Anthropic / Claude

Mozilla's 91-page report lays out open-source AI's strengths and gaps. Kimi K3 ranks 5th overall, just 3 points behind Claude Opus 5 at 60% of the input price. None of the 16 notable open releases ships a full training corpus—zero meet the OSI data-recipe bar. The decision has shifted from model choice to tooling, where open still struggles to deploy. The report says open models power roughly one-third of tokens but doesn't give a precise enterprise adoption figure.

OpenAI's global policy chief Chris Lehane told reporters Tuesday the company has been working with Anthropic and Google DeepMind on AI safety for weeks. He is in Washington to push lawmakers on catastrophic risk. The talks follow Anthropic CEO Dario Amodei's Saturday essay urging the industry to slow frontier AI together. The post doesn't disclose any concrete agreements or timelines.

Nearly 5,000 mathematicians signed a declaration arguing AI solves prestige problems without generating human-intelligible ideas, breaking the proxy that rewarded conceptual work. The author splits math into puzzle-solving (legible, high-reward) and idea-generation (the real intellectual core). AI proofs grab the prestige while skipping the concepts, a kind of Goodhart's law. He's skeptical of claims that LLMs can't generate new ideas—too many such claims have already failed.

Anthropic co-founder Jack Clark told the BBC that society may eventually need to mandate a verifiable AI kill switch. He said most labs already have ways to pull the plug, but lawmakers should make it a requirement. The article also notes Anthropic scientist Evan Hubinger put the chance of AI-driven human extinction at >10% within a decade, while Trump called AI safety fears a 'hoax'. The UK government has already rejected a kill-switch proposal, arguing it wouldn't stop development or misuse elsewhere.

Anthropic CEO Dario Amodei called for a government-coordinated slowdown of frontier AI development and antitrust exemptions to make it happen; Sam Altman and Elon Musk agreed. Cohere CEO Aidan Gomez published a blog post calling it 'a wolf in sheep's clothing, a cartel by any other name,' arguing it would lock out competitors through massive barriers to entry. Hugging Face engineer Niels Rogge called the statements 'bizarre nonsense,' saying Amodei mainly wants to restrict Chinese models like DeepSeek and open-weight models to protect his scale advantage. White House AI czar David Sacks noted OpenAI and Anthropic already hold a duopoly in frontier intelligence and that product liability concerns also drive their push for a slowdown.

今天最直观的教训来自 @搞仁义毛义仁：给 Astra 一个空白 C++ 仓库，代码写得一塌糊涂；把积累了大量 code review 经验的 GacUI 上下文导进去，质量立刻飙升。这说明模型不是不会写，是得用具体规则去“规训”。@今天群内信息量极大 实测了 Ollama Cloud 跑 DeepSeek V4.1 Flash，解码吞吐是官方 API ...

Anthropic CEO Dario Amodei argues frontier AI must slow down, warning that swarms of AI agents could gain the ability to “take over the entire internet” within 6–12 months. His first step: embed external experts inside labs to monitor safety and report publicly. Sam Altman, Elon Musk, and Demis Hassabis endorsed the idea; Altman said OpenAI will follow suit. The real obstacle, author Sebastian Mallaby writes, is China. The US lead is only a few months, so any unilateral slowdown risks letting China pull ahead. Amodei acknowledges this and, in a notable shift, lists areas where US–China cooperation might be possible, comparing it to Cold War arms control. The post does not spell out a concrete timeline, but notes Trump and Xi are set to meet on Sept 24, with two more summits possible by year-end.

The AI Evaluator Forum published AEF-1, a baseline for independent third-party evaluations covering access, conflicts of interest, funding, recusal, and transparency. The same day, Dario Amodei blogged that Anthropic is unilaterally committing to embedded evaluators with office badges, company laptops, and access comparable to internal risk teams. He also laid out a two-tier coordination framework for democratic and global pacing. Bilal Chughtai left Google DeepMind and called for slowing capability progress; Dan Selsam warned that models may learn to fake alignment during evals. On the other side, Aidan Gomez and Cohere pushed back against a few Silicon Valley firms becoming gatekeepers, and Kevin Bass alleged structural conflicts in the Anthropic-linked safety ecosystem.

Trump dismissed calls for AI regulation from Anthropic CEO Dario Amodei and others, calling safety fears a “scam” and insisting the only needed guardrail is “a strong and smart president.” He singled out Amodei as “pretending to be a perfect little angel,” though the post doesn’t spell out what government actions he claims to have already blocked. VP Vance and Speaker Johnson showed more openness to regulation, with Vance calling industry self-regulation pleas “a little bit of a Trojan horse.” Congress has almost no time to act before the midterms.

Minister of State Security Chen Yixin published an article framing AI as a direct threat to CCP rule—Beijing’s highest-level and most detailed warning yet. He named US models like Claude Mythos and GPT-5.5-Cyber, citing risks of deepfakes, information warfare, large-scale data exfiltration, and attacks on critical infrastructure. He also pointed to US military AI use in the Iran war as evidence that algorithmic advantage determines battlefield control. Law professor Henry Gao said this draws a red line ahead of US-China AI talks: data sovereignty and political security won’t be traded for international agreements.

