
From Prompts to Policies: How RL Builds Better AI Agents with Mahesh Sathiamoorthy - #731
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
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Exploring Compute Costs: Reinforcement Learning vs. Supervised Fine-Tuning
This chapter examines the contrasting computational requirements and costs associated with Reinforcement Learning and Supervised Fine-Tuning. It also discusses optimization strategies to make Reinforcement Learning more feasible for enterprise applications, especially in complex problem-solving scenarios.
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