Pre-training Insights
Pre-training is likened to the imitation learning phase of AlphaGo, where a neural network acquires foundational skills. This process elevates the model from zero to a competent level, making it powerful. Post-training, on the other hand, focuses on reinforcing good behaviors, akin to AlphaGo's reinforcement learning phase, enhancing the model's performance in conversational contexts. The underlying strategies for training both AlphaGo and Gemini share remarkable similarities.In this clip
From this podcast
Training Data
Reflection AI’s Misha Laskin on the AlphaGo Moment for LLMs | Training Data
Related Questions
How did AlphaGo's learning process through self-play lead to the development of its own strategies in the episode Michael Littman: Reinforcement Learning and the Future of AI | Lex Fridman Podcast #144 and the clip AlphaGo Insights?
How did AlphaGo's learning process through self-play lead to the development of its own strategies in the episode Michael Littman: Reinforcement Learning and the Future of AI | Lex Fridman Podcast #144 and the clip AlphaGo Insights?