
Third article in the From Instinct to Intent™ series. $5 billion raised in 90 days across LeCun (world models), Altman/Amodei (scaled LLMs), and Sutskever (new research). All focused on building better AI engines. This article argues that the gap between human intent and machine execution is architecture-agnostic and survives regardless of which engine wins. Includes analysis of the Anthropic/Pentagon standoff as a real-world proof point, evidence from 10,000+ developers showing the intent gap grows with AI capability, and a historical perspective on how humans have built intent layers for each other across millennia.
From Instinct to Intent, architecture-agnostic, AI safety, large language models, world models, intent layer, human-AI interaction, AI governance
From Instinct to Intent, architecture-agnostic, AI safety, large language models, world models, intent layer, human-AI interaction, AI governance
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