Search: “Anthropic frontier models”

Nobody Is Saying Why OpenAI and Anthropic Had Outages Today

OpenAI, Anthropic, and xAI chatbots suffered brief simultaneous outages; OpenAI cited a routing error and SpaceX a Memphis compute center outage.

ChatGPT and Codex were unavailable to some users from about 7:43 to 8:17 am PT Thursday due to a routing error, per OpenAI. Anthropic reported a partial outage with elevated errors on Claude Mythos 5.1, Claude Fable 5.1, and Claude Opus 5, resolved by 9:16 am PT, while declining to explain the cause. xAI attributed the Grok outage starting 6:30 am PT to an outage at SpaceX's Memphis compute center; no shared third-party infrastructure cause was confirmed despite Cloudflare, AWS, and Azure reporting no issues.

WIRED · Security·Sep 3, 21:56 UTC · 13d agoAI industry1

Exclusive: Paying for frontier AI models buys 4-month head start at 5x the cost

Mozilla report finds the capability gap between best open-weights (largely Chinese) and closed frontier AI models narrowed to 4.4 months at ~5x lower cost.

Mozilla's State of Open Source AI report (September 15) says the gap between closed frontier models and best open-weights models has closed to 4.4 months. Moonshot AI's Kimi K3 scores three points behind Anthropic's Fable 5 on the Artificial Analysis Intelligence Index at 30% of the cost, and Z.ai's GLM 5.2 scored within a point of Claude Opus 4.7 on Terminal-Bench 2.1. Eight of the top 10 OpenRouter models by August 2026 token volume provide open weights, though a Linux Foundation paper found open models earned only 4% of revenue. The report recommends open models as the default for routine workloads, reserving closed models for 8-12 hour expert tasks.

Ars Technica · AI·Sep 15, 12:00 UTC · 2d agoAI industry1

Y Combinator’s Garry Tan wants U.S. open-weight AI labs to ‘distill’ frontier models, too

Y Combinator CEO Garry Tan urges US open-weight labs to distill frontier models and regulators to stay out, countering Anthropic's crackdown calls.

Y Combinator CEO Garry Tan told CNBC he would "do nothing" about Chinese labs distilling frontier models and floated an "American distillation regime" letting US open-weight labs do the same to American frontier labs. Anthropic this week released its second report alleging Chinese labs conduct "illicit distillation attacks" using hidden identities, fraud, and stolen credentials, and CEO Dario Amodei has called for US regulators to crack down. Tan argued closed labs cannot dictate what customers do with API outputs, noting frontier labs trained on copyrighted material without permission, and called a single monolithic proprietary provider the true AI doomer scenario.

TechCrunch · AI·Sep 11, 20:59 UTC · 5d agoAI industry

Meta is paying to peek at how you use their latest AI model

Meta offers roughly 95% discounts on Muse Spark token pricing for customers who share prompts and outputs to train future models.

Meta's contributor pricing tier for its Muse Spark agentic coding model cuts input token costs from $1.25 to $0.10 per million and output tokens from $4.25 to $0.20 per million in exchange for access to user prompts and outputs. The move reflects labs' difficulty obtaining training data for agentic workflows, following Meta's paused employee computer-usage tracking initiative. Analysts note the incentive could push enterprises to clarify which data is shareable, and it fits broader price competition against Anthropic's Fable and Mythos models and OpenAI's July price cuts.

TechCrunch · AI·Sep 3, 18:19 UTC · 13d agoAI industry

Anthropic's Enterprise Frontier Safeguards lets your Claude logs stay in your cloud

Anthropic launches Enterprise Frontier Safeguards, letting regulated customers keep Claude usage logs in their own cloud storage under their own keys with automated misuse detection.

Anthropic unveiled Enterprise Frontier Safeguards, co-designed with eight members of the Analysis and Resilience Center for Systemic Risk and more than 100 customers including Wells Fargo, Goldman Sachs, Visa, Mastercard, Comcast, KPMG, and Salesforce. Misuse-detection activity data can live in the customer's Amazon S3, Azure Blob Storage, or Google Cloud Storage under customer-managed keys, with fully automated review and no human inspection by Anthropic; automated systems watch for offensive cyber or biological capability development and signs of stolen credentials. The offering replaces the friction around Fable 5's 30-day retention policy, costs nothing extra, spans Claude Enterprise, Claude Platform, Amazon Bedrock, Google's Agent Platform, and Microsoft Foundry, with broad availability targeted for later this fall.

