Artificial intelligence is evolving rapidly, and AI hardware advancements are revolutionizing training and inference for large language models.This transition reshapes how businesses and researchers approach compute-intensive tasks, such as training and inference for large language models. As the demand for AI capabilities grows, chip design and system architecture innovations are driving unprecedented performance gains, efficiency and scalability, according to Andrew Feldman (pictured), co-founder and chief executive officer of Cerebras Systems Inc.Cerebras Systems’ Andrew Feldman talks to theCUBE about AI hardware advancements