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Exploring Capacity Density in Large Language Models
This chapter explores the Densing Law of large language models (LLMs), emphasizing capacity density as a crucial metric for assessing performance. It discusses trends in model sizes, improvements in open-source capabilities, and the implications of optimization and compression techniques for AI efficiency.
Our 192nd episode with a summary and discussion of last week's* big AI news!
*and sometimes last last week's
Note: this one was recorded on 12/04 , so the news is a bit outdated...
Hosted by Andrey Kurenkov and Jeremie Harris.
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