Future Language Models

Connor and Aravind discuss the future of language models, addressing the challenges of behavior cloning and the potential of pre-training models on vast amounts of data to improve data efficiency. Aravind explains how utilizing reward models and RLHEF can help overcome compounding errors in trajectories, highlighting the importance of generating infinite data for model training.