Dietrich Dorner

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Documents
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Also known as:
Dorner

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person Joscha Bach
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person Joscha Bach
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person Joscha Bach
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person Psi Model
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This document is page 339 of a technical glossary, likely from a book or scientific paper regarding Artificial General Intelligence (AGI). It defines terms such as 'Procedure Learning,' 'Psi,' 'Psynese,' and 'Reinforcement Learning,' specifically referencing the OpenCog and Novamente AI architectures. The footer 'HOUSE_OVERSIGHT_013255' indicates this document was produced as evidence in a House Oversight Committee investigation, likely related to Epstein's funding of or interest in AI research and scientists.

Technical glossary / academic manuscript page (evidence production)
2025-11-19

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This document is a glossary page (p. 337) from a technical report regarding Artificial General Intelligence (AGI). It defines specialized terms including MOSES, Node, Novamente Cognition Engine (NCE), and OpenCog. The document bears a House Oversight Committee stamp, linking it to the investigation, likely due to Jeffrey Epstein's known funding of AI research and connections to the scientists behind OpenCog/Novamente (such as Ben Goertzel, though not named on this specific page).

Technical glossary / scientific report appendix
2025-11-19

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This document is page 331 of a glossary from a scientific paper or book regarding Artificial Intelligence, specifically focusing on the OpenCog architecture. It defines technical terms such as 'Embodiment,' 'Emotion' (referencing Dorner's Psi theory), 'Evolutionary Learning' (referencing MOSES), and 'Fishgram.' The document bears a 'HOUSE_OVERSIGHT_013247' stamp, indicating it was part of a document production to the US House Oversight Committee, likely related to investigations into Jeffrey Epstein's funding of or interest in AI and transhumanist research.

Academic glossary / scientific manuscript excerpt
2025-11-19

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This document is a page (p. 96) from an academic text regarding Artificial General Intelligence (AGI) and cognitive architecture, specifically Chapter 5. It discusses technical models such as CogPrime, LIDA, and CogAff, referencing prominent AI scientists like Aaron Sloman and Jeff Hawkins. While the text itself is purely scientific, the footer 'HOUSE_OVERSIGHT_013012' indicates this document was part of a production to the House Oversight Committee, likely related to investigations into Jeffrey Epstein's extensive funding of and connections to the scientific community.

Academic textbook/paper excerpt (house oversight committee production)
2025-11-19

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This document page (Bates stamped HOUSE_OVERSIGHT_013006) contains an excerpt from an academic text regarding cognitive architectures, specifically detailing the 'Psi Model' and its handling of motives, urges, and emotions in AI systems. It includes a flowchart (Fig 4.14) illustrating the architecture. While the content is purely scientific, the footer suggests it was included as evidence in a House Oversight investigation, likely related to Jeffrey Epstein's funding of or involvement with scientific research (e.g., MIT Media Lab or AI research).

Academic text/diagram (scientific paper excerpt within government oversight file)
2025-11-19

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This document is page 88 from a scientific text titled 'Brief Survey of Cognitive Architectures.' It discusses technical theories of Artificial General Intelligence (AGI), specifically comparing 'LIDA' and 'CogPrime' systems, and introducing 'Psi' and 'MicroPsi' architectures created by Dietrich Dorner and Joscha Bach. While the content is purely academic, the footer 'HOUSE_OVERSIGHT_013004' indicates it was part of documents collected by the House Oversight Committee, likely regarding Jeffrey Epstein's funding of or interest in transhumanist and AI research.

Scientific paper / academic book excerpt
2025-11-19

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This document provides a brief survey of hybrid cognitive architectures, specifically detailing CLARION, DUAL, LIDA, MicroPsi, and PolyScheme. It describes the core mechanisms of each system, their theoretical foundations (such as Global Workspace Theory or Society of Mind), and evaluates their strengths and limitations regarding symbolic vs. non-symbolic processing and scalability.

Technical report / academic paper
2025-11-19
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