Understanding Mixture of Experts in Large Language Models

Understanding Mixture of Experts in Large Language Models

Explore the concept of Mixture of Experts (MoE) in this 28-minute video lecture. Delve into the rationale behind MoE, its training process, and potential challenges. Learn about techniques like adding noise during training and adjusting loss functions for router evenness. Examine the applicability of MoE for large language models on laptops and its potential benefits for major AI companies. Investigate the binary tree MoE (fast feed forward) approach and compare performance data between GPT, MoE, and FFF models. Analyze the inference speed improvements with binary tree MoE and evaluate the overall viability of MoE in various contexts. Gain insights into why large companies might adopt MoE technology for their AI systems.