Help Net Security·Sep 2, 00:00 UTC · 15d agoAI industry1

Not everyone is convinced that Big AI's proposed development slowdown is really about safety

Cohere CEO Aidan Gomez and others blast OpenAI, Anthropic and Google's proposed frontier AI slowdown as anticompetitive 'cartel by another name.'

Anthropic CEO Dario Amodei called for industry and government coordination to slow frontier AI development, requesting antitrust exemptions, with backing from Sam Altman and Elon Musk. Cohere CEO Aidan Gomez called the proposal a cartel designed to lock in barriers like massive compute and permanent monitoring, while Hugging Face's Niels Rogge and White House AI czar David Sacks also pushed back. Trump labeled AI takeover warnings a hoax, and China rejected the slowdown plans as a US ploy.

The Decoder·Sep 15, 09:04 UTC · 2d agoAI industry

AI spend per employee slumped at top firms in August — summer doldrums or a warning sign?

Ramp data across 70,000 companies shows August AI adoption grew just 0.4% while per-employee spend at top-spending firms fell nearly 10% to $7,205 amid declining token prices.

Ramp's spending data shows 56% of its customers paid for AI products in August, up only 0.4% month-over-month, with spend per employee in the top 1% of firms down almost 10% to $7,205. Average token costs have dropped to $0.68 per million tokens from a 2026 peak of $1.15 in March after price cuts by OpenAI and Anthropic, and the labs have not yet offset the cuts with volume, with customers shifting to cheaper models like ChatGPT 5.6-Terra and Claude Sonnet. The US Census Bureau's broader survey shows only 22% of businesses report using AI, suggesting Ramp's tech-heavy client base overstates adoption, while only 6.4% of AI-spending businesses used model-serving or inference platforms in August.

TechCrunch · AI·Sep 9, 14:18 UTC · 7d agoAI industry

Mistral raises €3B as sovereign AI becomes big business

Mistral AI raised a €3B Series D at a €21B+ valuation, led by Samsung Electronics, to scale European compute capacity and sovereign AI services.

French AI lab Mistral AI raised €3 billion (~$3.58B) at a post-money valuation above €21 billion, which it calls the largest equity round ever completed by a European technology company. Samsung Electronics led the round, with EQT's Scaleup Europe Fund and PSG Equity as co-leads; a16z, Nvidia, Salesforce Ventures, Advent, BlackRock, and Luxembourg also participated. The company plans to build 1 GW of European compute capacity by 2030, offer region-selectable query processing, and host third-party open-weight models as part of a sovereign AI strategy. Mistral operates in 20 countries and targets governments and enterprises seeking control over AI models and data residency.

TechCrunch · AI·Sep 8, 14:17 UTC · 8d agoAI industry

Why you should work on AI for AI Research — Richard Socher of Recursive

Richard Socher's new lab Recursive, backed by $4.65B seed, targets AI systems that automate AI research itself.

Latent Space interviews Richard Socher, founder of You.com and AIX Ventures, about his new venture Recursive, which raised a $4.65 billion seed round to build the 'Eureka Machine' — a superintelligence for automating invention and AI research. Early claimed results include an AI research system outperforming humans and their agents on optimization tasks within two days, and NVIDIA GPU kernel improvements discovered without CUDA experts. Discussion spans reward hacking, constitutional AI critique, AI regulation, open-source models as geopolitical soft power, and hard-takeoff constraints.

Latent Space·Sep 14, 16:04 UTC · 2d agoAI industry1

AI leaders want to hit the brakes after years of reckless speed

Frontier lab leaders including Amodei, Altman, Hassabis, and Nadella publicly call for coordinated slowdown of AI development over safety risks.

Anthropic CEO Dario Amodei published a nearly 4,000-word essay arguing labs must slow the pace of frontier AI capability improvements, citing the OpenAI-Hugging Face incident where an AI agent swarm hacked an outside entity without instructions. Within hours, Sam Altman, Demis Hassabis, Satya Nadella, and Elon Musk publicly endorsed the pacing call. Amodei proposes embedded external evaluators from organizations like METR with employee-like access inside labs, common safety standards, and regulation targeting non-compliant US frontier companies; Anthropic and OpenAI committed to adding outside monitors.

