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1.6 MB
Extraction Summary
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Document Information
Type:
Technical book chapter / academic paper (evidence item)
File Size:
1.6 MB
Summary
This document is page 271 from a technical book or academic paper discussing Artificial Intelligence, specifically Chapter 14: 'Representing Implicit Knowledge via Hypergraphs.' The text details the 'CogPrime' architecture, the concept of 'glocality,' and 'SMEPH' (Self-Modifying, Evolving Probabilistic Hypergraphs). While the content is purely scientific/technical, the page bears the Bates stamp 'HOUSE_OVERSIGHT_013187,' indicating it is part of a larger document production for a House Oversight investigation, likely related to Jeffrey Epstein's connections to or funding of scientists and AI research.
Organizations (2)
| Name | Type | Context |
|---|---|---|
| CogPrime |
Subject of the technical discussion regarding knowledge representation.
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| House Oversight Committee |
Indicated by the Bates stamp 'HOUSE_OVERSIGHT_013187' at the bottom right.
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Key Quotes (3)
"Explicit knowledge is easy to write about and talk about; implicit knowledge is equally important, but tends to get less attention in discussions of AI and psychology"Source
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"CogPrime combines these two sorts of representation according to the principle we have called glocality."Source
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"we have referred to "derived" or "emergent" hypergraphs of the sort described here using the acronym SMEPH, which stands for Self-Modifying, Evolving Probabilistic Hypergraphs."Source
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Quote #3
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