#215 - Runway games, Meta Superintelligence, ERNIE 4.5, Adaptive Tree Search
Last Week in AI
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Exploration vs. Exploitation in AI
This chapter explores the balance between exploration and exploitation in machine learning, emphasizing Adaptive Branching Tree Search and innovative methods like Thomson's sampling. It discusses advancements in AI, especially concerning Monte Carlo Tree Search adaptations for large language models (LLMs) and the need for improved benchmarks to assess AI's effectiveness in replicating scientific discoveries. Additionally, it reviews recent performance metrics of various models and highlights the potential implications for future AI developments.
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