Muhang Xie @Midoria_7

Incoming PhD in SII & GAIR Shanghai Joined March 2026

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Pengfei Liu @stefan_fee

6 months ago

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-E… 📄 Paper: arxiv.org/abs/2603.29640 (1/8) ⭐ Star it. Fork it. Point it at your hardest problem.

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Muhang Xie @Midoria_7

6 months ago

Let’s build pre-training science together!

Yi wei Qin @QinYi88814

6 months ago

🚨 We can download models, but not see how they were built. Introducing daVinci-LLM: most transparent LLM pretraining project. 🔓 Open source: model weights, data pipeline, training process, ablations. 🎯 3B model matching 7B performance 🔗 Report: huggingface.co/papers/2603.27… (1/7)

Muhang Xie @Midoria_7

Pengfei Liu @stefan_fee

Muhang Xie @Midoria_7

Yi wei Qin @QinYi88814

Weixian Xu @WeixianXu

Ethan Chern @ethanchern

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