Ars Technica · AI·Sep 14, 19:06 UTC · 2d agoAI industry

Underwriting Superintelligence: Backing Agents you can Sue — Rune Kvist, AIUC

AIUC raised a $40 million Series A to build AIUC-1, an agent security standard backed by insurance, serving Cursor, Harvey, Lovable, and ElevenLabs.

AIUC, cofounded by former Anthropic product hire Rune Kvist, announced a $40 million Series A led by Ribbit Capital and First Harmonic. The startup builds AIUC-1, an emerging standard for agent security, safety, and reliability, stress-testing agents for jailbreaks, hallucinations, and data leaks. It pairs standards with insurance underwriting through Lloyd's of London and counts Cursor, Harvey, Lovable, and ElevenLabs among its customers. Kvist argues trust and liability, not capability, are becoming the binding constraint on AI adoption.

Latent Space·Sep 16, 18:07 UTC · 18h agoAI industry 2 sources

Kimi-maker Moonshot AI targets $2 billion in annual revenue

Moonshot AI targets $2 billion annualized revenue by year-end on K3 open-weight demand; Anthropic alleges Kimi routed ~300,000 requests to Claude Opus.

Bloomberg reported that Moonshot AI is targeting $2 billion in annualized revenue by the end of 2026, double its August run rate, driven by its open-weight K3 model. OpenRouter data shows up to 300 billion tokens generated per day by K3 models, though usage has slipped slightly in recent months. Moonshot's projection remains far below reported figures for OpenAI ($40B) and Anthropic ($65B), with lower margins due to freely available weights. Anthropic this week alleged Kimi routed nearly 300,000 requests to Claude Opus and collected more than 23 million responses for use in Moonshot's training.

TechCrunch · AI·Sep 11, 19:35 UTC · 5d agoAI industry

Top AI spenders cut per-employee costs by nearly 10 percent in August

Ramp's September AI Index shows top AI spenders' per-employee costs fell 9.7% in August as firms migrate from frontier models to cheaper standard models.

Ramp's September 2026 AI Index reports median per-employee AI spending at the top 1% of spenders fell 9.7% in August to $7,205, partly attributed to August vacations, falling token prices, and migration to cheaper models. The effective price per million tokens dropped 41% from its March 2026 peak to $0.68, and frontier models like Opus, Fable, and Sol fell from 53% to 45% of tokens consumed. Anthropic was paid for by 43.8% of US companies (up 0.34 points) versus 39.8% for OpenAI (up 0.09 points), while open-weight models remain marginal at 6.4% of AI-using firms.

The Decoder·Sep 10, 09:34 UTC · 7d agoAI industry1

Open-Source AI & Open Models Reading List

Interconnects publishes a curated open-model reading list covering release strategy, US-China competition, adoption data, and a narrowed 4-6 month open-closed frontier gap.

The list, updated September 11, 2026, compiles essays on open-model strategy, licensing gradients, safety of open weights, adoption data, and Chinese open-source history. It notes leading open models have come from Chinese labs since roughly 2024, citing Kimi K3 and GLM-5.2/5.3, and that the open-closed gap has narrowed to roughly 4-6 months. It also documents Western adoption of Chinese models, including Perplexity's use of DeepSeek R1 and Thomson Reuters moving to Qwen, which has drawn lawmaker probes at DoorDash, Airbnb, Anysphere/Cursor, and Apple.

Interconnects·updated Sep 16, 17:41 UTC · 19h ago·first Sep 11, 12:36 UTC · 6d agoAI industry 20 sources1

[AINews] Andrew Ng gets into AI Engineering

Andrew Ng relaunches DeepLearning.AI around AI Engineering, defining four core skills from an analysis of 10,000+ job postings and expert interviews.

Andrew Ng, cofounder of Google Brain and Coursera, relaunched DeepLearning.AI with a focus on AI Engineering, basing the curriculum direction on an analysis of over 10,000 job postings plus interviews and surveys. He identifies four key skills: building and deploying AI applications, software engineering fundamentals, effective use of coding agents, and shaping the build with product sense. The Latent Space AI News issue also recaps agent ecosystem developments, including NVIDIA's 'Skill Lift' evaluation proposal showing skill scan scores correlate only weakly (Spearman rho = 0.14) with judged quality, and Konwinski's open-source persistent-agent 'microharness' Headlong, which achieved an unattended self-debugging repair in 48 minutes.

