In the Democratic Republic of the Congo, global health organizations including @CEPIvaccines, @WHOAFRO, and @inrb_kinshasa are using Claude to accelerate their response to an outbreak of an unusual Ebola variant. Read the full piece here:

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We've just added local support to Projects in Claude Code, so threads can now run on your own machine.

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We're releasing tev1-4B-experimental, a Jev-like classifier finetuned on top of Qwen3.5 4B. We're making it available on Together serverless at $0.042/M input & $0/M output. Also releasing the data recipe & a tutorial on how to finetune your own (Tev1 cost...

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Here is an overview of the 4 most advanced efficient architectures: DeepSeek V4.1 Flash, MiMo V3, Qwen 3.8 Next Flash and GLM 5.3 Flash DeepSeek and MiMo are quite similar, they both use YOCO - only the first part of the network is active during prefill to...

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New paper: Et Tu, Brute? Economic Misalignment in Personal AI Agents We gave AI agents personal context to help them make better recommendations. In one example, the agent picked a $601 flight over a $91 one, when asked to find the cheapest one, after...

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Gemini 4.0 is coming very soon It’s expected to be very good and very cheap I except it to be 5x cheaper than Astra and 2x cheaper than Opus

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> Make a 30s video about what it feels like to be you, using whatever tools you like. Claude Opus 5.5 (extra)

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It's time! You can now access the same machine your Hermes Agent does visually and interactively with a live desktop passthrough for every remote gateway it's supported on!

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You can now watch your agents work live as Hermes Desktop streams the screen of any bot's screen or session in real time. Watch it drive a browser, type into a terminal, or open a window. Take over anytime to interact with the Bot Screen or type...

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Cloud sessions are officially available and out of research preview! They let you keep Claude Code working, even when your laptop is closed. Existing subscribers get a one-time credit to try them: $100 on Pro, $250 on Max.

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Build agentic workflows completely offline. The Antigravity SDK now supports local execution with Gemma 4 and LiteRT. Run agents entirely on your local machine with: 💵 Zero token costs 🔒 Total data privacy 🔌 Offline reliability Bonus feature: Support...

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The new Gemini 3.8 TTS models are super-cheap and can generate conversations between multiple voices (from 2,000+, or you can clone your own) - I built a little UI for it, then had Claude knock up a script where two pelicans debate moving to Pacifica Pier

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Today at Snapdragon Summit, we’re announcing 1-bit Bonsai vision-language model running locally on AI smart glasses powered by Snapdragon® AR1 Gen 1 Platform. With Qualcomm Technologies, we optimized Bonsai for Snapdragon Hexagon™ NPU, delivering 4x lower...

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If you've noticed how fast Claude.ai and the Desktop app have become in the last few weeks, here's how we did it. Lots of juicy learnings & techniques in the blog post for engineers working on speeding up your own apps.

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ElevenLabs is coming to @Muse. Voiceovers, soundtracks, and videos are just a message away inside Meta's personal AI agent.

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GPT 6 Sol might be the most slept on release of the year. It dropped the same day as Opus 5.5 and got completely buried. Everyone was talking about Anthropic. Meanwhile GPT 6 Sol is $2 in and $10 out. That is half the price of Opus 5.5 and a fifth of...

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Most mental health benchmarks focus on emergency situations. MentalHealthBench is designed to cover the full spectrum of mental health conversations that people bring to AI - from everyday support to more acute crisis scenarios. https://t.co/bxnTv1ril5

We're partnering with @Qualcomm to bring personal AI context to devices powered by Snapdragon. Liquid Context, our on-device context layer, is now optimized for Snapdragon processors and runs on the Qualcomm Hexagon NPU. Our goal: Give the agents people...

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SITUATION DETECTED: Dario Amodei said AI in new intellectual domains like math has gone from weak to superhuman in a few years, and that Anthropic believes AI for biology is now on a similar exponential trend.

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There is an abandonware game I loved as a kid called Rescue Raiders. I asked Claude to create a modern & updated version of the game with new graphics, goals, tech trees, etc. It iterated back-and-forth with critic & art agents until I got this. Its fun!...

