Unlocking AI’s Potential with Topological Phi (Φ)
At InductivityAI, we’re pioneering breakthroughs in AI with our innovative approach to measuring integrated information within neural networks. While debates on AI consciousness abound, we focus on the mathematical science behind it.
Key Highlights:
- Introducing the $O(N^3)$ Heuristic: Successfully computes Topological Phi (Φ), making it feasible to evaluate complex neural network architectures.
- LLM Diagnostics – The “Phi-Collapse”:
- Early Layers (0-2): Show high Φ-scores, indicating effective context integration.
- Deep Layers (3+): Experience a dramatic Φ-collapse, losing integrated information and fragmenting learning capabilities.
- Φ-Regularization: Our novel technique maximizes information integration during training, leading to the formation of structured concepts.
Join us in exploring these revolutionary findings through our public API! Test your attention matrices and gain insights like never before.
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