Ep 44: Co-Founder of Together.AI Percy Liang on What’s Next in Research, Reaction to o1 and How AI will Change Simulation
Unsupervised Learning
From Prediction to Action: The Evolution of Agents
The evolution of artificial intelligence showcases a shift from traditional reinforcement learning techniques, exemplified by projects like AlphaGo, to a more agent-centric approach focused on long-term tasks and action-based learning. Current developments indicate that large language models are no longer just about predicting text; they are evolving into agents capable of taking actions within defined spaces. This paradigm shift allows these agents to gather experience over time, coupled with appropriate reward systems, enabling them to learn, iterate, and improve in complex tasks. Future advancements are likely to see increased deployment of AI agents in various applications, harnessing feedback mechanisms to enhance their effectiveness.