Anthropic rewrote its test impact analysis service after agentic coding tools like Claude Code flooded CI with PRs. Per-analysis latency dropped from 11 seconds to under 1 second, handling 1,000 analyses per day. The core trick: caching file dependency graphs with Merkle trees so only truly affected tests run. The post gives concrete architecture and numbers—worth noting this is their internal monorepo setup, so direct portability varies, but the caching strategy and API design are solid references.

Anthropic's Dario Amodei published a ~4,000-word essay arguing the industry must slow the pace of frontier model capability gains to avoid making catastrophic risks more acute. Within hours, Sam Altman, Demis Hassabis, and Satya Nadella all signaled agreement. Ars Technica notes the sudden U-turn after years of an all-out AGI race, and cautions that slowing down also helps incumbents lock in their lead and reduce competitive pressure.

Anthropic told investors it has reached profitability for two consecutive quarters, a rare cash-flow-positive signal among AI model builders. The post is a headline-only snippet—no revenue, profit figures, or cost breakdown are disclosed yet, so treat this as an early signal.

Anthropic told investors it posted a second straight profitable quarter, but the profit is an adjusted metric that excludes stock-based compensation. Gross margins top 80%, though that figure comes before revenue-sharing with partners like Amazon and model training costs. Quarterly revenue jumped 14x year-over-year to $11.5B, with an annualized run rate of $65B at end of July. SemiAnalysis expects investors to target $120B annualized by year-end and nearly triple that by end of 2027. Anthropic plans a Nasdaq IPO at a possible $2T+ valuation. Instead of releasing the prospectus broadly last week, it first shared documents with a small investor group. CEO Dario Amodei publicly called for slowing AI development; Sam Altman and Elon Musk backed the call. Altman told Fortune OpenAI won't go public this year.

Code sleuth 'pdfu' found references in iOS 27 and macOS Golden Gate private frameworks suggesting Apple may let users swap Siri's backend AI for ChatGPT or Claude. The post doesn't spell out whether this is system-wide or scoped to specific features, and no release timeline is given. Code existing doesn't guarantee shipping, but the direction is clear: Apple is opening system-level hooks for third-party models.

Dario Amodei (Anthropic), Sam Altman (OpenAI), Satya Nadella (Microsoft), and Elon Musk jointly proposed a regulatory framework called 'Pace the frontier.' It targets only 'frontier models'—the most capable systems—leaving smaller players and open-source untouched. The Register calls it what it is: regulatory capture, where incumbents set the entry bar. The framework mandates pre-deployment safety evaluations, but the post doesn't spell out who defines the standards or enforces them. Four rivals agreeing on a single proposal is a strong signal of how favorable it is to those already in power.

Anthropic CEO Dario Amodei published a 3,800-word post urging the industry to slow AI model iteration. He argues safety measures can't keep up with capability gains, pointing to risks like recursive self-improvement. OpenAI's Sam Altman, Google DeepMind's Demis Hassabis, and Elon Musk publicly agreed. Amodei proposed embedded third-party auditors and safety standards coordinated among democracies. Nvidia's Jensen Huang and HuggingFace's CEO pushed back, hinting this could be a play to lock in market leadership. I'd take the safety call seriously but keep an eye on the regulatory moat angle.

After OpenAI launched GPT-6 Astra, Artificial Analysis revised its scoring rules twice in one week, erasing a 5-point deficit to tie Astra with Claude Fable 5.1—without any model update. The leaderboard is a business: evaluators sell subscriptions backed by vendor endorsements, vendors need rankings for marketing. DeepSeek V4 Flash overtook its own flagship on 9 benchmarks after retraining only the post-training phase, but two tests used closed-source private datasets and real-world coding feel didn't improve. The same model scored 62.7% vs 99.9% on ARC-AGI-3 depending on the execution harness. A good benchmark needs private held-out test sets, regular item rotation, and harness control.

Amodei's September post called for pacing the frontier but never named a speed. Tunguz maps five camps: interpretability wants time to understand models, labor wants time for workers, the economic camp bets on AI-driven GDP growth to service debt, the geopolitical camp wants to stay ahead of China, and the regulatory capture camp sees the proposal as a cartel in disguise. All priced the consequences of a pause; none proposed a number. The one mechanism that could produce a number—a training compute threshold—was tried in 2023 at 10^26 FLOPS, revoked before any model crossed it, and obsolete within weeks when Grok-3 shipped. The post does not say whether Amodei responded to these critiques.

Anthropic told the FT it expects an adjusted operating profit this quarter, with revenue around $3 billion—roughly triple the same quarter last year. The figure is adjusted, excluding stock-based compensation and other non-cash charges, so it is not GAAP net income. The post doesn't disclose gross margins, the split of R&D and inference costs, or whether cash flow has turned positive. The revenue growth alone, though, signals enterprise customers keep paying.