https://undark.org/2026/02/19/opinion-jagged-intelligence/ “we need to give models knowledge — rigidly described concepts and constraints, rules and relationships — that anchor their behavior to the realities of our world. To give AI models a human stock of knowledge, we need to rapidly build a public database of formal knowledge spanning a range of disciplines. Of course, the rules of math are clear; the workings of other fields — health care, law, economics, or education, say — are, in some ways, vastly more complex. This challenge is now within our reach, as the growth of companies such as Scale AI , which provides high-quality data for training AI models, points to the emergence of a new profession — one that translates human expertise into machine-readable form and, in doing so, shapes not just what AI can do, but what it comes to treat as true. This knowledge base could be accessed on demand by developers (or even AI agents) to provide verifiable insights covering everything from loading a dishwasher to the intricacies of the tax code. AI models would make fewer absurd mistakes, because they wouldn’t need to deduce everything from first principles. (Some research also suggests that such models would require far less data and energy, though these claims have yet to be proven.) Unlike today’s opaque AI models, whose knowledge emerges from pattern recognition and is spread across billions of parameters, a formally distilled body of human knowledge could be directly examined, understood, and controlled. Regulators could verify a model’s knowledge, and users could ensure that tools were mathematically guaranteed not to make idiotic mistakes.” submitted by /u/AngleAccomplished865
Originally posted by u/AngleAccomplished865 on r/ArtificialInteligence
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