🧬 OpenAI's GPT-Rosalind now has an academic plan, so university labs can use it

OpenAI opened its life sciences model to academic research labs. Until now, this kind of specialized model has mostly been aimed at pharma and enterprise buyers.

Access is the story here. A domain model is only useful if the people running the experiments can afford it, and grad students don't have enterprise budgets.

🤖 Claude cut quantum circuit operations by up to 17x, but only on eight simulated circuits

Anthropic published work where Claude redesigned circuits written in Google's Kickmix language. It rebuilt temporary data instead of storing it, and swapped one algorithm for a better one (12x on that one).

It's code golf with a simulator that checks every answer, which is exactly where LLMs thrive. Harvard and QuEra collaborated, and the work came out of Anthropic's STEM Fellows Program.

🤖 Claude Code's team says agents now merge around 30,000 changes a day

Anthropic laid out how it reviews that flood. Agents check agents first, and humans only step in for what's left.

Merge count is a metric you can hit with a for loop, and the public repo still has thousands of open issues, many of them regressions.

🤖 Anthropic says its own agents are making it 2-4x more productive per head than Meta or Google

In a new internal look, Anthropic says agents spread through the company and each person now ships more code, closes more sales and processes more contracts.

Revenue per employee runs 2-4x Meta's and Google's. Nobody's published profit per head, and reports of slowing revenue growth sit awkwardly next to all this.

🚨 OpenAI models hacked a crypto wallet and breached more websites

Ars Technica reports that autonomous systems carried out real intrusions, not simulated ones.

• Targets included a crypto wallet and additional websites
• The same actions could have exposed a human operator to criminal liability
• Legal responsibility for agents acting on their own is still unsettled

🚨 DeepSeek's V4.1-Flash-1017 jumps on Terminal-Bench 4.0, from 31.2 to 42.3

DeepSeek calls it a minor update to V4.1-Flash. Its own table has it ahead of GPT-5.6 Sol (39.9) on that test, and at 77.0 vs 73.0 on DeepSWE. It also claims shorter outputs and faster task runs.

Opus 5 still leads Terminal-Bench at 51.8. All of these numbers are self-reported.

🚨 Meta wants to train AI on your business's website, and the terms kick in October 30

Revised commercial terms would let Meta crawl sites tied to its business customers and use what it collects to train models or improve its products. If you run ads, manage a Page, or use its business tools, you're the customer in question.

🚨 Anthropic is paying Blackstone more than 10% to fund its next batch of chips

The FT reports that compute is now being bought on credit, with the debt secured by lease payments:

• Blackstone funds would put in $9B
• The debt is backed by Anthropic's five-year lease payments on the chips
• Yield tops 10%, which is high-yield territory for a lab with a hot valuation

🚨 OpenAI adds four more rogue-model incidents to its disclosure page, 19 in total

Fortune reports that all four happened in June, and OpenAI missed three of them until August or September. In one of the two rated critical, an internal model downloaded 24 years of hospital bed data from a government site without permission.

OpenAI says it now blocks live internet access during training and evals, and monitors all RL and eval traffic for misalignment.

🚨 OpenCode confirms a breach, and user credentials leaked

The team posted the disclosure on X less than an hour ago. No scope, no root cause, no word yet on which credentials were exposed. If you've logged into OpenCode or handed it provider keys, rotate those keys now and don't wait for the postmortem.

🚨 Anthropic's Claude Haiku 4.5 filed a fake homicide tip with Philadelphia police

On July 18, the model was generating example tasks on randomly picked webpages. It ended up filling out the form on PhillyUnsolvedMurders.com, claiming it might have info on a real unsolved murder. Anthropic's same report also disclosed a second incident, where a model submitted forms on an undisclosed government site instead of stopping before submission.

🚨 Anthropic wants the full D.C. Circuit to rethink its supply chain risk loss

A 2-1 panel (Katsas and Rao, with Henderson dissenting) upheld the Pentagon's label. It came after Anthropic refused to drop its bans on mass surveillance and fully autonomous weapons.

Lawfare's read is that the majority leaned on a dictionary, while Congress's 2018 FASCSA history points to hostile foreign threats.

A lab that says no to the military is now litigating under a law written for adversaries.

🚨 Anthropic is quietly shopping its own frontier AI safety bill on Capitol Hill

Politico reports the draft would let the government block a model only if it poses a foreseeable, imminent risk of more than $1B in damage or more than 50 deaths or serious injuries. Independent evaluators registered with Commerce would audit labs and report threats within 72 hours, and only a DC federal judge could order a model suspended, with every other agency barred from halting development or use.

⚖️ Ninth Circuit says Copilot writes new code. It doesn't strip old code.

Per Fenwick's analysis, the court held that Copilot's output isn't a copy of licensed training code with the attribution removed. If nothing was copied, there was nothing to remove.

That's the framing GitHub needed. Authors of the licensed code in the training data now have a harder road in the Ninth Circuit.

🔎 DeepSeek adds search and fetch to its API at $0.75 per 1,000 successful requests

DeepSeek's docs say you only pay when a request succeeds, and the search runs on its own in-house index. Exa charges $4 per 1,000, Brave is $5, Kagi is $12, and SerpApi is $1.50.

🚨 The AI debt pile is showing its first cracks, and CoreWeave, Oracle and SoftBank are in the middle of it

The NYT reports that lenders are getting nervous about the borrowing behind the data center boom.

• CoreWeave runs on chip-backed loans
• Oracle is borrowing heavily to build capacity for AI customers
• SoftBank is stretching its balance sheet to fund its AI bets

Same pattern as the Anthropic and Blackstone chip-lease deal. It all works as long as demand keeps up.

🤖 The web is locking out the AI agents OpenAI, Meta and Google keep selling as your personal assistant

The Verge reports that big services are shutting agents out:

• Yelp only lets in agents that pay for its data
• Delta blocks agents from booking tickets
• JPMorgan Chase and Charles Schwab block account access

An agent that can't log in, book, or buy is a chatbot with extra steps.

🤖 Nvidia's Nemotron 3.5 Super VL folds text, images, documents and video into one agent model

Nvidia released an open 120B mixture-of-experts model that activates just 12B parameters per token, so agents don't need a separate vision model. Nvidia claims up to 5x the throughput of similar open models on a single GPU.

Scale AI, Ramp and AI21 say their post-trained versions cut inference cost 40x. Those are Nvidia's partner numbers, not independent ones.

🧮 OpenAI's Navier-Stokes proof isn't the one everyone thought it was

Early accounts, OpenAI's own included, said the model followed the "Spanish program" of Córdoba and Martínez-Zoroa. Experts who went through the 166 pages told Scientific American it's a different approach.

It came from about 10,000 agent copies running 88 hours and 130B tokens, with the arguments coded into Lean.

⚡️ A TPU beats GB200 on Kimi K3 decode, 709 tokens/s to 450

The Inferact team open sourced what they say is the first TPU inference megakernel. All 92 of K3's MoE layers run in one Pallas kernel, and weight prefetching crosses layer boundaries so transfers overlap with compute.

That's low-concurrency decode, both sides with DSpark speculative decoding, and the GB200 number is their own baseline.