AI agents enter mathematics, personal errands, and the laboratory

OpenAI presents an AI-produced Navier–Stokes proof

OpenAI published what it says is a solution to the Navier–Stokes existence and smoothness problem, one of mathematics’ Millennium Prize Problems. The company says an unreleased model more capable than GPT-6 Astra coordinated roughly 10,000 agents, found a finite-time singularity after 88 hours, and then used GPT-6 Astra to formalize the proof in Lean over another 17 hours. The paper and formal proof are public, but the result still needs sustained scrutiny from mathematicians before it should be treated as settled.

The mathematics arrived with a priority dispute. OpenAI says it began the effort after hearing that NYU mathematician Tristan Buckmaster and Anthropic researcher Levent Alpöge had made related progress. The Guardian reported that Buckmaster worried their unpublished work, which had been handled through Codex, might have been visible to OpenAI. He stopped short of alleging misuse; OpenAI denied accessing the material, while acknowledging it could not rule out that product usage had helped improve its models. The proof’s validity and the provenance of the ideas are separate questions, and both deserve examination.

Meta gives a personal agent its own computer

Meta launched Muse, a personal agent for US adults that can work through a standalone app or WhatsApp. The company says Muse can send email, book travel, fill out forms, and break long-term goals into plans. It runs inside a dedicated virtual machine containing its browser and user data, while a separate Sentinel system decides whether requested outbound actions are allowed, blocked, or sent back to the user for approval.

That separation is the product’s central bet. Useful personal agents need broad access to accounts and private context, which also raises the cost of a bad decision. Meta describes the architecture as private and user-controlled; the Associated Press notes that adoption will depend on whether people trust the company with enough access for the agent to be useful.

ChatGPT Images gets faster, more persistent editing

OpenAI released ChatGPT Images 2.5 across ChatGPT, ChatGPT Work, and Codex, with two API variants called GPT-Image-2.5 Flare and Sunburst. The company claims the new model cuts generation latency by as much as 50% from Images 2.0 and better preserves subjects and composition through repeated edits. New ChatGPT tools include direct sketching, templates, image comments, and shareable prompts.

OpenAI says people now create more than 3 billion images a week across ChatGPT Images and its image APIs. At that scale, mundane improvements such as keeping an unedited face, object, or layout intact can matter more than a dramatic demo. The release retains C2PA metadata and invisible watermarking, according to the company.

An agent calibrates a real quantum chip

Researchers from MIT and OpenAI connected GPT-5.6 Sol through Codex to the software controlling a previously uncalibrated six-qubit superconducting chip. The agent selected measurement parameters, operated laboratory hardware, analyzed results, and stored calibrations. In the case study, it found all six readout resonators; across 40 target measurements for four fixed-frequency qubits, researchers intervened to improve four.

The boundary is as informative as the success. Clear signals let the agent run standard sequences with little supervision, while weak or noisy measurements still needed an experienced researcher. This is automation of a narrow, tool-mediated laboratory workflow, not autonomous scientific judgment, but it shows agents crossing from software into live experimental systems.

OpenAI funds research on teens and generative AI

OpenAI committed up to $5 million for independent studies of how generative AI affects people ages 13 to 17. Individual grants may reach $1 million, with proposals covering social and emotional development, relationships, usage patterns, safeguards, and age-appropriate design. Applications close October 6.

The program explicitly asks applicants to disclose conflicts and address consent, privacy, data security, and responses to disclosures of harm when research involves minors. Funding studies is not evidence that current products are safe; the useful output will be whether credible researchers publish methods, limitations, and results that can challenge provider assumptions.

Missouri scales AI training statewide

Google and Missouri announced free AI tools and career training for public schools and residents. Google says the agreement covers nearly 100,000 educators and more than 1 million students, while local job centers will offer professional certificates in fields including cybersecurity and data analytics.

The partnership moves generative AI adoption from individual classroom trials into statewide infrastructure. Its value will depend less on access alone than on implementation: teacher support, student privacy, clear usage rules, and evidence that the tools improve learning rather than simply increasing use.