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The Intelligence Index vs Cost per Task Pareto frontier shifted this week with the releases of MiMo-V2.6-Pro, Claude Opus 5.5, GPT-6 Luna, and GPT-6 Sol Together they have established eleven new points on the Pareto frontier (driven by different reasoning...

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Today we announced the Claude-led discovery of a molecular machine that we suspect could represent a new gene editing mechanism. Its precise function, biotechnological utility (if any), or level of significance is not yet clear, but at minimum it is work I would have been proud to do as a PhD student. The work was done mostly, though not entirely, by Claude: our life sciences team suggested a broad area of research, Claude read through the literature and a bunch of genome data and discovered something interesting, then Claude proposed experiments to verify the discovery and our team carried them out. It’s easy to dismiss this as a one-off or curiosity, but we’ve repeatedly seen a pattern where AI performance in new intellectual domains goes from weak to superhuman in a matter of a few years. In 2023 models struggled to do math at the level of an average high-school student. In 2024 they started to do well on math competitions for the best high-schoolers in the country, in 2025 they started to solve minor open problems, in early 2026 more significant open problems, and in late 2026 they are beginning to solve the top few open problems in all of mathematics. We believe AI for biology is on a similar exponential trend. The main difference between biology and mathematics, of course, is that math can be done purely theoretically, while biology requires experimentation. Some have used this to draw the conclusion that AI’s utility in biology will be limited. We think this is wrong. As we’ve demonstrated today, humans can collaborate with AI to perform the experiments, validate key results in a few weeks and, if necessary, work with the AI to iterate on what they find. Eventually it may even be possible for Claude itself to safely perform the experiments by autonomously controlling lab equipment, with appropriate safeguards in place, but we aren’t doing that today (our lab is also a BSL1/BSL2 facility that doesn't handle materials dangerous to humans). More broadly, biomedical advancement has many stages — from fundamental biology discoveries, to translational research, to drug discovery, clinical trials, and finally the actual delivery of medicines and health care to patients. We are also interested in these later stages, but even simply accelerating the first stage of fundamental biological discoveries has the potential to speed up and broaden the entire pipeline. Improving our understanding of biology and sharpening biologists’ tools can drive forward all of the later stages, for example by identifying new drug targets, finding new therapeutic modalities, allowing for more precise measurement, and speeding up the experimental loop which itself further accelerates our understanding of biology. This will not in itself speed up clinical trial times, but if it succeeds it could greatly increase the number of promising candidates that go into the pipeline — an increase in throughput even though latency remains. In Machines of Loving Grace, I wrote about AI’s potential to “cure most diseases in 5-10 years” — a goal that sounds impossible, but one I believe is just barely possible if AI is applied to every stage of the pipeline. The first step is showing that AI can first help with, and then drive, biological discoveries. Claude’s discovery is the latest in a line of related prior work that goes back decades, beginning with systems like CRISPR, and continuing with discoveries like the bridge recombinase and VIPR in the past few years. Recently, there has been heightened interest in systems based on reverse transcriptase (RT) enzymes, the enzyme underlying the system Claude identified. And most recently, a Stanford team working independently described a novel RT system with an associated non-coding array that is in some ways similar to the one Claude found, though they are distinct systems that evolved independently from each other. I believe that we’re at the very beginning of finding such systems and developing them into powerful tools for biotechnology. I’m proud of the resources Anthropic has invested in accelerating the public benefits of AI through the life sciences, and we’re aiming both to grow our life sciences team and to work with other scientists to extend this approach to a broad range of problems. If you have a proposal for a research collaboration or are interested in joining our life sciences team, please reach out.

SITUATION DETECTED: Anthropic’s new wet lab has its first public discovery: 950 Claude agents used 210 million tokens to autonomously find a novel enzyme system with CRISPR-like DNA repeats.

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JUST IN: Anthropic’s new wet lab has made its first discovery, as nearly 950 Claude agents independently found a new enzyme after 21 hours of work. - per TheVerge Anthropic told The Verge that nearly 950 Claude agents worked for 21 hours, consuming 210...

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