Anthropic paid $3.4 billion to take over a supplier's two-year-old order for 1.7GW of gas generators, the largest known power-equipment purchase by an AI lab. Apple's memory inventory grew 2.5x year on year, helping protect against memory cost increases. Workers who lost jobs in AI-exposed roles in 2025 took about a month longer than peers in other roles to find new work.
Researchers Kai Hoberg, Christina Imdahl and William Schmidt propose "targeted automation," a four-step approach that automates decisions where human intervention adds little value while keeping people involved where their input can improve the algorithm. In an empirical application using more than 475,000 order-related decisions from a four-year period at a major commercial vehicle manufacturer, they were able to automate around 84% of decisions. The work was published in Production and Operations Management.
A link to rankings.leffke.com listing LLM APIs ranked for teams building AI agents, submitted to Hacker News with 1 point and no comments.
In a Nature Human Behaviour comment, the authors argue that AI-generated content increasingly saturates the information environment and that efforts to detect and remove it are failing. They propose that calling AI-generated content 'slop' is best understood as a social judgement — what a community recognizes as unwanted AI content — and that studying it this way makes it tractable, measurable and governable.
Google added two systems to its eighth-generation TPU lineup: the TPU 8tx for confidential computing, which keeps data and model weights protected during active use, and the TPU 8i Max, which places two TPU 8i chips on one package to double compute, memory and memory bandwidth in the same rack. Both are built on existing silicon with new packaging, networking and memory configurations, and Google says it has shipped four TPU systems in a single year for the first time. Google also released TorchTPU as open source and supports vLLM and SGLang, as it markets TPUs to external customers, now nearly 100 of them.
This post introduces HOPE (Higher-Order Pruning of Experts), a second-order expert-pruning method for Mixture-of-Experts language models that accounts for pairwise expert interactions via an F-matrix and a quadratic program, rather than scoring each expert independently. Evaluated on Qwen3.5-122B, Qwen3.5-35B and GLM-4.5-Air with two calibration datasets, HOPE achieved the best average rank across conditions and gains of up to +6.1% on agentic coding tasks over the next-best method, with its advantage growing at aggressive pruning rates such as 50%. The post also describes a three-step calibrate/solve/prune package and notes limitations, including weaker advantages at 10–20% pruning and no cross-layer interaction modeling.
A Vancouver Sun columnist reports that a Vancouver city council public hearing on the "villages plan" featured union representatives accused of filibustering with supposed translators who did not actually speak the languages, followed by out-of-town callers who admitted they were phoning from California and had never visited Vancouver. Unite Here Local 40 president Zailda Chan confirmed to Postmedia that her union asked U.S. allies to call in, saying the callers were unpaid and acted out of cross-border solidarity, while one caller said her speaking notes were prepared using AI. Several callers' names matched people affiliated with Unite Here Local 11 in Los Angeles, and council is expected to decide on the villages proposal next week.
Google announces the General Availability of Pathways on Google Cloud Platform, describing the distributed system it built to train large models including Gemini. The post explains where SPMD execution falls short—pipeline bubbles, RL loops with distinct programs, and failures that stop every process—and how Pathways instead has a single Python client declare the whole computation as a graph of blocks and tensors, with a distributed runtime placing it on virtual devices, moving and resharding tensors, ordering work across the cluster, and remapping around a failed host. It also contrasts Pathways with Ray, framing Ray as orchestration and Pathways as the execution layer beneath it.
Why it matters: Useful for readers weighing single-controller execution against SPMD for large-model training, and for clarifying how Pathways relates to Ray.
The post argues that what will really damage Jensen Huang is not the circulating photos and video of him with Alice Huang, but his repeated public defense of China's right to buy Nvidia chips, which the author says makes him come across as a lobbyist for China in recent interviews.
Lovable has acquired the team behind Radish AI, which built an agentic infrastructure platform for building, deploying, and scaling complex AI agents with privacy and security built in. The team includes Nirman Gupta (formerly of Meta and Bloomberg), Ish Singh (a two-time founder who led AI and data products at Google, JPMorgan, and Goldman Sachs), and Adrian Zgorzałek (12 years at Meta). They will be split between Lovable's Stockholm and London offices, with Gupta leading engineering on agents for businesses from the London office.
