Mixture-of-Experts and Trends in Large-Scale Language Modeling with Irwan Bello - #569

This article from Practical AI discusses Irwan Bello's work on sparse expert models, particularly his paper "Designing Effective Sparse Expert Models." The conversation covers mixture of experts (MoE) techniques, their scalability, and applications beyond NLP. The discussion also touches upon Irwan's research interests in alignment and retrieval, including instruction tuning and direct alignment. The article provides a glimpse into the design considerations for building large language models and highlights emerging research areas within the field of AI.

• •Mixture of Experts (MoE) is a key technique for building large language models.
• •The article explores the scalability and applicability of MoE beyond NLP.
• •Alignment and retrieval are important research areas, including instruction tuning and direct alignment.