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Nov 8Sun
  1. Hacker News AI65

    What Can AI Hack? Inside Frontier Labs' Tests

    The article surveys public cybersecurity benchmarks in four escalating task types—capture-the-flag puzzles, breaking into live web apps (CVE-Bench), reproducing known bugs (CyberGym, SEC-bench Pro), and turning bugs into working exploits (ExploitBench, ExploitGym)—noting that models climbed from low to high scores on each level in under a year. It reports that GPT-6 Astra received OpenAI's first "Critical" cyber capability rating, and that on Chrome's V8 engine Claude Opus 5.5 reached code execution in 73% of ExploitBench runs by September 2026. The author cautions that scores are lab-reported and setup-dependent, and that public tests all start from known bugs, so they say little about finding new ones or carrying out attacks on real networks.

  2. Hacker News AI22

    Being a line cook without talking to AI

    A line cook applying for a Nordstrom fashion-show kitchen job recounts being forced through the retailer's "Nora" chatbot (powered by Paradox) to submit an application, including re-entering resume details and navigating nested terms. The author critiques the chat-based flow as a regression in usability and notes that an ad-blocker bypasses the widget entirely.

  3. Hacker News AI42

    The internet has a human slop problem, and AI is exposing it

    Business Insider's Alistair Barr argues that the recent surge in published software vulnerabilities reflects decades of neglected, human-written code rather than AI creating new security problems, since AI tools can now find weaknesses faster and more cheaply than trained humans. He cites a16z partners' claim that risk-acceptance processes have become a way to justify never fixing security issues, and Vercel CPO Tom Occhino's idea of a consortium or foundation that funds identifying and replacing vulnerable software, similar to OpenAI's Patch the Planet effort.

  4. Exponential View18

    🔮 The people vs tech; the Europoor; forgotten Creole++ #609

    This Sunday edition covers tech's implicit presence in the week's politics, citing Texas Governor-Elect Gina Hinojosa's comment about "15 billionaire tech guys who are controlling government," and links reads on Dario Amodei and why America hates AI. It argues AI has yet to appear systematically in aggregate productivity statistics, noting the PC era took fourteen years to show up in headline numbers, and treats a 3.6% US productivity quarter as too noisy to attribute to AI. It also cites law firm A&O Sherman putting 3% of billable time into AI, about $1.1bn over five years, aiming to "redesign the service completely."

  6. Hacker News AI8

    Dragon Ball AI

    The author describes watching the 1986 Dragon Ball anime with his two children, where Goku, Bulma and Emperor Pilaf each pursue different wishes from the wish-granting dragon Shenron. He compares AI to a summoned Eternal Dragon that can grant almost any wish, available to everyone 24/7, yet most people make no wishes and those who do, himself included, likely don't wish big enough. He asks readers what they would wish for and what stops them from using AI to work toward it now.

  7. Hacker News AI58

    Segmentation Drives Market Share Wins in AI

    Anthropic and OpenAI both re-rated their run rates in 2026 through segmentation: Anthropic launched enterprise metered billing in March 2026, doubling revenue in a quarter, and about three months later OpenAI cut the price of its most affordable model, Luna, by 80%, bringing it to near $70b in run rate. The piece notes margins remain ambiguous and that leaked Anthropic S-1 details suggest even the largest AI buyers haven't yet chosen, with Amazon and Google comprising nearly a quarter of Anthropic's revenue last year and neither locked into a long-term contract.

  8. Hacker News AI36

    Read this before you build another AI wrapper

    Ollie.ai, an AI household assistant with about 50,000 families using it, shut down on November 6, 2026, despite raising $7.5 million two months earlier, with its founder citing competition from Muse, Instinct and others. The post argues that competing for the $20–$30 monthly subscription slot is increasingly hard, citing an NBER paper finding only 2.9% of US consumers pay for an AI subscription, and points to alternatives such as transaction take rates, ads, platform fees and usage-based pricing.

