🚨 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.
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.
X (formerly Twitter)
OpenCode (@opencode) on X
We had a security breach last night related to a large scale distillation attack that impacted 1.4% of OpenCode Console users
We have notified them all this morning via email
The incident is ong…
We have notified them all this morning via email
The incident is ong…
🚨 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.
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.
NBC News
Anthropic says its AI model submitted a false cold case tip to Philadelphia police
The bad tip “had minimal impact,” but Anthropic said it takes the action seriously, as “the same behaviors could do far more harm as models become more powerful.”
🚨 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.
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.
Default
Why Anthropic Is Asking for a Rehearing En Banc
The D.C. Circuit relied on a dictionary for key parts of its ruling against Anthropic. Congress’s own words tell a different story about the threats the law was designed to address.
🚨 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.
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.
POLITICO
Anthropic quietly pitches its own AI safety bill to lawmakers
The draft proposal would limit the circumstances in which the government could block the release of an advanced model and preempt some state AI safety laws.
⚖️ 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.
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.
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.
Deepseek
Search & Fetch | DeepSeek API Docs
The Search API and the Fetch API give agents and RAG applications access to live web content:
🚨 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 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.
Nytimes
Weak Links Start to Show in A.I. Borrowing
Debt trouble at CoreWeave, Oracle and SoftBank raises questions about whether there are broader problems with the data center build-out.
🤖 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.
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.
The Verge
Websites are closing their doors to AI agents
Online roadblocks are undermining the narrative behind AI agents.
🤖 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.
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.
NVIDIA Technical Blog
NVIDIA Nemotron 3.5 Super VL Powers Specialized Agents with Multimodal Reasoning
Always-on agents are taking on longer, more complex enterprise workflows. A single request can involve reading a document, checking information across sources, following company policy…
🧮 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.
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.
Scientific American
OpenAI’s blockbuster Navier-Stokes proof isn’t what we thought it was
Rumors that OpenAI’s “Navier-Stokes” solution stole the work of two mathematicians may have been overblown
⚡️ 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.
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.
vllm.ai
Hyper Optimizing Kimi K3 in vLLM: Moving Fast and Responsibly
How agent-assisted CuTe DSL optimizations accelerate Kimi K3 decode on NVIDIA GB300, and how scoped changes, correctness tests, and reproducible benchmarks help
🚨 AI's debt pile is now spooking the people who funded it
The Economist looks at how labs and neoclouds are borrowing to build data centers, and who gets stuck if the cycle breaks. Anthropic's Blackstone chip financing and its lowered IPO valuation hopes show the strain in more than one place.
The Economist looks at how labs and neoclouds are borrowing to build data centers, and who gets stuck if the cycle breaks. Anthropic's Blackstone chip financing and its lowered IPO valuation hopes show the strain in more than one place.
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🚨 Anthropic sets aside 5% of its shares for a public benefit fund
The FT reports the stake goes to a fund built around Anthropic's public benefit mission. The company is already a Public Benefit Corporation, so this puts actual equity behind the label.
Shares only, though. Nothing here gives the public a vote on how the models get built, and 5% of a company with IPO talk in the air is still a very large number.
The FT reports the stake goes to a fund built around Anthropic's public benefit mission. The company is already a Public Benefit Corporation, so this puts actual equity behind the label.
Shares only, though. Nothing here gives the public a vote on how the models get built, and 5% of a company with IPO talk in the air is still a very large number.
🤖 Epoch AI gave six models its own real work. None could replace the staff.
Epoch tested them on tasks like graphic generation and research design, graded against its employees' standards. Claude Fable 5.1 and GPT-6 Astra lead and are reliable on well-defined tasks. Open-weight models trail, even on those.
They miss implicit conventions like house visual style and what the audience cares about. They can spot promising research directions but lack the judgment to follow through.
Epoch tested them on tasks like graphic generation and research design, graded against its employees' standards. Claude Fable 5.1 and GPT-6 Astra lead and are reliable on well-defined tasks. Open-weight models trail, even on those.
They miss implicit conventions like house visual style and what the audience cares about. They can spot promising research directions but lack the judgment to follow through.
Epoch AI
Can AI automate Epoch?
Frontier models can handle well-defined tasks reliably, but fail in the more open-ended aspects that prevent full work automation. Explore Epoch AI's Automation Reports: realistic, open-ended tasks taken directly from our work, manually graded by our own…
🤖 Mistral's first non-language model is a time-series forecaster that runs on a CPU
Timestral ships in four sizes, 5M to 209M params, with probabilistic multivariate forecasts and covariate support. Mistral says the 28M version beats Chronos-2 (about 4x larger) on GIFT-Eval and TIME, and the 209M beats TimesFM-3 and Falcon-2.0, all on Mistral's own benchmark runs.
