{"id":189375,"date":"2024-05-14T11:23:30","date_gmt":"2024-05-14T16:23:30","guid":{"rendered":"https:\/\/lifeboat.com\/blog\/2024\/05\/mit-gives-ai-the-power-to-reason-like-humans-by-creating-hybrid-architecture"},"modified":"2024-05-14T11:23:30","modified_gmt":"2024-05-14T16:23:30","slug":"mit-gives-ai-the-power-to-reason-like-humans-by-creating-hybrid-architecture","status":"publish","type":"post","link":"https:\/\/lifeboat.com\/blog\/2024\/05\/mit-gives-ai-the-power-to-reason-like-humans-by-creating-hybrid-architecture","title":{"rendered":"MIT gives AI the power to \u2018reason like humans\u2019 by creating hybrid architecture"},"content":{"rendered":"<p><a class=\"aligncenter blog-photo\" href=\"https:\/\/lifeboat.com\/blog.images\/mit-gives-ai-the-power-to-reason-like-humans-by-creating-hybrid-architecture2.jpg\"><\/a><\/p>\n<p>But MIT scientists now claim to have cracked this problem by creating \u201ca treasure trove\u201d of natural language \u201cabstractions\u201d that could lead to more powerful AI models. Abstractions turn complex subjects into high-level characterizations and omit non-important information \u2014 which could help chatbots reason, learn, perceive, and represent knowledge just like humans.<\/p>\n<p>Currently, scientists argue that LLMs have difficulty abstracting information in a human-like way. However, they have organized natural language abstractions into three libraries in the hope that they will gain greater contextual awareness and give more human-like responses.<\/p>\n<p>The scientists detailed their findings in three papers published on the arXiv pre-print server Oct. 30 2023, Dec. 13 2023 and Feb. 28. The first library, called the \u201cLibrary Induction from Language Observations\u201d (LILO) synthesizes, compresses, and documents computer code. The second, named \u201cAction Domain Acquisition\u201d (Ada) covers AI sequential decision making. The final framework, dubbed \u201cLanguage-Guided Abstraction\u201d (LGA), helps robots better understand environments and plan their movements.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>But MIT scientists now claim to have cracked this problem by creating \u201ca treasure trove\u201d of natural language \u201cabstractions\u201d that could lead to more powerful AI models. Abstractions turn complex subjects into high-level characterizations and omit non-important information \u2014 which could help chatbots reason, learn, perceive, and represent knowledge just like humans. Currently, scientists argue [\u2026]<\/p>\n","protected":false},"author":396,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[6],"tags":[],"class_list":["post-189375","post","type-post","status-publish","format-standard","hentry","category-robotics-ai"],"_links":{"self":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/189375","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/users\/396"}],"replies":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/comments?post=189375"}],"version-history":[{"count":0,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/189375\/revisions"}],"wp:attachment":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/media?parent=189375"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/categories?post=189375"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/tags?post=189375"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}