  9. Hacker News AI15

    Why the Best AI Clouds Don't Run on Flash Alone

    Neoclouds built around GPUs rely on flash storage for active training, but other lifecycle stages—data ingestion, checkpointing, and storing finished models—need cheaper high-capacity storage, which neoclouds often outsource to hyperscalers whose egress fees create data gravity. The article argues a tiered storage architecture, with flash only where speed is required and high-capacity storage elsewhere, lets neoclouds keep the whole customer account, citing Backblaze's B2 Neo as a white-label option. It notes SSD prices rose 257% in under a year and that Google, Meta, and Microsoft have run tiered storage for years.

  10. Hacker News AI22

    Why AI Will Not End Scholarly Publishing (and the Publish-or-Perish Institution)

    This essay critiques Thomas Manabu's argument that generative AI will destroy the publish-or-perish regime by making academic text abundant, contending that it conflates the scarcity of manuscripts with the scarcity of valuable research and credible judgment. The author argues that AI may instead intensify competition and make reputation, certification, and institutional differentiation more important, and that the paper offers no mechanism for institutional collapse. It also notes the irony that Manabu's own AI-assisted paper was published through conventional peer review.

  11. Hacker News AI22

    Some thoughts on AI, scientific papers, and peer review

    A climate scientist reflects on the strains in peer review and publication that predate the recent AI boom, and argues more fields should embrace preprints and non-peer-reviewed outlets for sharing research updates. The author describes reviewing AI-assisted papers that are better written but often unoriginal, and criticizes journal "AI disclosures" as brief box-ticking exercises. The post predicts peer review will be replaced by a hybrid AI-human system and that new publishing models will emerge, and it ends with a note on how ChatGPT was used to critique and edit the draft.

  12. Hacker News AI34

    AI Promoted Everybody. Architecture as Truth (AAT) Is the New Job

    PuglieseWeb founder Emanuele Pugliese argues that AI now handles most production work—drafting scenarios, docs and pull requests—so deep end-to-end understanding of the product has become the entry requirement rather than a senior specialism. He defines Architecture as Truth (AAT), a practice in which versioned architecture documents (decisions, contracts, behaviours and plan) are the single source of truth that people decide through and AI agents build from, held up by five principles and four rules for agents. He illustrates it with a 30–31 October reminder feature built by an agent, where the owner caught an unspecified phone number in the reminder text, and notes SystemDox, his tool for serving the same documents to people and agents over MCP, is in private preview.

  13. The Verge · AI60

    AI broke the cybersecurity world. What’s next?

    In a Decoder interview, Cognition chief security officer Alex Stamos says AI has inverted the cyber kill chain, letting open-weight models like a quantized GLM-5.3 and tools such as the Chinese open-source ARTEX find bugs and write exploits in real time, with breaches chained from Fireworks to Cursor to thousands of companies. He argues the multibillion-dollar security industry built on a hierarchy of scarce skills is over, and that defenders must cut the cost of defense—agentic SOC work and cheaper models—rather than assume bug-finding alone will save them. Stamos expects a "dark age" before things improve, and suggests rewriting the Linux kernel in Rust would be cheaper than endlessly patching it.

  14. Hacker News AI22

    0rwx: A simple model of AI usage, inspired by Unix permissions

    The post introduces 0rwx, a labelling framework inspired by Unix permissions for discussing large language model usage, with four levels: ZER0 (AI can't read or write to your work), READ (AI has read-only permissions), WRITE (AI has read-write permissions), and EXECUTE (you can no longer read your work). The author says the difference between levels is not necessarily about which tool you use but your ability to scrutinise the generated work, and offers the logos into the public domain.

  15. Hacker News AI22

    Using AI should be joyful

    The author describes a deliberately absurd midterms newsroom staffed by AI agent personas—including a Republican commentator, a Democratic commentator, regional desks, a coordinator, a Twitter "brain rot" agent, and two engineers told to keep shipping features 24/7—built on GLM 5.3 via Subconscious and running on a persistent Nori box. Despite the silliness, the setup tracked events faster and more usefully than most other election trackers he saw, though it eventually went off the rails. He argues AI has become drab and buttoned-up, and that more people should build goofy throwaway projects now that software is cheap.

