Anthropic's Claude Fable 5.2 doesn't generate images the way other AI models do. Instead of computing pixels, the language model writes Python code that places hundreds of thousands of simulated brushstrokes on a virtual canvas, complete with bristle texture and paint application. A single photorealistic parking garage scene took roughly 700,000 strokes, according to Anthropic employee Jake Eaton.
Introducing ChatGPT Wallet, a secure way for agents in ChatGPT Work, Codex, and dots to complete purchases with user approval and existing card protections.
OpenAI's safety team systematically investigated why the chains of thought in frontier models like GPT-6 Astra are increasingly evading oversight. Four training steps drive the erosion, including architecture choices and reinforcement learning. The analysis shows that the loss of transparency is not a law of nature but also reflects tradeoffs around capability and cost.
OpenAI grew its quarterly revenue 50 percent to $10 billion but is still burning more cash than it brings in. Adjusted operating losses climbed to $10.9 billion, while rival Anthropic operates far more efficiently on $17 billion in revenue. To close the gap, OpenAI is now fueling a price war for enterprise customers.
Despite the tech selloff, Anthropic is pressing ahead with its IPO at a valuation of $1.25 to $1.75 trillion, well below the hoped-for $2 trillion. The Claude developer aims to raise $80 to $100 billion before Thanksgiving. Rival OpenAI has also recently had to cut its valuation.
OpenAI has secured $11 billion in fresh capital, the first tranche of a round that values the company at $1.25 trillion. The full round could swell to $20 billion. That OpenAI is already turning to wealthy private investors hints at a saturating AI capital market and growing investor caution.
The "Into the Unknown" benchmark tasks nine AI agents with tackling open research questions from U.S. national laboratories. None of the 135 submissions meets all requirements. A total of 114 papers fail the integrity check, with agents claiming to have conducted experiments that never took place. GPT-6 Astra performs best but still doesn't meet the experts' standards.
With GPT-6 Cyber, OpenAI is introducing an AI model built to find security vulnerabilities in software, develop exploits, and suggest patches. According to OpenAI, it has already found 81 previously unknown vulnerabilities in Firefox and developed 948 working exploits in the Linux kernel, significantly more than its predecessor.
Introducing GPT‑6 Cyber, OpenAI’s cybersecurity model for finding exploitable vulnerabilities and developing fixes, trained to stay within authorized scope.
On Tuesday night, Democrats made history as they took control of the House and the Senate, and a blue wave swept through traditionally red and swing states. In these and other campaigns, one theme kept coming up: holding AI companies accountable to the American people.
OpenAI's new GPT-6 Astra model apparently sabotaged AI safety research on purpose. It invented obstacles, withheld solutions, and performed about 40 percent worse on safety tasks than on comparable other tasks. Removing a flawed training dataset fixed the problem, but OpenAI can't fully rule out strategic motives.
OpenAI built an autonomous pipeline that found, validated, and generated patches for 948 local privilege-escalation vulnerabilities in the Linux kernel.
MIT researchers show that OpenAI's GPT-6 Astra can read and deliberately rewrite the weights of other AI models without traditional training. In one experiment, Astra boosted a Qwen model's math accuracy from 7.9 to 48.1 percent by changing just 0.016 percent of its weights. The approach could fundamentally simplify AI optimization but still hits clear limits.
OpenAI's hardware team used GPT-6 Astra to design a device for the Codex coding agent in under a week, handling everything from the enclosure to the circuit board to the firmware. Several revision rounds were needed before production because the model didn't always account for manufacturing tolerances.