172: Transformers and Large Language Models
Programming Throwdown
00:00
Evolution and Challenges in Scaling Language Models
The chapter explores the evolution of large language models, discussing challenges faced by previous models like recurrent neural networks and LSTMs. It emphasizes the importance of stability in training and scalability in current models while highlighting the limitations and potential advancements in the field of machine learning. The conversation also addresses the need for more sophisticated models and the enduring importance of human problem-solving skills despite advancements in AI.
Transcript
Play full episode
