Future of LLMs
There is significant potential for improvement in language models, particularly in multi-hop tool use and integration with external systems. As models advance, the ability to assess their quality may become more nuanced, moving beyond simplistic human comparisons. Insights reveal that even minor changes can greatly influence perceptions of model effectiveness, highlighting the need for more robust evaluation methods that align with real-world business applications.In this clip
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Machine Learning Street Talk (MLST)
Cohere co-founder Nick Frosst on building LLM apps for business
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