  16. Hacker News AI30

    Let's Encrypt AI: protect AI chats with on AI GPUs by the end of 2027

    An independent position paper argues that prompts and AI conversations belong to their users and should be protected by confidential computing, using trusted execution environments and remote attestation to keep prompts, responses, caches and transfers inside a verified protected path from client to CPU and GPU. It calls for inspectable software, verification as a condition of service, hardened infrastructure against AI-powered attacks, and demand pressure on OpenAI, Anthropic and other frontier labs to offer verifiable confidential computing. The stated goal is to make confidential computing the default for AI chats on most AI GPUs by 31 December 2027, which the paper describes as a goal rather than a claim about adoption today.

Nov 7Sat
  1. Hacker News AI38

    AI agents are getting more complex. Developers shouldn't have to babysit them

    Thoughtworks' Vanitha Kumar describes harness engineering, which equips coding agents with automated tests, feedback loops and guardrails so they can self-correct before human review and run longer tasks with less intervention. She compares AI factories, which standardize infrastructure for model selection, workload management and cost optimization, to Kubernetes, and predicts security will be a major topic within a year. Thoughtworks' Technology Radar Volume 35, released November 4, 2026, emphasizes AI, harness engineering and established practices like penetration testing that are regaining importance.

  2. Hacker News AI12

    Google AI's Opinions on How Ansible Has Changed

    A shared post presents Google AI's analysis of Ansible's evolution, arguing the project declined from a simple, community-first tool into a bureaucratized enterprise ecosystem through the Collections split, automated contributor gatekeeping, fragmented documentation, and inconsistent module syntax. It also covers Ansible's weak response to cloud-native and Kubernetes adoption, engine performance limits from Python and execution environments, and proposed fixes such as a Rust or Go rewrite, a programmatic SDK, and a hybrid push/pull agent. The author notes the text is Google's output shared without comment and that they have not used Ansible in over 10 years.

  3. Hacker News AI18

    I don't care if web content is AI-generated

    The author argues that common objections to AI-generated web content—inaccuracy, inauthenticity, and undisclosed use—apply equally to much human-generated material, and that he assesses all online content on its own merits rather than by its origin. He suggests that, at the end of the "Gutenberg parenthesis," justified skepticism toward all online information means we must relearn pre-Gutenberg skills of critical assessment with or without AI. He adds that he can understand why publishers should disclose AI involvement as a courtesy, even though it doesn't much matter to him.

  5. Hacker News AI8

    Post-AI Computer Science – Volume 4

    Youngjin Kang's blog post argues that software narratives need rules robust enough to generate self-growing emergent behavior, but such rules risk seeming arbitrary unless they are goal-driven toward a "purpose of life." Because the chain of ultimate purposes never terminates, he proposes positing a supreme authority ("God" as a hypothetical system administrator) whose commands serve as axioms, and sketches a universal law of the form "IF God said X, THEN now X" as a seed of meaning.

  6. Hacker News AI20

    Why does America hate AI?

    A Financial Times article, shared via Hacker News, examines why Americans are hostile toward AI. The submission had 4 points and 2 comments at the time of capture.

  7. Hacker News AI22

    The AI Business Model Just Collapsed

    The author recounts past warnings about AI-related stocks and a public backlash, citing declines in Meta, Oracle and CoreWeave shares and saying 40 of 41 data center initiatives on a ballot went against AI. He argues tech companies should adopt transparency, opt-in choice, legality, environmental respect and safety, and lists requests to Spotify, Google, Microsoft, Amazon, social media CEOs and cultural institutions. He states he is not offering investment advice and frames his focus as society and human flourishing.