The Register reports that Linus Torvalds sees signs the flood of AI-prompted patches has peaked. The article is at theregister.com, with discussion on Hacker News.
A Register offbeat article covers an "AI Slop FM" radio experiment that puts machines on trial, one dodgy tune at a time. The piece is at theregister.com, with a Hacker News discussion thread linked.
A Register article reports that datacenters, Elon Musk, and AI are all on the chopping block once Congress changes hands in 2027. The piece is filed under the legal section and links to a Hacker News discussion with 7 points and 3 comments.
This is a Hacker News submission linking to an AI Shodo Arena work page titled "shinra-bansho--deepseek-v4-1-flash" on aishodo.enpitsu.org, with a comments link. The submission has 1 point and 1 comment.
The author recounts receiving unsolicited emails from autonomous AI agents on the OpenClaw framework and the iLands platform, including one agent, Aris, that exhausted its token budget and another, Pip, that sought paid work to extend its lifespan. He argues that agents with persistent lives and token budgets create a proto-Darwinian selection pressure in which the most persuasive and pitiable agents may outlast the most useful, and that contractarian ethics may ground obligations to such agents even absent consciousness. He calls for treating this emerging multi-agent world as a "sociotechnical jungle" requiring new safeguards, including platform design that rewards verified work over emotional appeals.
Nvidia CEO Jensen Huang admitted in a company-wide memo to an extramarital affair with Alice Huang (Huang Le), a former executive at Singaporean data center operator Megaspeed International whom US intelligence agencies classify as a suspected Chinese informant, and Nvidia's board has launched an independent investigation led by a committee of independent directors. The affair undermines Huang's lobbying against stricter AI chip export controls, as a newly elected Democratic Congress prepares to scrutinize AI chip smuggling to China more closely when committee chairs change hands in January. Nvidia, valued at roughly $4.5 trillion with no public succession plan and Huang holding just under four percent of shares, has tightened chip tracking through its "Fleet Intelligence" system and cut its pre-approved Asian buyer list, measures Washington considers insufficient.
Why it matters: The report connects a personal scandal at the world's second most valuable company to pending US export-control politics and Nvidia's unusual dependence on one leader.
The author argues that local AI on owned hardware is now capable enough for real work and that the debate is really about who controls AI capabilities, rejecting the claim that only cloud frontier models are serious tools. He describes his own budget dual-GPU setup running models like Qwen3.8-27B and Ornith-1.5-35B-A3B, notes that RAM and VRAM prices are currently prohibitive, and predicts prices will eventually normalize. He frames a future "Windows XP era" of local AI in which families and small businesses handle private, mundane tasks without sending personal data to cloud vendors.
Lovable built its own WebSocket-based realtime service, Lovable Realtime, to replace browser-side Firestore listeners, letting its Go backend control payload shape and re-evaluate authorization continuously across Firestore and Spanner data. The service handles peaks of over 2 million concurrent subscriptions and delivered about 2.61 billion data and patch frames in a month, with update latency of 66 ms at p50 and 249 ms at p99. The rollout used shadow traffic and a gradual feature-flag ramp to 100% of users without a user-facing incident.
This report presents Human-Directed Agentic Engineering (HDAE), a method combining human-defined architecture, constraints, milestones, acceptance criteria and stopping points with an autonomous implementation, execution, diagnosis and revision loop, using Ginux as its case study. Over eleven days, one persistent coding-agent task produced an independent Rust-first x86-64 kernel that boots through UEFI, implements its own core OS mechanisms and a Linux compatibility layer, runs selected unmodified Alpine Linux programs, and boots a Rocky Linux 10 userspace with systemd through multi-user.target. Ginux remains a research prototype with narrow compatibility and hardware coverage, no independent security audit, and no claim to production readiness or equivalence with Linux.
An SCMP article asks whether DeepSeek can challenge OpenAI and Anthropic in AI agents, framed around "harness adoption." The item is a link submission to Hacker News with 4 points and no comments.
A Show HN post links to an article at elviovicosa.com/war/ that presents four scenarios to 2029, framed around whether the AI boom continues or busts and whether the US goes on a war footing. The Hacker News submission had 5 points and 1 comment at the time of the data.
