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Autoresearch from @karpathy runs 1 experiment at a time. We gave it 16 GPUs and let it run them in parallel.
8 hours. 910 experiments. 9× faster to the same best result.
The most surprising part: the agent had access to both H100s and H200s. Without being told, it noticed H200s
Karpathy's Autoresearch is bottlenecked by a single GPU. We removed the bottleneck.
We gave the agent access to our K8s cluster with H100s and H200s and let it provision its own GPUs. Over 8 hours:
• ~910 experiments instead of ~96 sequentially
• Discovered that scaling model
