LLMs+ โ
The article discusses the next evolution of large language models, termed "LLMs+", which aim to tackle complex problems requiring extended autonomous reasoning. Key advances include mixture-of-experts architectures for efficiency, alternative neural network designs like diffusion models, expanded context windows up to a million tokens, and recursive LLM approaches that break tasks into smaller chunks. These improvements address fundamental challenges in making LLMs more reliable and capable of handling long, difficult tasks that currently cause models to lose focus or accuracy.
The next big thing after LLMs is more LLMs. But better.
Multiple LLMs processing smaller pieces of information seem to be far more reliable for long, hard tasks.