• September 2, 2025
Entropy-Aware Training: Building Self-Regulating AI

Entropy-aware training leverages information theory to regulate uncertainty in AI. By monitoring and minimizing entropy, models become more stable, generalizable, and trustworthy. Verified use…

  • September 1, 2025
Cognitive Black Holes: Preventing AI Collapse

Artificial intelligence faces a hidden threat: cognitive black holes. When models are trained on their own outputs, they spiral into collapse—producing distorted, self-referential, and…

  • August 29, 2025
JEPA: A Predictive Alternative to Generative AI

JEPA, or Joint Embedding Predictive Architecture, is a new self-supervised learning framework that predicts abstract representations instead of generating raw data. Proposed by Yann…