Beidi Chen

Beidi Chen, a PhD candidate in Computer Science at Rice University, discusses groundbreaking research that challenges the dominance of GPUs in deep learning. The conversation dives into their innovative algorithmic approach, SLIDE, which uses locality-sensitive hashing to optimize extreme classification tasks. Chen highlights how randomized algorithms enhance computational efficiency, often outperforming conventional hardware solutions. The importance of collaboration and the evolution of machine learning systems are also key themes, showcasing a new path forward for AI development.