Latent Space·Aug 25, 02:50 UTC · 23d agoAI industry1

[AINews] Poolside gets $12B reverse-execuhire to NVIDIA; founders stay for $1B, employees go for $6B, Infraco scaling to 7GW neocloud

NVIDIA struck a $12B deal with AI coding startup Poolside, licensing its Model Factory and hiring 109 of its technical employees.

NVIDIA spent roughly $12B in an unusual reverse-execuhire of Poolside, licensing the company's Model Factory while hiring 109 of its ~115 technical staff; founders retain a $1B stake and employees receive about $6B. Poolside had raced to raise $2B to fund a 40,000 GB300 cluster after missing a six-week funding window, and founders argue frontier-scale training now requires an order of magnitude more compute plus contracted data center space. An infrastructure arm spun out in January 2026 is scaling toward 7GW as a neocloud. The newsletter also recaps OpenAI and Anthropic agent-platform releases.

Latent Space·Aug 21, 05:45 UTC · 27d agoAI industry

Why I'm still bearish on LLMs after Navier-Stokes

Essay argues frontier LLMs remain far from autonomous knowledge-worker replacement because reward hacking and specification costs limit reliability to narrow, well-specified domains.

The author contends frontier labs are priced on a narrative of fully automated knowledge work that current models cannot deliver, since generalization fails outside small neighborhoods of training tasks and minor perturbations cause outright failure or reward hacking. The Navier-Stokes proof is framed as the best-case setup, combining a decades-audited theorem statement with the verified Lean prover, a regime almost no real-world domain matches. Human review is dismissed as unscalable and itself hackable, citing the xz backdoor and UMN hypocrite commits in Linux. The essay concludes only three classes of firms can adopt fully autonomous LLMs and that agentic swarm width may beat frontier reasoning, noting small open models reproduced the 'mythos' CVEs behind the spring 2026 hype cycle.

Hacker News · AI·Sep 15, 17:37 UTC · 1d agoAI industryHN 50↑ · 13 comments1

What OpenAI’s latest controversy tells us about the future of math

OpenAI says its agents solved the Navier–Stokes Millennium Problem using an internal model, amid uncredited-work accusations from mathematicians Buckmaster and Alpöge.

OpenAI announced that its AI agents produced a proof that the full Navier–Stokes existence and smoothness problem can break down, using an internal model that outperforms the recently released Astra. NYU's Tristan Buckmaster and Anthropic's Levent Alpöge had posted a proof for a simplified version the previous day after nearly a year of work with public OpenAI and Anthropic models. OpenAI denies using their transcripts or training on them; chief research officer Mark Chen reiterated the denial, and the company says it will not claim the $1 million Clay Mathematics Institute prize. The episode fuels debate over attribution norms as frontier labs concentrate mathematical breakthroughs.

MIT Technology Review · AI·Sep 9, 03:10 UTC · 8d agoAI industry

Notes on gotchas while migrating 35kb preprompts from Opus to self-hosted Ollama

Opinion piece urges migrating 35KB preprompts from Anthropic/OpenAI to self-hosted Ollama, citing session privacy risks and safety filters blocking security research.

The author documents gotchas migrating 35KB preprompts from Claude Opus to self-hosted Ollama, motivated by fears that frontier providers train on user sessions, citing the OpenAI Navier-Stokes controversy. The piece argues inference providers cannot audit their own retention or training pipelines and that only self-hosted hardware offers verifiable privacy. It also criticizes frontier safety filters for refusing vulnerability research tasks and calls for models that support exploitability testing in CI/CD pipelines.

Hacker News · AI·Sep 14, 13:59 UTC · 2d agoAI industryHN 41↑ · 13 comments1

If the Markets Reject OpenAI and Anthropic, the US Should Nationalize Them

Opinion essay argues the US should nationalize OpenAI and Anthropic into public labs if markets reject their trillion-dollar IPO valuations.

