For the last 72 hours since ml-intern launched we have had over 500+ autonomous AI research projects running on the Space at all times. Some…

For the last 72 hours since ml-intern launched we have had over 500+ autonomous AI research projects running on the Space at all times. Some insane ones I saw: 1. A new AI paradigm from scratch — trying to replace transformers with a reasoning architecture based on energy minimization, binary sparse address tables and circular convolution binding. No GPU, no gradients, no training data — pure bitwise operations. Years of research done in 2 days. https://huggingface.co/Harry00/MLE-Morpho-Logic-Engine 2. Someone took LoopLM (ByteDance's recurrent depth transformer with shared layers and infinite depth via looping) and crossed it with BitNet b1.58 (ternary 1.58-bit weights). The result: a model that's both infinitely deep AND uses almost no memory per parameter. 3. Designing a new attention mechanism modeled on the thalamo-cortical circuit in the human brain. Pulling from 2025/2026 research out of MIT, Harvard, and UF. The thalamus gates what information reaches the cortex. They're building a learnable gate that mimics this for transformer attention heads, combined with EEG datasets and a reinforcement learning loop. https://huggingface.co/spaces/daniel8919/limbic-reasoning-agent The use cases people bring are cooler and more impressive than anything we imagined when we built this. Introducing ml-intern, the agent that just automated the post-training team @huggingface It's an open-source implementation of the real research loop that our ML researchers do every day. You give it a prompt, it researches papers, goes through citations, implements ideas in GPU …

Source: Clem Delangue (X) | 2026-04-24