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Cognitive Parsimony Theory — Lumen Labs

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Today’s most advanced AI systems — large language models, vision transformers, multimodal architectures — are extraordinarily capable within their training distribution. They can draft legal briefs, generate photorealistic images, and beat grandmasters at chess. Yet they fail in ways that no conscious being would: they cannot reliably generalize to novel situations, they lack the ability to know what they don’t know, and they process the world through statistical correlation rather than understanding. We believe this gap is not merely an engineering problem. It is a theoretical one. Current AI architectures lack a formal account of what it means to efficiently process experience — the very thing that consciousness appears to do. Without such an account, scaling alone will not produce general intelligence. This white paper introduces Cognitive Parsimony Theory (CPT), a mathematical framework that defines consciousness as the optimization of predictive efficiency. The core quantity is th

Cognitive Parsimony Theory — Lumen Labs Cognitive Parsimony Theory Why Consciousness is a Constrained Optimization Problem written by Harry Gandhi | February 20, 2026 Created with the assistance of Claude (Anthropic) Abstract Today’s most advanced AI systems — large language models, vision transformers, multimodal architectures — are extraordinarily capable within their training distribution. They can draft legal briefs, generate photorealistic images, and beat grandmasters at chess. Yet they fail in ways that no conscious being would: they cannot reli

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