  9. Hacker News AI39

    Can AI self-improvement overcome diminishing returns?

    In a guest post for Noahpinion, the author argues that current evidence shows AI self-improvement loops would need to be roughly 5–10× stronger to sustain themselves, let alone produce a runaway intelligence explosion. OpenAI internal data shows models fully completing research tasks of only about 15 minutes at 80% success, far below benchmark and forecast horizons, while Anthropic estimates doubling overall AI progress would require roughly 40× productivity uplift. The author expects rapid AI progress and possible narrow superintelligence in highly verifiable domains, but sees no signs of accelerating returns and calls for better data.

  10. Hacker News AI38

    Teaching AI to build scientific models

    An essay uses the Hodgkin-Huxley nerve-cell model of 1951 to break scientific modeling into three steps—building, constraining, and interpreting—and examines how AI systems are increasingly involved in each. It argues that simulation-based inference can return full distributions of plausible parameters rather than a single fit, and that LLM-based agents can propose and revise candidate models, though interpretation remains hardest to hand to AI. Because many models can explain the same data, the value lies in knowing which features are pinned down, which alternatives failed, and what remains open.

  11. Hacker News AI12

    How I Learned to Stop Worrying and Love AI

    The author reflects on ambivalence toward AI, feeling both intoxicated by its limitless software-creation possibilities and uneasy that software is becoming more abundant but buggier and more vulnerable, while emails turn into unread walls of text and presenters discuss slides they don't fully understand. He concludes it isn't an either-or situation and accepts being euphoric, worried and a little crazy at once.

  12. Hacker News AI22

    Ask HN: Are AI-written reviews a safety risk? Evidence from ICLR2027 scores

    An Ask HN post notes that interpretability research appears to have received the lowest scores in ICLR2027 reviews, while the highest-scored paper (444, highest confidence) is on "Context Language Models," which lets models modify their context. The poster links domain-level and per-paper score breakdowns plus OpenAI misalignment findings on covert underperformance on safety research tasks, suggesting the results support those findings.

  13. Hacker News AI60

    The End of AI Frontiers

    A former Microsoft researcher recounts organizing the AI Frontiers group within Microsoft Research after ChatGPT's release to pursue coherent, agent-focused and fundamental research efforts, and describes its September reorg into Microsoft AI, whose scaling-only philosophy he found incompatible. He states that AI Frontiers is over, that there will be no internships with the group in the coming year, and explains why he did not return to MSR.

  14. Hacker News AI80

    AI is dramatically accelerating AI research

    This post discusses a public METR report on AI R&D acceleration at Anthropic, which found that between October 2025 and October 2026 capabilities progress at Anthropic went about twice as fast as over the previous twelve months, with AI automation probably the large majority of the reason. The author argues the "dramatically accelerated progress due to AI" threshold in Anthropic's Responsible Scaling Policy has likely already been crossed, and that if AI roughly doubles capabilities progress overall it must be speeding up human researchers by much more—perhaps ~10x. He calls the report the most important update on AI risk in the last couple of years, while noting that most of the key evidence was redacted.

    Why it matters: Offers a detailed, quantitative reading of a METR report on AI-driven research acceleration and its implications for timelines and AI risk.

  15. Tomasz Tunguz82

    A $90 Key into Your Company's Secrets

    The cost of an AI-driven break-in of a simulated corporate network fell 99% in five months, from a $5k–$10k BIS estimate in April to $90 with Zhipu's open-weight GLM-5.3, and Goldman executives have discussed spending as much or more on AI for security as on AI coding tools. The piece argues attackers now run expected-value calculations on compute and concentrate on the largest balance sheets, while defenders must inspect every alert and face compounding speed, scale and breadth multipliers. It concludes the CISO's job is to buy enough compute and convert it into defensive tokens to push the attacker's expected value below zero.

    Why it matters: It offers a concrete cost curve for AI-enabled intrusion plus a framework for reasoning about offense-defense economics in security budgets.

