These startups are chasing the next big thing in LLMs

The article discusses the limitations of the Transformer architecture and highlights startups exploring alternatives like sparse attention, rolling-summary memory, diffusion-based text generation, and worm-brain-inspired networks. These new approaches aim to improve efficiency, reduce costs, and potentially overcome current bottlenecks in AI reasoning.