Toward Coherence-Driven Artificial Intelligence
The dominant paradigm in modern AI rests on a deceptively simple premise: intelligence emerges from minimizing prediction error across vast datasets. We train neural networks to be accurate, to match patterns, to reduce loss functions. Yet this approach, for all its empirical success, may be fundamentally misaligned with the nature of intelligence itself. Here is …
