A naukri.com initiative
Medium
1d
130
Semantic Gravity: How the Brain's Power Law Could Reshape AI Reasoning
- Large Language Models (LLMs) excel at patterns but lack inherent sense of significance, leading to wide yet often shallow reasoning.
- Neuroscience reveals brain's 'neural avalanches' follow a power law, with small events common and large events rare, optimized for insights.
- Semantic Information Mathematics (SIM) aims to quantify coherence and significance of ideas through V, S, and E components with tunable weights.
- Proposed model combines brain's power law with SIM to create AI reasoning based on semantic gravity, overcoming mere probability.
- Introducing Semantic Mass as a measure of idea complexity, the model selects outputs based on Semantic Coherence and power-law filtered mass.
- Resulting AI prioritizes significant ideas, simulates 'aha' moments, and fosters creativity through its selection mechanism.
- This model could enhance LLMs by emphasizing significance over probability, enabling the discovery of profound and meaningful insights.
- Understanding semantic gravity offers a path for AI to transcend pattern-matching and engage with the weight and depth of human language.
- It represents a shift towards AI models that uncover rare, valuable ideas within human knowledge, going beyond mere echo chambers.
Read Full Article
7 Likes
For uninterrupted reading, download the app