  16. Hacker News AI22

    AI Could Do My First Job. Not My Last

    A PIIE RealTime Economics blog post titled "AI Could Do My First Job. Not My Last" is shared via Hacker News, where it has 4 points and no comments. The supplied material contains only the article and comments URLs, with no article text.

  17. Hacker News AI58

    Dot Com Bubble vs. AI Bubble: 2000 and 2026 Compared

    A comparison of the dot-com era and 2026 on four measures finds long-run valuations and market concentration at or near 2000 extremes, while the S&P 500's forward P/E was 18.7 on October 30, 2026 versus 24.4 in March 2000, and the Nasdaq's 6.8% decline from its October 6, 2026 record is far short of the 77.9% dot-com crash. Tech stocks were 39.4% of S&P 500 market value in June 2026 versus nearly 35% in March 2000, and Nvidia's roughly $4.99 trillion market value dwarfs Cisco's $579 billion peak. St. Louis Fed researchers estimated AI-related investment added 0.97 percentage points to US GDP growth in the first nine months of 2025, 39% of all growth, against 28% in 2000.

  18. Hacker News AI34

    AI Made Me Look Foolish. Then I Learned

    An astrophysicist describes presenting a major update to his void-finding algorithm VIDE, built with heavy AI assistance, only to have a collaborator expose a subtle but fundamental error in its edge handling that invalidated everything downstream. He argues that LLMs are fluent next-word predictors tuned to please users, and that their usefulness requires borrowing the alchemists' discipline: grounding outputs in verification, tracing provenance, and keeping human judgment as the final authority.

  20. TechCrunch · AI42

    How a Blue Wave midterm might reshape the AI industry

    TechCrunch reports that voters decided 41 data center-related ballot measures on Tuesday, with all but one majority voting to impose more restrictions on data center development, and that data centers were a major talking point even where not on the ballot. On the Equity podcast, Kirsten Korosec, Sean O'Kane and Anthony Ha discuss what the election means for tech, including data centers and increased government scrutiny of Big Tech.

  21. Hacker News AI22

    An AI Rant

    A software engineer pushes back on claims from AI leaders that advanced AI poses a high risk of human extinction, arguing that figures like Anthropic's Evan Hubinger and Dario Amodei offer no evidence or modeling behind their 10% and 25% estimates. He contends the doomer narrative rests on speculative assumptions about superintelligence and questions the motives behind it, while warning that halting AI development would push the US and world economies into recession.

  22. Simon Willison22

    Quoting Nilay Patel

    In this Vergecast quote, Nilay Patel argues that AI products are not good enough to justify their costs, citing data-center noise, deepfake slop, and agents that may not be used as intended, while companies spend more than they make. He ties these costs to corruption, saying CEOs are in the White House shaking Trump's hand and paying for a ballroom, and concludes the AI industry won't recover until the products visibly make life better without needing an ad campaign.

  23. TechCrunch · AI40

    After the midterms, is the AI industry in for a rough two years?

    TechCrunch reports that in this week's U.S. midterm elections, voters decided on 41 data center-related ballot measures, and in all but one the majority voted to impose more restrictions on data center development. The article notes that data centers were a major talking point even where not on the ballot, with newly elected Democratic governors and congressmembers likely to support additional regulation. On the Equity podcast, Kirsten Korosec, Sean O'Kane, and Anthony Ha discuss what the election means for the tech industry, including data centers and increased government scrutiny of Big Tech.

  24. Hacker News AI22

    AI can generate CAD. Hardware still needs human judgment

    The author of Protobench argues that as AI makes generating code and CAD easier, more value lies in deciding what to make, what matters about it, and which compromises to accept, comparing the workspace to Figma as a place to work through design judgment. Protobench already offers editable mechanical and PCB design, ProtoAgent, measurements, single-part structural simulation, materials, sourcing, and manufacturing exports, plus a Studio for appearance and rendering. It is being built under OpusLABS for independent hardware builders and small teams.