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Our WeatherNext 2 AI model from @GoogleDeepMind and @GoogleResearch can predict tropical cyclones with an extra day of lead time. Now, we’re open sourcing the model. Published in @Nature, Google researchers demonstrate how it delivers roughly a decade's worth of weather forecasting progress in a single jump. Here's how it works:
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📣 Kimi K3 is now available in GitHub Copilot for @code! Try Kimi Moonshot's latest open-weight model for agentic coding, now hosted by @FireworksAI_HQ. 📖 Learn more:
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Predicting cyclones accurately can help save lives - and every hour of lead time counts. Published in @Nature, our AI model WeatherNext achieves state-of-the-art accuracy in forecasting a storm’s track and intensity, giving us a critical extra 24 hours to prepare on average. 🧵
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7 days of unlimited Seedance 2.5 for everyone joining today. The most realistic and production-ready video model. 7 DAYS of ZERO credit cost to generate. Deeper shadows, better acting performances, next-level physics, native voice generation. 7-day unlimited access starts August 7.
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Tesla Self-Driving 14.2.2.6 in Amsterdam at night The diversity of driving scenarios this model can handle blows my mind
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We tried using Meta's new Muse Code agent, but it has a bug that doesn't let it sign in from a docker container. So we did a fun experiment: Meta claims Muse Spark 1.2 was co-trained with their Muse agent harness. So we extracted instructions from their system prompt and added them to the Cline harness. TL;DR of this special prompting: - Trust source code over the user prompt, so read every call site and existing tests before starting the task - Weigh edge and error cases as heavily as the happy path - Always reproduce the bug before fixing - Don't trust the first passing test suite, and verify suspicious looking half-baked tests - Never stop at just editing, keep working until the change is verified complete. We then asked this modified harness to fix a real bug from our repo, and compared the results to the original Cline agent harness. Results: - Used 2.7x fewer tokens (19.7M → 7.2M) - Finished 2x faster (49min → 24min) - Cost 2.4x less ($7.69 → $3.25) Same Muse Spark 1.2 model, same task, only the prompting changed. Incredible how much of a performance gain Meta was able to achieve training it on these special instructions!
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BREAKING: MiniMax H3 by @MiniMax_AI is 1st across 3 Video categories (Multi-Image to Video, Image to Video, and Video Editing) on Design Arena. MiniMax H3’s performance in Video Arena puts it ahead of other top performing models like Seedance 2.0 by @BytePlusGlobal, Grok Imagine Video 1.5 Preview by @SpaceXAI, and Gemini Omni Flash by @GoogleDeepMind. This marks another category to be led by open-weight models, following Kimi K3’s first place in our coding categories. Congratulations to the @MiniMax_AI team for establishing a new SOTA in video generation!
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Two weeks ago, I resigned from OpenAI to join Conduit as a founding researcher, where we're training models to non-invasively read the human mind. I've written some thoughts about what telepathy could look like by 2035 and how to get there:
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Introducing the GOAT plan 🐐 Command Code GOAT plan is the best low-cost coding plan on the market today. - $10/mo to get $70 credits. 7x what you pay - 30+ open weight and closed models $1 Go got you started. GOAT gets you shipping. Subscribe — be a GOAT.
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Announcing Discovery Loop! I am very excited to announce that, along with my longtime friends and collaborators @Sanjay_Ghemawat, @OriolVinyalsML and @quocleix, we are founding Discovery Loop (@DiscoLoopAI), a Public Benefit Corporation whose mission is to automate machine learning, science, and engineering to accelerate discoveries and progress. The four of us have worked together for 14 to 30 years, and have helped build some of the world’s most used products, infrastructure and AI models, and we’re excited to turn our attention to this ambitious endeavor. ♾ Learn more at:
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