Can AI accelerate AI itself? Let's look at what actually happened!!! AI autonomously discovered a new RL algorithm, invented 100+ novel architectures, and evolved a data curation strategy — each one outperforming the best human-designed counterparts: 🤖 RL algorithm design — discovered novel optimization mechanisms that beat human-designed GRPO by +12.5 pts on AMC 🧠 Neural architecture search — invented 100+ new architectures, surpassing Mamba, GatedDeltaNet, and more by +0.97 pts over SOTA 📦 Pretraining data curation — evolved a pipeline that outperforms FineWeb-Edu, DCLM, and Nemotron-CC by +18 pts on MMLU 🧬 Drug-target interaction — discovered a new architecture that outperforms all prior human-designed methods by +6.94 AUROC These aren't toy demos. These are frontier-level results — produced without a human in the loop. This is ASI-Evolve: an open-source agentic framework that closes the loop between knowledge → hypothesis → experiment → analysis, and repeats it autonomously until it finds something that works. We built it for AI research. But the loop doesn't care about the domain. A year ago, we made a prediction: Scale computation → Scale scientific discovery. The world caught up faster than we expected. Which raises a question we can't stop thinking about — and we think you shouldn't either: In the post-AGI era, when AI generates breakthroughs faster than humanity can absorb them — when the rate of discovery permanently outpaces the rate of value conversion — what becomes the new scarcity? Not intelligence. Not data. Not compute. Something far more irreplaceable. We don't have the full answer. But we think it's worth asking — loudly, and together. 💻 Code: github.com/GAIR-NLP/ASI-Evol… 📄 Paper: arxiv.org/abs/2603.29640 (1/8) ⭐ Star it. Fork it. Point it at your hardest problem.

Seedance 2.0 is impressive. But it's closed-source! Introducing our daVinci-MagiHuman — a single-stream 15B Transformer trained from scratch that jointly generates video + audio. No cross-attention. No multi-stream branches. Just self-attention. ⚡ 5s 1080p video in 38s on a single H100 🏆 80% win rate vs Ovi 1.1 | 60.9% vs LTX 2.3 (2,000 human comparisons) 🌍 6 languages 📦 Fully open-source Speed by simplicity. By @SII_GAIR × @SandAI_HQ 📄 arxiv.org/abs/2603.21986 💻 github.com/GAIR-NLP/daVinci-… 🤗 huggingface.co/spaces/SII-GA…