The Evolution of Transformer Models

Recent advancements in AI software, particularly from OpenAI, highlight the evolution of transformer models, emphasizing the need for increased computational resources for inference rather than just training. The new model introduced uses reinforcement learning and multi-layered reasoning, resulting in a more complex process that may sacrifice speed for depth of analysis. Experts note that the demand for inference compute will soar as these models become more capable, leading to a gap in current silicon architecture that needs to be addressed. This raises concerns about the ability of existing semiconductor technologies to keep pace with the rapid advancements in AI software, suggesting that significant innovations will be necessary in the coming years.