Can you take the cheapest open model from a frontier lab & beat closed models on the hardest long range tasks? Yep Our open adaptive intelligence system Zenith ramps DeepSeek v4.1 Flash past GPT 5.6 Sol to the frontier 🚀 h/t Opus 5.5 for making the video in like 2 mins 😮‍💨

This film cost $29,575 and took 10 days to make. AI ≠ Cheap Our Nexus feature will still cost millions next year. But it'll look like a $200M film. I have a Claude skill you can copy that makes this easy. Full process and Dreamina prompts below👇🏼🧵

I've attempted to map everything in oncology in a public website and open source repo for all. The site is trying to get all cancers, products, technologies, bottlenecks, people, startup opportunities with 1000+ ideas for upgrading the field. If you have a loved one with cancer and you are technical or can engineer, go take a look, file improvement requests or bugs or help with the open repo and make this the best open and free info resource for individuals, researchers and educational use. This should save people time, aid AI oncology projects and generate positive action. If you are not technical just complain in this thread about broken or annoying or things you want and I'll fix them live. Some of the interesting pages: Treatments: A gallery of the molecules being used And targets: The technologies in oncology: 1100 ideas for helping oncology: Bottlenecks on oncology: Open questions (LETS GO RESEARCH PEOPLE) Startup requests (LETS GO STARTUP PEOPLE) Mechanics of cancer: Battlefronts: Isotope supply: Key papers: Pipeline funnels: Cancer by type: Institutional rankings: The startups: Heros and heroines : Key medical people: Here is the project roadmap: Models and data sets: There are other views as well, take a browse. Try making a PR if you have an upgrade to this on the repo here: If you are biologically/medically minded and something is wrong, file a bug as well or say on the thread and we will get it fixed live. If this is a useful project star the repo and help get it calibrated. I've tried to add some other languages but I cannot speak them so tell me if that doesnt work well. I believe we will crack oncology and having total information dominance is key to the problem. Let the feedback flow!

Nearly half a year of silence. We spent it studying one problem: how far RL can scale. MiMo-V2.6 is in the middle of its RL run right now. Three things we scaled: compute (~2B tokens per step, 1568 prompts × 16 rollouts, fully async), environments and harnesses (multi-task agentic RL, mixed across multiple harnesses in one run), and grader compute (agentic in-group credit assignment, with test-case and rubric-based rewards). We'll open-source the details piece by piece over the coming weeks. Streaming the run:

Access to AI is not the same as ownership. A Champion is a locally owned AI institution, built for its country and owned by the people it serves. Every nation should have a stake in the intelligence shaping its future.

I write on the virtues of swarms and some suggestions on how to align AI with values There is a small bit of math and a small bit of Aristotle in this, don't let that discourage you! Feedback as always welcome. Prior blog:

Today @Brendan_McCord and I are launching Cosmos Ventures. AI is overturning assumptions society has organized itself around for centuries. The models keep getting better, but no level of capability can tell us what kind of society we should make with them. We need a new class of founders to build what comes next. Instead of only “building what people want” and iterating their way to product-market fit, these founders start from the question of how we should live together. They build new institutions that set the standards for how entire industries operate. They combine a philosophical vision of the society they’re building toward with the technical ability to realize it. We call them philosopher-builders. Immanuel Kant gave the Enlightenment its motto: Sapere aude. Dare to know. The AI age demands another. Condere aude. Dare to found. 🫡

Fun story: I had dinner with Steve Bannon once (think ~2018) and asked him about why he was really so anti-China. Can remember him saying it was primarily driven by his fears around Chinese AI and how it must be stopped (!)

$20M Raised. 7 M&A’s completed in 12 months. Investors include Expa, Coinbase Ventures, and Tenet Fund. 825 million users impacted. You have probably used us already. We help your favorite fintechs move money to the rest of the world.

This is actually a big deal, you can now spin up Mac VMs with Devin. That means if you want to build and test iOS apps you can do so completely end to end from your slack or web interface. One of the other big customer use cases is if someone reports a mobile app issue Devin can automatically reproduce, fix, and send you proof of the issue, demo of it working and of course a working PR

So @deepseek_ai v4.1 Flash I estimate cost $10m to train, 100x less than GPT-6 Astra. It also costs 100x less to run and scores about the same on everyday design and other benchmarks What's the bull case for the frontier AI labs once the open source models are competent enough

One point that people aren't discussing re @DarioAmodei's essay. In 2016, DeepMind brought in third-party evaluators to monitor its AI health work. The result was messy. It's a cautionary tale. Gift link to my latest in the NYT.