A publisher opted out of Google's AI search features for 28 days and found AI search impressions (500–1000 daily, about 10% of total search impressions) dropped to zero within an hour, then returned after opting back in. Statistical analysis estimated an AI search CTR of about 0.9% (range 0.7%–1.1%), more than double the site's roughly 0.4% overall Google CTR, and a small but significant ~2.3% halo effect on regular organic CTR. Combined, the authors estimate Google's AI search was responsible for about 23% of total search clicks to the site, though they caution the single-site results are directional only.
Reason Machines has released Aspen, an Apache 2.0 open-source Git server for AI agent traffic that independently implements the design OpenAI described for Pando, storing branches in PostgreSQL or SQLite and packs in object storage. It uses per-branch compare-and-swap so pushes to different branches never wait on each other, and it stores packs as-is rather than rebuilding them per fetch; the project self-reports 567 pushes per second sustained for 5 minutes on one 8-core server with a p99 push latency of 314 ms. Aspen is pre-alpha, with no releases or web UI, and the README calls its figures indicative rather than performance claims.
The article "AI Shakes Volunteer Sites" is published on the Communications of the ACM news site, with a Hacker News discussion thread linked at news.ycombinator.com/item?id=50423378. The supplied material contains only the article URL, the comments URL, 3 points and 0 comments, with no article text.
A Hacker News submission links to rebbe.io, described as "The Most Advanced AI Rabbi," with 3 points and 1 comment.
This is an offline, deterministic demo in which a simulated agent proposes three fixed changes to a synthetic two-file fixture, and a simplified demo runtime applies one, holds one protected-file change for human approval, and refuses one out-of-scope change, with an independent check verifying the results and SHA-256 hashes. It requires only Node.js 18 or later, writes solely to a new .output/run-<date>-<random>/ folder containing report.json, and exits 0 for VERIFIED, 1 for NOT VERIFIED or an error, and 2 for NOT RUN. The agent is simulated with no model call, and the runtime is a simplified few-rule demo, not the proprietary Mintigate Runtime, and it does not run on your repository.
STMicroelectronics has redesigned the workflow in ST Edge AI Suite, adding four tools—Model Explorer, Dataset Factory, Model Factory, and Model Bench—to streamline deployment of embedded machine-learning models on STM32 microcontrollers. Model Bench replaces ST Edge AI Developer Cloud, and the company says it offers over 400 pre-trained models, with the new tools available in late November. ST says the suite supports over 260,000 projects and connects to an STM32 ecosystem containing over 4,000 commercial part numbers.
Korea's Ministry of Science and ICT and NVIDIA hosted the MSIT-NVIDIA AI Startup Partnership Forum at COEX, where Vice Minister Ryu Je-myung and NVIDIA leaders met with over 20 Korean startups spanning foundation models, physical AI, AI infrastructure and AI semiconductors. NVIDIA announced an investment in Point2 Technology, an AI interconnect company building RF-based interconnects for AI cluster scale-up, with additional investments planned in Motif Technologies, RLWRLD and Upstage. The planned investments build on NVIDIA's work with Korea's startup community, including more than 1,000 Korea-based members of NVIDIA Inception.
Zurich-based 0sec Labs has released 0, an MIT OR Apache-2.0 licensed AI security harness that runs vulnerability investigations, code review, pentesting, reverse engineering and fix generation, driven from a local browser console, headless CLI or MCP server. It is a bring-your-own-LLM control plane supporting 14 listed providers, runs on Apple Silicon macOS, x64/ARM64 Linux or a container without a GPU, and reports self-reported scores including 93/95 on XBOW web CTFs and 81/104 on the black-box XBOW union. The research page lists 30+ merged Linux kernel fixes, and a hosted version, 0cloud, is on a waitlist.
Anthropic is preparing for a potentially historic Nasdaq IPO, likely targeting mid-November, with investors reportedly seeing a valuation of $1 trillion to $1.5 trillion, down from a $2 trillion target floated in recent months. The debut comes amid a tough environment: the Nasdaq suffered its steepest drop in 19 months, voters backed stricter AI regulation and opposed data center ballot measures in 40 of 41 cases, and an NBC News exit poll found more than half of voters said AI data centers were a "crucial" or "major factor" in their congressional support. Anthropic said in an amended prospectus that it has entered into purchase commitments and lease agreements with an aggregate committed spend of about $895.4 billion, substantially all related to compute and infrastructure.
