Exploring Large Language Models with ChatGPT - #603
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
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Supervised Learning and Fine-Tuning in LLMs
This chapter investigates the role of supervised learning in training large language models such as ChatGPT, highlighting its importance in understanding natural language. It also clarifies the supportive function of Reinforcement Learning from Human Feedback (RLHF) and introduces Proximal Policy Optimization (PPO) as a method for improving model responses. Additionally, the chapter discusses the benefits of LLMs in translation systems and explores fine-tuning options, speculating on future enhancements for user-specific applications.
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