Timestral ships in four sizes, 5M to 209M params, with probabilistic multivariate forecasts and covariate support. Mistral says the 28M version beats Chronos-2 (about 4x larger) on GIFT-Eval and TIME, and the 209M beats TimesFM-3 and Falcon-2.0, all on Mistral's own benchmark runs.
Mistral
Timestral: Mistral's time-series foundation models | Mistral
State-of-the-art probabilistic forecasting in four sizes (5M–209M params), CPU-efficient, zero-shot ready.
🚨 Stripe is buying OpenRouter for $7.5B, and a payments company now owns the model traffic cop
Stripe will acquire the routing layer that sends one API call to hundreds of LLMs. Agents that pick models and pay for them on their own need exactly that pipe.
I haven't seen terms beyond the price, and the deal hasn't closed.
Stripe will acquire the routing layer that sends one API call to hundreds of LLMs. Agents that pick models and pay for them on their own need exactly that pipe.
I haven't seen terms beyond the price, and the deal hasn't closed.
Startup Fortune
Stripe will pay $7.5 billion for OpenRouter, the AI model traffic cop - Startup Fortune
Stripe agreed to buy AI model router OpenRouter for $7.5 billion, per the New York Times, after outbidding Databricks and beating its May valuation 6x.
🚨 MiniMax M3.1 Flash costs $0.15 in and $0.60 out per 1M tokens, and MiniMax says agent costs drop 70%
MiniMax says the Flash tier hits 73.7% on DeepSWE v1.1 and 82% on CyberGym, with 200+ tokens/sec output. The 70% cut is versus its own predecessor, and the benchmark numbers are all MiniMax's.
MiniMax says the Flash tier hits 73.7% on DeepSWE v1.1 and 82% on CyberGym, with 200+ tokens/sec output. The 70% cut is versus its own predecessor, and the benchmark numbers are all MiniMax's.
MiniMax
MiniMax M3.1 Flash: Redefining Agent Performance and Cost - MiniMax Research
Today, we officially roll out MiniMax M3.1 Flash. As a next-generation Flash model, M3.1 Flash delivers a generational leap in agentic tasks, coding, Computer Use and cybersecurity, while making online inference nearly three times faster and reducing usage…
⚡️ Inception's Mercury 3 hits 1,000+ tokens/sec on Blackwell GPUs, and it's a diffusion LLM
Inception launched it with a 1M-token context, up from 260K. It claims a win over GPT-6 Luna and Claude Haiku 5.5 at matched reasoning effort, running 4-8x faster.
Price is $0.20 in and $0.70 out per million tokens, half off at launch. Inception's own DeepSWE score is 46% versus Haiku's 52%.
Inception launched it with a 1M-token context, up from 260K. It claims a win over GPT-6 Luna and Claude Haiku 5.5 at matched reasoning effort, running 4-8x faster.
Price is $0.20 in and $0.70 out per million tokens, half off at launch. Inception's own DeepSWE score is 46% versus Haiku's 52%.
www.inceptionlabs.ai
Diffusion at Scale: Introducing Mercury 3 – Inception
Mercury 3 is the most capable diffusion LLM released to date. It outperforms GPT-6 Luna and Claude Haiku 5.5 while running 4–8x faster at 1,000+ tokens per second.
🚨 DHS bans DeepSeek across U.S. civilian agencies, and self-hosting doesn't get you out
The order also covers third-party products built on DeepSeek implementations. So open weights running inside an agency's own walls count too.
The stated reasons are PII collection, fingerprinting, PRC legal access to company servers, and critical flaws in the iOS app.
The order also covers third-party products built on DeepSeek implementations. So open weights running inside an agency's own walls count too.
The stated reasons are PII collection, fingerprinting, PRC legal access to company servers, and critical flaws in the iOS app.
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🚨 Tenstorrent raises $1.5B at a $6.2B valuation, and Nvidia's challengers keep getting funded
Jim Keller's RISC-V chip shop announced a Series E to push its Wormhole and Blackhole accelerators. The pitch is open designs and cheaper silicon for people who can't get Nvidia allocation, and investors are still buying it even with AI infrastructure debt piling up elsewhere.
Jim Keller's RISC-V chip shop announced a Series E to push its Wormhole and Blackhole accelerators. The pitch is open designs and cheaper silicon for people who can't get Nvidia allocation, and investors are still buying it even with AI infrastructure debt piling up elsewhere.
Tenstorrent
Tenstorrent Announces a $1.5B Series E at a $6.2B valuation | Tenstorrent
The equity raise will fund volume manufacturing and global commercial expansion as chip designers, sovereign players, and inference platforms move to own their AI compute.