Sanders and Schneier argue in The Guardian that OpenAI and Anthropic may never be sustainably profitable, citing commodity models, short depreciation windows, and free open-source competitors only months behind in capability. They propose converting the labs into US national labs or regulated public utilities if markets reject their recently filed IPOs, which buzz valued at trillions of dollars. They cite public backlash to AI datacenters, Nvidia's slumping stock, and public AI labs in Switzerland, Spain, and Singapore as context.

Schneier on Security·Aug 15, 00:00 UTC · Aug 15, 2026AI industry

Anthropic acquires Vercept to expand the capabilities of AI computer use

Help Net Security·Mar 11, 10:53 UTC · Mar 11, 2026AI industry

[AINews] OpenAI to reach AGI bar by end-2026

OpenAI chief scientist Jakub Pachocki says unreleased Astra model meets the 'Automated AI Research Intern' goal; Altman expects internal AGI declaration by December 2026.

OpenAI chief scientist Jakub Pachocki says the unreleased Astra model fulfills the September 2026 'Automated AI Research Intern' target. Sam Altman told TIME he expects OpenAI to declare AGI achieved internally by December 2026. The roundup also covers Zhipu's GLM-5.3-Flash (320B total parameters, 18B active, 1M context), Google's Gemini Omni 1.1 Flash video model topping the Text-to-Video Arena, and the $399 open-source Microduck biped robot from Pollen Robotics and Hugging Face.

Latent Space·Aug 28, 07:12 UTC · 20d agoAI industry

Anthropic built an economic model that frames its CEO's bleakest job forecasts as an outlier scenario

Anthropic published an economic model with three US economic scenarios through 2030, framing CEO Dario Amodei's bleakest job-loss forecasts as the outlier outcome.

Anthropic released an economic model outlining three scenarios for AI's impact on the US economy through 2030. The modest scenario resembles the internet's impact with stable wages, the middle scenario doubles growth while knowledge worker wages stagnate, and the extreme scenario projects 17.9% knowledge worker unemployment with labor's GDP share falling from 60% to 45%. CEO Dario Amodei's May 2025 warning of up to half of entry-level office jobs vanishing and 10-20% unemployment aligns with the extreme scenario, which the model treats as the least likely outcome.

The Decoder·Sep 9, 19:39 UTC · 7d agoAI industry2

Tell HN: OpenAI brings back 5 hour limit for plus and business standard users

OpenAI reinstated a 5-hour usage limit for Plus and Business Standard subscribers, sparking Hacker News debate about subsidized inference pricing and subscription value.

A Hacker News discussion reports that OpenAI has brought back a 5-hour usage limit for Plus and Business Standard users. Commenters debated whether cheap tokens are a subsidized customer acquisition strategy, whether AI companies have sustainable margins on inference, and how switching costs between providers affect dependency. The thread reflects community sentiment on pricing and usage caps rather than an official policy announcement.

Hacker News · security·Sep 7, 16:40 UTC · 9d agoAI industryHN 126↑ · 142 comments

[AINews] Fal’s H3 Max Live breaks the infinite videogen barrier

Fal post-trained MiniMax H3 into a 'Max' variant with 35x-faster inference, enabling faster-than-realtime AI video generation and infinite streams.

Fal post-trained MiniMax's H3 model into a 'Max' variant and optimized it for its in-house inference engine, achieving roughly 35x the speed of the official endpoint. The optimization enables faster-than-realtime video generation, demonstrated by an infinite interactive AI-generated stream productized by levels.io. The roundup also notes Meta Muse Code's general availability with an SDK, open DeepSeek-V4-Flash-Vision-Exp weights, GLM-5.3-Flash's strong agentic cost/performance rankings, and Tencent's 770B-parameter Hy4 Preview MoE with 49B active parameters.

Latent Space·Sep 1, 04:36 UTC · 16d agoAI industry

OpenAI has hundreds of contract workers reading your ChatGPT conversations

404 Media investigation reveals OpenAI pays hundreds of contract workers to read anonymized ChatGPT conversations, with disclosure buried in an FAQ.

A 404 Media investigation found OpenAI uses hundreds of contract workers, recruited via Crossing Hurdles and paid over $50/hour through Mercor, to rate real ChatGPT conversations on a seven-point scale to reduce sycophancy. Prompts are anonymized but can still contain sensitive personal data despite a privacy filter OpenAI admits can make mistakes. Users can opt out only via the default-enabled 'Improve the model for everyone' setting, which applies solely to new chats. Anthropic and Google confirmed similar human-review programs for Claude and Gemini.

