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.
Palantir CEO thinks governments might nationalize AI
，这一点在爱思助手下载最新版本中也有详细论述
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This article originally appeared on Engadget at https://www.engadget.com/computing/accessories/apples-new-studio-display-xdr-monitor-has-limited-functionality-on-older-silicon-macs-082212069.html?src=rss
And yet dependence is reinforced daily through routine decisions. Public institutions continue to default to foreign platforms. Procurement rules favour incumbents. Civil servants upload public data into non-European systems. None of this is inevitable. It is the result of choices.