{"id":174672,"date":"2023-10-24T23:22:52","date_gmt":"2023-10-25T04:22:52","guid":{"rendered":"https:\/\/lifeboat.com\/blog\/2023\/10\/eureka-with-gpt-4-overseeing-training-robots-can-learn-much-faster"},"modified":"2023-10-24T23:22:52","modified_gmt":"2023-10-25T04:22:52","slug":"eureka-with-gpt-4-overseeing-training-robots-can-learn-much-faster","status":"publish","type":"post","link":"https:\/\/lifeboat.com\/blog\/2023\/10\/eureka-with-gpt-4-overseeing-training-robots-can-learn-much-faster","title":{"rendered":"Eureka: With GPT-4 overseeing training, robots can learn much faster"},"content":{"rendered":"<p><a class=\"aligncenter blog-photo\" href=\"https:\/\/lifeboat.com\/blog.images\/eureka-with-gpt-4-overseeing-training-robots-can-learn-much-faster.jpg\"><\/a><\/p>\n<p>On Friday, researchers from Nvidia, UPenn, Caltech, and the University of Texas at Austin announced Eureka, an algorithm that uses OpenAI\u2019s GPT-4 language model for designing training goals (called \u201creward functions\u201d) to enhance robot dexterity. The work aims to bridge the gap between high-level reasoning and low-level motor control, allowing robots to learn complex tasks rapidly using massively parallel simulations that run through trials simultaneously. According to the team, Eureka outperforms human-written reward functions by a substantial margin.<\/p>\n<p>\u201cLeveraging state-of-the-art GPU-accelerated simulation in Nvidia Isaac Gym,\u201d writes Nvidia on its demonstration page, \u201cEureka is able to quickly evaluate the quality of a large batch of reward candidates, enabling scalable search in the reward function space.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>On Friday, researchers from Nvidia, UPenn, Caltech, and the University of Texas at Austin announced Eureka, an algorithm that uses OpenAI\u2019s GPT-4 language model for designing training goals (called \u201creward functions\u201d) to enhance robot dexterity. The work aims to bridge the gap between high-level reasoning and low-level motor control, allowing robots to learn complex tasks [\u2026]<\/p>\n","protected":false},"author":359,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[41,6,8],"tags":[],"class_list":["post-174672","post","type-post","status-publish","format-standard","hentry","category-information-science","category-robotics-ai","category-space"],"_links":{"self":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/174672","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\/359"}],"replies":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/comments?post=174672"}],"version-history":[{"count":0,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/174672\/revisions"}],"wp:attachment":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/media?parent=174672"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/categories?post=174672"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/tags?post=174672"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}