Researchers Reveal LLMs Rely on Context for Knowledge, Lacking Internal State
| Source: Mastodon | Original article
LLMs are stateless, relying on context for knowledge. This limits their capabilities compared to humans.
Today's revelation that Large Language Models (LLMs) are stateless has significant implications for the field of artificial intelligence. This means that all knowledge is conveyed through context, and LLMs lack the ability to retain information like humans do. As we previously discussed, the concept of feeding vast amounts of context into LLMs has been explored, particularly in relation to VibeCoding and LLM orchestration systems.
The fact that humans carry a lifetime's worth of context, equivalent to many terabytes of data, highlights the enormous potential for LLMs if they could be fed such vast amounts of experience. This could drastically reduce the cost of using LLMs compared to human labor. The cost savings would be substantial, making LLMs an even more attractive option for businesses and organizations.
As researchers and developers continue to push the boundaries of LLM capabilities, the next step will be to explore innovative methods for feeding context into these models. This could involve advancements in data storage, processing power, or novel approaches to programming LLMs. The potential for LLMs to revolutionize industries and transform the way we work is vast, and this latest discovery is sure to accelerate progress in the field.
Sources
Back to AIPULSEN