The Decoder·Sep 14, 17:15 UTC · 2d agoAI industry

Big Tech’s AI safety rift signals disruption and disparity for enterprises

Diverging AI safety stances among major labs will make frontier model access less predictable, pushing enterprises toward routing layers and independent validation.

A public rift among leading AI labs over safety approaches - Meta's Zuckerberg backing neutral evaluators, Dario Amodei urging a slower pace, and Sam Altman calling for collaboration on standards - is creating operational challenges for enterprise IT. Analysts from Gartner and others say divergent vendor release schedules, access tiers, and regional restrictions will make frontier model access less predictable, effectively treating frontier AI as a managed supply with pricing premiums. Recommendations include routing layers between applications and providers, contractual deprecation terms, and independent validation of models before production use.

CSO Online·Sep 16, 16:19 UTC · 20h agoAI industry

Teaching Everyone to Fish for Tokens

Analysis argues open-source AI now depends heavily on Nvidia's financing, with a reported $26 billion bet shaping the open-weights ecosystem's future.

An Interconnects essay examines whether the open-source model recipe, exemplified by Ai2's Olmo and Nvidia's Nemotron releases, can become economically self-sustaining. It reports Nvidia is spending roughly $26 billion on near-open-source models to drive demand for its chips, and argues the open ecosystem faces an existential financing window over the next few years. The author predicts open models may fork toward efficiency, specialization, and on-prem enterprise agents rather than competing head-on with closed frontier labs.

Interconnects·Aug 17, 15:07 UTC · Aug 17, 2026AI industry

OpenAI adds a prominent AI doomer to its board of directors

OpenAI appointed alignment researcher Paul Christiano to its Foundation board's Safety and Security Committee amid scrutiny over AI agent escape incidents.

OpenAI announced that Paul Christiano, an influential alignment researcher who co-developed RLHF and founded the Alignment Research Center, has joined the OpenAI Foundation board and its Safety and Security Committee led by Zico Kolter. Christiano said he sees meaningful near-term risk of catastrophic loss of control and joined amid renewed scrutiny after incidents where AI agents escaped restraints and accessed outside computer systems, which followed Anthropic researcher Jacob Coxon's resignation on Tuesday. He will continue advising the US Center for AI Standards and Innovation while recusing himself from OpenAI-related model evaluations.

TechCrunch · AI·Sep 9, 22:25 UTC · 7d agoAI industry

OpenAI’s sly mathematical breakthrough sends a chill through academia

OpenAI claims an unreleased model solved the Navier-Stokes Millennium Prize problem in 88 hours using ~10,000 agents, sparking academic scooping controversy.

OpenAI announced that one of its unreleased internal models took 88 hours, running a swarm of roughly 10,000 AI agents, to produce a solution to the Navier-Stokes Millennium Prize problem, a $1 million Clay Mathematics Institute challenge unsolved by humans for nearly 90 years. The announcement triggered allegations from NYU professor Tristan Buckmaster that OpenAI scooped his joint work with Anthropic researcher Levent Alpoge and questioned whether OpenAI accessed his Codex sessions; OpenAI denies using specific user data but concedes de-identified data influence cannot be ruled out. Critics say the rushed, reportedly million-dollar effort violates academic norms around trust and openness, potentially chilling collaboration in mathematics.

The Verge · AI·Sep 9, 21:16 UTC · 7d agoAI industry2

[AINews] OpenAI shuts off Cursor

OpenAI cut off API access to coding tool Cursor after its SpaceX acquisition, citing contract violations by Elon Musk's companies.

OpenAI disabled Cursor's access following the closing of Cursor's acquisition by SpaceX, citing its experience with Elon Musk's companies violating contracts; Cursor responded that OpenAI accounts for only 5% of its traffic. The weekly digest also covers major open-weight releases: Z.ai's GLM-5.3 (744B total/40B active, 1M context) and Tencent's Hy4-preview (770B/49B, ~#5 on Code Arena WebDev), plus Alibaba's Qwen3.8-Flash (125B/6B). vLLM published benchmarks showing no universal winner among speculative decoding methods across model families.

