RL Post-Training on Macs
July 2026Post-training an 8B MoE with GRPO on 14 consumer Macs and one B200, decoupled over R2; held-out pass@1 on agentic search more than doubled, from 29% to 63%
Post-training an 8B MoE with GRPO on 14 consumer Macs and one B200, decoupled over R2; held-out pass@1 on agentic search more than doubled, from 29% to 63%
Reducing blocking communication in DiLoCo by factoring synchronization into a non-blocking parameter mixing and a minimal blocking gradient mixing
We replicated Meta's full post-training pipeline on a single compute node with one researcher, matching Llama-3.2-1B-Instruct quality
A deep dive into our library built for fault-tolerant multi-party distributed training
Nesterov Method for Asynchronous Pipeline Parallel Optimization
Developing the true open-source AI
Two enormous, previously disparate fields converge and a path towards the largest models to ever be trained is opened
Collaborative Training of foundation models is closer to actualization than broadly understood. The popular view that low bandwidth node-to-node connections render this infeasible is incorrect