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Links From Todays Video:
https://arxiv.org/pdf/2408.03314
00:00 – Introduction and background on LLMs
02:15 – Test time compute explained
03:26 – Scaling model parameters strategy
04:48 – Scaling vs optimizing test time compute
05:53 – Key concepts from DeepMind research
06:39 – Verifier reward models
07:45 – Adaptive response updating
09:04 – Compute optimal scaling strategy
10:28 – Math benchmark for testing
11:30 – Palm 2 models used
12:36 – Core techniques tested
14:16 – Search methods used
15:05 – Results and comparisons
15:27 – OpenAI’s O1 model comparison
15:58 – Conclusion and future implication
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