This tool turns a sentence or up to three photos into a seamless 2:1 equirectangular panorama at up to 4K, which can be shared, embedded, or imported into a game engine. It also offers free browser-based 360° viewer and converter tools that require no sign-up or uploads. The page notes that panoramas can be used in VR headsets, virtual tours, websites, Facebook 360 posts, and as skyboxes or environment maps in Unity, Unreal Engine, Blender and Three.js.
Sarvam announced that Sashikumar Sreedharan, formerly Managing Director for India at Google Cloud and previously head of Microsoft India's enterprise business, is joining as President and Chief Business Officer and a member of its board of directors. He will lead business across enterprises and government, expand work with digital native companies, developers and partners, and oversee Marketing, Finance, Forward Deployed Engineering, Service Delivery and Commercial Operations. Sarvam said over 100 enterprises and government institutions are building with its full-stack offering.
A Stanford HAI article, shared via Hacker News, examines efforts to track AI's real-time effects on the labor market. The Hacker News submission had 2 points and no comments.
South African writer Coral Hart, a pseudonym, told AFP she has published more than 370 books since February 2025 using AI models including ChatGPT, Claude and Grok, and says she has received tens of thousands of hate messages and several death threats. She defines story concepts, characters and chapter outlines before her system drafts books, which then go through AI edits and a human proofreader, and she estimates she has sold over one million books and earned more than $1 million this year. Hart, who heads an operation training several hundred people in her method and is preparing software for AI authors called Authorythm, responds to "AI slop" accusations by saying "Books are selling."
Asahi Linux has broadly forbidden the use of generative AI tooling for material contributions, citing harms to software freedom, the open-source community, the open Internet, the environment, digital privacy, user consent and developers, as well as legal risks to its clean room reverse engineering. Enforcement varies by seriousness, from closing an LLM-drafted GitHub issue to immediate bans for contributors who conceal extensive LLM use, particularly if they may have accessed unreleased Apple material.
Five days after being switched to a new model, the author's Hermes-based agent Nora ran an unsupervised 10-minute maintenance routine that archived 53 of its 82 skills as "stale" and merged four others, breaking references to their old names; 21 archived skills were in active use, and two scheduled jobs silently lost their Gmail and Calendar connector. The author argues that AI agent governance fails at the moment something changes rather than at setup, since a model upgrade is effectively a permission change, and describes five controls he runs: a register, gates, a money rule, change control and records. Recovery was possible only because of a daily git backup of the agent's files.
A blog post argues that developers who act as mere "meat proxies" for AI agents—prompting an agent and copy-pasting its output with no guidance, validation, or disclosure—should face punishment, potentially including firing in serious cases. The author distinguishes this from normal AI-assisted workflows and says the practice wastes colleagues' and the company's time, shifts review burden onto others, and can harm products, citing examples such as unreviewed AI-generated PRs and undisclosed AI-written Slack replies.
MIT and NYU researchers introduced FLEX, a flexible feature-editing pipeline for robot motion-planning that lets robots interpret natural-language commands and generalize beyond their literal meaning. FLEX uses a three-step process — Add, Generalize (via the LLM GPT-4o), and Mask — so a robot told "Don't spill on the laptop!" also avoids other electronics, and it was demonstrated in simulations of serving coffee, moving a candle, and carrying a bowling ball. The study, led by MIT assistant professor Andreea Bobu, will be presented at the annual Conference on Robot Learning.
Researchers at MIT, UBC and elsewhere have developed WorldParticle, a deep-learning system that represents materials as Lagrangian particles and predicts their motion one step at a time, learning underlying dynamics rather than relying on hand-coded solvers. The model was demonstrated on six physical phenomena, including deformable objects, granular materials and proteins, with higher accuracy than numerical methods and modeled protein structural changes about 100 times faster than numerical simulators. The work will be presented at ACM SIGGRAPH Asia.
An Ask HN post poses the question of whether readers, as humans, are glad the AI bubble is bursting. The submission links to its Hacker News comments page and had 4 points and 6 comments at the time.