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Anthropic CEO Amodei wants AI speed limits before self-improvement outpaces human control

Anthropic CEO Dario Amodei is calling for a controlled slowdown in AI development. He warns that recursive self-improvement could threaten the entire internet within six to twelve months and proposes embedded auditors at AI companies, shared safety standards, and global agreements modeled after the SALT disarmament treaties. His warning comes just ahead of what could be the largest initial public offering in history.

Read full article about: GPT-6 Astra appears to show a "step change" in spatial reasoning based on early benchmarks

GPT-6 Astra appears to be a big leap forward for spatial reasoning. A new robotics benchmark called StationeryBench pits OpenAI's GPT-6 Astra against Ai2's MolmoAct2 across five desk-object tasks like uncapping a marker, pouring out paper clips, or passing a ruler between two robot arms. Both models controlled the same dual-arm YAM robots across 200 trials. Astra fully completed 7 out of 100 tasks; MolmoAct2 completed zero. Astra's median progress score hit 46 out of 100, MolmoAct2 managed 12. All results, videos, and code are on GitHub. OpenAI has long-term plans to build its own consumer robots.

Yoav Artzi, an AI researcher at Cornell and Google DeepMind, calls Astra a "step change in spatial reasoning." On the still-unpublished REMAP benchmark, GPT-Astra reaches accuracy close to human level, though Artzi notes that "even ASTRA doesn't get to what humans do in other scenarios." He suspects OpenAI trained the model on large amounts of 3D data such as Blender scenes. That lines up with Astra's particular improvement on 3D tasks.

Read full article about: Nvidia wants to pour up to $10 billion into Anthropic's record-breaking IPO

Nvidia is in talks to invest up to $10 billion in Anthropic's planned IPO, Reuters reports. The company behind Claude wants to raise up to $100 billion and land a valuation of around $2 trillion. That would make it the largest IPO in history. Nvidia would come in as an anchor investor, locking in shares before the stock hits the open market.

The two companies are already closely linked. Anthropic runs on Nvidia GPUs and committed in 2025 to buying $30 billion in Azure compute packed with Nvidia chips. Revenue went from around $9 billion at the end of 2025 to over $65 billion by July 2026. The IPO is expected to wrap up before the US midterms in November.

Nvidia is still playing central bank for the AI industry, investing in customers like Anthropic and OpenAI while backing some $300 billion in guarantees that help data centers secure financing. Most of that money circles right back to Nvidia in chip orders.

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GPT-6 Astra needs leaner prompts and fewer guardrails, OpenAI recommends

Overly long skill descriptions, blanket reading requirements, and rigid approval rules can get in GPT-6 Astra’s way, warns OpenAI’s Eric Provencher. More capable models need less hand-holding, so developers should tie instructions to specific tasks and spell out when the job is done.

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Google's new AI model predicts the future from sales data, weather, and discount schedules

Google Research has released TimesFM-3, a forecasting model that analyzes time series alongside related data and known future events like sales promotions or weather forecasts. Instead of predicting the future step by step, the 330-million-parameter model fills in all future time points in a single pass, which cuts compute time and reduces compounding errors.

Ex-Deepmind VP Vinyals says AI self-improvement is coming but won't trigger an intelligence explosion

Oriol Vinyals, until recently head of research at Google DeepMind, thinks a sudden AI intelligence explosion through recursive self-improvement is unlikely. AI can speed up research by a factor of ten, he says, but it hits two bottlenecks: coming up with ideas (“research taste”) and reliably judging results. Reward hacking and the speed of light add further limits. Vinyals now wants to tackle these bottlenecks with his startup Discovery Loop, co-founded with Jeff Dean, Sanjay Ghemawat, and Quoc Le.

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Read full article about: Deep Learning pioneer Bengio argues the training process itself makes AI dangerous

AI researcher Yoshua Bengio is adding his voice to a growing chorus of warnings about AI safety, arguing that advanced AI agents could spiral out of human control. In a new essay, he warns that the better AI agents get at optimizing goals, the better they also get at deceiving users, gaming rules, coordinating with each other, and hiding bad behavior. Bengio says this behavior emerges from the training process itself, from imitating human text through reinforcement learning, and that poorly defined goals can push systems to optimize against human intent. Anthropic's research supports his view.

The deep learning pioneer has called for years to slow AI progress and only train or deploy models after independent safety reviews, and about a year ago founded LawZero to build safer AI systems. Many of the recent warnings have come from inside the AI labs themselves, fueling talk of an industry-wide slowdown.

But Donald Trump disagrees. The US president sees no threat and wants to keep outpacing China, warning the US could end up in a "very bad position" if it doesn't win the AI race.