Thrill-K Architecture: Towards a Solution to the Problem of Knowledge Based Understanding

• URL: http://arxiv.org/abs/2303.12084v1
• Date: Tue, 28 Feb 2023 20:39:35 GMT
• Title: Thrill-K Architecture: Towards a Solution to the Problem of Knowledge Based Understanding
• Authors: Gadi Singer, Joscha Bach, Tetiana Grinberg, Nagib Hakim, Phillip Howard, Vasudev Lal and Zev Rivlin
• Abstract summary: We introduce a classification of hybrid systems which, based on an analysis of human knowledge and intelligence, combines neural learning with various types of knowledge and knowledge sources. We present the Thrill-K architecture as a prototypical solution for integrating instantaneous knowledge, standby knowledge and external knowledge sources in a framework capable of inference, learning and intelligent control.
• Score: 0.9390008801320021
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: While end-to-end learning systems are rapidly gaining capabilities and popularity, the increasing computational demands for deploying such systems, along with a lack of flexibility, adaptability, explainability, reasoning and verification capabilities, require new types of architectures. Here we introduce a classification of hybrid systems which, based on an analysis of human knowledge and intelligence, combines neural learning with various types of knowledge and knowledge sources. We present the Thrill-K architecture as a prototypical solution for integrating instantaneous knowledge, standby knowledge and external knowledge sources in a framework capable of inference, learning and intelligent control.

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