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| The Next Decade in AI: Four Steps Towards Robust Artificial Intelligence (arxiv.org) | |
| 3 points by Anon84 on Jun 13, 2020 | hide | past | pdf | 1 comment on HN | |
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In plain words: A proposed AI design pairs general-purpose learning with built-in knowledge and step-by-step reasoning, organized around models of how people think. Unlike today's push for ever-larger training sets and more computing power, this mix is argued to yield AI that is richer and more robust. AbstractRecent research in artificial intelligence and machine learning has largely emphasized general-purpose learning and ever-larger training sets and more and more compute. In contrast, I propose a hybrid, knowledge-driven, reasoning-based approach, centered around cognitive models, that could provide the substrate for a richer, more robust AI than is currently possible. | |
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Good read (both paper and their book).
A little off topic, but I have been an AI practitioner since the early 1980s. The beginning of my career was "symbolic" AI, the last 6 years were deep learning, and now I am also getting interested in hybrid AI which I mostly do in Common Lisp with some code calling out to Python and TensorFlow.