Summary of A Mathematical Framework Of Intelligence and Consciousness Based on Riemannian Geometry, by Meng Lu
A mathematical framework of intelligence and consciousness based on Riemannian Geometry
by Meng Lu
First submitted to arxiv on: 2 Jul 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Differential Geometry (math.DG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper proposes a mathematical framework based on Riemannian geometry to describe the structure and dynamics of intelligence and consciousness. Intelligence is conceptualized as tokens embedded in a high-dimensional space, with learned token embeddings capturing interconnections across various scenarios and tasks. Thought flow is depicted as sequential activation of tokens along geodesics within these manifolds. The framework integrates geometric concepts to offer a unified, mathematically framework for describing intelligence and consciousness. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper tries to understand how our brains work by using special math called Riemannian geometry. It says that our thoughts are like little tokens floating in a big space, and these tokens get connected as we learn new things. The way we think is like following paths through this space, and our brain’s “consciousness” helps us adjust those paths so we can learn and remember. This idea might help us understand how both human brains and artificial intelligence work. |
Keywords
» Artificial intelligence » Token