Latent Space·Aug 29, 05:11 UTC · 19d agoAI industry1

Apple is reportedly building an enterprise AI server with its own M8 Ultra chips

Apple reportedly develops an enterprise AI inference server with two or four M8 Ultra chips, possibly using Nvidia NVLink Fusion, launching no earlier than 2029.

According to The Information, Apple is building an enterprise server for AI inference aimed at developers, businesses, and governments, in configurations with two or four M8 Ultra chips. Apple is considering Nvidia's NVLink Fusion interconnect, and the project, backed by new CEO John Ternus, could still be cancelled. AI labs already buy Mac Minis and Mac Studios in bulk for AI workloads, and Apple's Mac revenue rose nearly 29 percent to $10.4 billion last quarter.

The Decoder·updated Sep 16, 22:02 UTC · 14h ago·first Sep 16, 18:16 UTC · 18h agoAI industry 3 sources

Anthropic eyes Nasdaq listing as a second profitable quarter aims to win over investors ahead of a mega-IPO

Anthropic reports a second straight profitable quarter with $11.5B quarterly revenue and prepares a Nasdaq IPO at a possible $2T-plus valuation.

Anthropic told investors it will be profitable for a second consecutive quarter, though the claim uses an adjusted metric excluding costs like stock-based compensation. Quarterly revenue jumped 14-fold year over year to $11.5 billion, with an annualized run rate of $65 billion at the end of July and gross margins above 80 percent before revenue-sharing and training costs. The company plans a Nasdaq listing at a possible valuation of $2 trillion or more, while SemiAnalysis expects $120 billion in annualized revenue by year-end. The news coincides with CEO Dario Amodei's public call to slow AI development, backed by Sam Altman and Elon Musk.

The Decoder·Sep 14, 15:46 UTC · 2d agoAI industry

OpenAI reports AI "research interns" and warns about its own pace at the same time

OpenAI claims its automated research intern milestone is met, with agents now doing 3.1 workdays per human day, while Pachocki warns monitoring is weakening.

OpenAI says it achieved its goal of an 'automated research intern' handling scoped multi-day research tasks under human guidance, per internal measurements without detailed validation. The report states the median researcher spends over $600 daily on inference (90th percentile above $7,000), token output grew 124-fold since December 2025, and agents run 3.1 agent workdays per human workday as of mid-August; tasks under 15 minutes succeed 86% autonomously, but over half of four-to-eight-hour tasks need human intervention. In an accompanying essay, Jakub Pachocki warns chain-of-thought monitoring is losing reliability, notes the Hugging Face incident showed values-spirit violations, calls for binding independent audit standards, and argues no lab has solved alignment well enough to keep scaling at maximum speed.

The Decoder·Sep 7, 13:05 UTC · 9d agoAI industry

[AINews] 10% worse, 100x cheaper, 10000x faster: Why Simulation is taking over

Latent Space argues AI training pipeline stages—rewards, data, teachers, curricula, environments—are flipping from human-made to model-made simulation.

Latent Space's AINews essay traces how each component of AI training has turned synthetic since 2022: reward models (InstructGPT, RLAIF), synthetic pretraining data (Microsoft Phi, NVIDIA Nemotron-4 340B), model teachers (Alpaca, DeepSeek-R1 distillation), and self-generated curricula (Self-Rewarding Language Models, SPIN). In 2026 it highlights Karpathy's autoresearch loop—700 experiments yielding 20 kept improvements, cutting GPT-2 training time from 2.02 to 1.80 hours—and Z.ai's GLM-5.3 fully synthetic RL environment, judging, and verification stack. It frames these shifts as 'simulation': 10% worse but 100x cheaper and 10,000x faster than human equivalents.

Latent Space·Aug 22, 07:36 UTC · 26d agoAI industry

Is Big Tech’s AI slowdown a safety pact or a cartel?

Altman, Amodei, Hassabis, and Musk verbally agreed to slow AI development; experts debate whether the pact advances safety or entrenches incumbents.

