hardmaru
@hardmaru
Building Collective Intelligence @SakanaAILabs 🧠
The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery 👩🔬 arxiv.org/abs/2408.06292 It’s common for AI researchers to joke amongst themselves that “now all we need to do is figure out how to make AI write the papers for us!” but I think we’re now getting there!
Introducing The AI Scientist: The world’s first AI system for automating scientific research and open-ended discovery! sakana.ai/ai-scientist/ From ideation, writing code, running experiments and summarizing results, to writing entire papers and conducting peer-review, The AI…
Nice to see a figure from our 2018 paper about World Models is still being used in 2025. worldmodels.github.io arxiv.org/abs/1803.10122
Models and tools that worth your attention in 2025: ▪️ Reasoning Models ▪️ World Models ▪️ Cosmos World Foundation Model Platform by @nvidia ▪️ Mixture-of-Mamba ▪️ AlphaEvolve and Codex Explore detailed overviews of these spotlights in one place -> turingpost.com/p/models-recap…
1 decade ago: Reinforcement Learning Prompt Engineer in Sec. 5.3 of «Learning to Think …» [2]. Adaptive Chain of Thought! An RL net learns to query another net for abstract reasoning & decision making. Going beyond the 1990 World Model for millisecond-by-millisecond planning…
先日の勉強会の資料が公開されました！🙌 オープンエンドな探索と知識発見 speakerdeck.com/sakana_ai/2025…
Every ML Engineer’s dream loss curve: “Kimi K2 was pre-trained on 15.5T tokens using MuonClip with zero training spike, demonstrating MuonClip as a robust solution for stable, large-scale LLM training.” arxiv.org/abs/2502.16982
🚀 Hello, Kimi K2! Open-Source Agentic Model! 🔹 1T total / 32B active MoE model 🔹 SOTA on SWE Bench Verified, Tau2 & AceBench among open models 🔹Strong in coding and agentic tasks 🐤 Multimodal & thought-mode not supported for now With Kimi K2, advanced agentic intelligence…
Neural Network GOATs 🚀🚀
Congrats to @NVIDIA, the first public $4T company! Today, compute is 100000x cheaper, and $NVDA 4000x more valuable than in the 1990s when we worked on unleashing the true potential of neural networks. Thanks to Jensen Huang (see image) for generously funding our research 🚀