Book : https://leanpub.com/sst-4-agenticai

How to represent knowledge for LLMs and build memory for agents, I discovered Mark's work on semantic spacetimes. It's more of a theoretical framework from someone who came from physics. But actually, jumping to knowledge representation and reasoning, and trying to answer the question of how to build dynamic and complex systems—semantic spacetimes and promise theories are crucial for the future of agentic systems, in my belief.

The semantic spacetime approach gives us answers on how to organize better memory and how to have better knowledge representation that could be understood quite well by LLMs. Vector embeddings actually create a lot of challenges—some spaces and some relations in vector embeddings simply don't exist. We all have this problem where "love my wife " and "hate my wife" while actually quite distant in practice, and also time and dynamics matter