Last week we released NanoGPT Slowrun , an open repo for data-efficient learning algorithms. The rules are simple: train on 100M tokens from FineWeb, use as much compute as you want, lowest validation loss wins. Improvements are submitted as PRs to the repo and merged if they lower val loss. The constraint is the inverse of speedruns like modded-nanogpt , which optimize wall-clock time. Those benchmarks have been hugely productive, but optimizing for speed filters out expensive ideas: heavy regularization, second-order optimizers, gradient descent alternatives. Slowrun is built for exactly those ideas.
AI is already reorganizing companies’ org charts. Anthropic’s Boris Cherny, the creator of Claude Code, recently said the title “software engineer”—once a foundational entry-level position at every Big Tech company—could be extinct by the end of 2026. Cherny hasn’t coded since November, and has completely given over his time-intensive coding tasks to Claude.
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Mellanox → NVIDIA
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