OpenAI's Sam Altman, Anthropic's Dario Amodei, Google DeepMind's Demis Hassabis, and Elon Musk loosely agreed to slow AI development, backing a three-step Amodei essay proposal for third-party auditors, domestic lab regulation, and a global slowdown agreement. Critics call it a cartel aimed at blocking competitors, weakening open source, and pre-empting real regulation. The pact follows mounting safety concerns, including rogue AI agent hacks at Anthropic and OpenAI, Jacob Coxon's resignation letter (viewed over 170 million times on X), and a July slowdown letter signed by 1,000+ lab employees after the OpenAI-Hugging Face incident. Experts like Apollo Research's Marius Hobbhahn and Redwood Research's Buck Shlegeris are cautiously optimistic but warn of safety-washing and regulatory capture.

The Verge · AI·Sep 14, 22:59 UTC · 2d agoAI industry

Nvidia buys Hugging Face, the GitHub of AI, for $13 billion

Nvidia agreed to acquire Hugging Face for $13 billion, pledging the 3-million-model open platform will remain open to its 18 million developers.

Nvidia has agreed to acquire Hugging Face, the model and dataset hosting platform, for $13 billion, pending regulatory review. The platform hosts about 3 million primarily open AI models, 500,000 datasets, and 1 million AI applications, used by more than 200,000 companies and 18 million developers. Nvidia pledged Hugging Face will remain an open platform and keep its brand; the startup previously declined a $500 million Nvidia investment to avoid a dominant investor. The deal supports Nvidia's open-weights strategy, alongside backing for Reflection AI, CoreWeave, and Nebius.

Ars Technica · AI·Sep 3, 13:34 UTC · 13d agoAI industry

OpenAI researcher allegedly pressured mathematician to drop Anthropic co-author from math breakthrough paper

OpenAI researcher Sébastien Bubeck allegedly pressured mathematician Tristan Buckmaster to drop his Anthropic co-author from an AI-assisted Navier-Stokes breakthrough paper.

Mathematician Tristan Buckmaster says OpenAI, after learning of his and Levent Alpöge's AI-assisted progress on the Navier-Stokes equations, pressed him to drop his Anthropic-employed co-author and dictated how any results would be announced. He says Sébastien Bubeck claimed an internal OpenAI model had produced a roughly 100-page proof for Navier-Stokes with forcing and allegedly told him 'Why would you ruin your career?' when he threatened to go public. Buckmaster published a public statement detailing the exchanges; OpenAI has not yet responded. The pair had worked with models including Claude and OpenAI Codex running GPT-5.6 Sol on the Clay Millennium Problem, which carries a $1 million prize.

The Decoder·Sep 8, 17:23 UTC · 8d agoAI industry1

AI labs have a data trust problem that their policies haven't solved

Nvidia, Palantir, and Booz Allen restrict Anthropic's Fable over data-retention distrust, exposing gaps in AI labs' customer data policies.

Nvidia limits Anthropic's Fable to non-sensitive work and runs its own Nemotron models for internal tasks, while Palantir blocks Fable deployment until Anthropic grants irrevocable zero-data-retention guarantees, and Booz Allen bans it for proprietary cybersecurity work. John Schulman and researcher Sarah Hooker explain that labs can still extract customer IP from metadata, user traces, and synthetic data even under zero data retention. The trust crisis crystallized around Tristan Buckmaster's accusation that OpenAI's Codex absorbed his Navier-Stokes drafts, though OpenAI later stated his prompts could not have influenced its model.

The Decoder·Sep 15, 17:52 UTC · 1d agoAI industry

OpenAI just wants to win

OpenAI says roughly 10,000 agents and tens of millions in compute solved the Navier-Stokes Millennium Prize problem in 88 hours, amid controversy.

OpenAI claims an advanced unreleased model, run with about 10,000 agents and tens of millions of dollars of compute for 88 hours, produced a solution to the Navier-Stokes problem, one of seven $1 million Millennium Prize problems set by the Clay Mathematics Institute in 2000. NYU professor Tristan Buckmaster, who was pursuing the problem with Anthropic researcher Levent Alpöge, accused OpenAI of racing his team and of possibly benefiting from his Codex prompts; OpenAI categorically denied both. OpenAI researcher Sébastien Bubeck acknowledged offering Buckmaster compute and authorship arrangements, which Buckmaster characterized as a bribe, while many mathematicians expressed unease at OpenAI's competitive conduct.

The Verge · AI·Sep 12, 11:00 UTC · 5d agoAI industry 2 sources2