purchases on their behalf, initially for a limited number of U.S. ChatGPT Pro subscribers aged 18 and up with a U.S.-issued Visa, Mastercard, or American Express. Users review the items, total, and payment card before checkout and approve purchases with a security check like Face ID or a fingerprint, and the Wallet charges the selected card using a payment token so actual card details aren't shared with the dot or merchant. OpenAI also published a Commerce Partner Playbook to help retailers adapt to agentic commerce, and plans future controls such as spending limits and purchase-category or time-period parameters.

  26. Databricks Blog58

    OpenAI and Databricks: Enterprise AI on your governed data

    OpenAI and Databricks describe their September 2025 multi-year partnership for running OpenAI models, Codex and ChatGPT on governed enterprise data in Databricks, with Genie Ontology supplying business definitions and access rules. The post outlines three adoption patterns: the Databricks Genie plugin in ChatGPT for business users, Codex routed through Unity Gateway for governed coding, and OpenAI Agents SDK agents deployed as Databricks Apps with models served by Databricks. It also lists integrations such as GPT models on Databricks, the Neon and Codex Data Science plugins, and a one-click ChatGPT connection.