LLMilestonesA milestone timeline of AI and large language models

Act IV · Multimodal, open source catches up

PaperGoogle DeepMind / UC Berkeley

Scaling test-time compute optimally

Showed that spending compute wisely at inference time can beat a much larger model.

14×larger model outperformed on some problems

Why it matters

Gave reasoning models a systematic footing: rather than only making models bigger, let them think longer.

Built on

Chain-of-Thought

Source: arxiv.org ↗

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