{"id":86100,"date":"2023-10-23T16:42:11","date_gmt":"2023-10-23T13:42:11","guid":{"rendered":"https:\/\/forklog.com\/en\/?p=86100"},"modified":"2025-09-13T03:22:00","modified_gmt":"2025-09-13T00:22:00","slug":"nvidia-boosts-robot-mobility-with-ai","status":"publish","type":"post","link":"https:\/\/u1f987.com\/en\/nvidia-boosts-robot-mobility-with-ai\/","title":{"rendered":"Nvidia boosts robot mobility with AI"},"content":{"rendered":"<p>Nvidia has made a significant leap in the agility of robots thanks to the <a href=\"https:\/\/blogs.nvidia.com\/blog\/2023\/10\/20\/eureka-robotics-research\/\">\u0418\u0418-\u0438\u043d\u0441\u0442\u0440\u0443\u043c\u0435\u043d\u0442\u0443 Eureka<\/a>, which trains mechanisms in complex skills such as turning a knob.<\/p>\n<p><iframe loading=\"lazy\" width=\"560\" height=\"315\" src=\"https:\/\/www.youtube.com\/embed\/sDFAWnrCqKc?si=ZOtWH2Kl6rSqS8P8\" title=\"YouTube video player\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" allowfullscreen><\/iframe><\/p>\n<p>The neural network has also taught robots to open drawers and cupboards, throw and catch balls, use scissors, and perform other tasks.<\/p>\n<p>Eureka is based on OpenAI&#8217;s GPT-4 large language model by Sam Altman and uses generative AI to write code.<\/p>\n<p>According to the company, AI-generated &#8216;reward programs&#8217; that train bots by trial and error outperform analogues from domain experts in 80% of tasks.<\/p>\n<p>Eureka does not require prompts or canned templates to perform tasks. The technology takes into account prior developer feedback and, on that basis, adjusts the incentives to yield more accurate results.<\/p>\n<p>Nvidia&#8217;s product has already been trained on a wide range of tasks for quadruped and biped robots, drones, and manipulators.<\/p>\n<blockquote class=\"wp-block-quote is-layout-flow wp-block-quote-is-layout-flow\">\n<p>&#8220;Using GPU-accelerated modelling, Eureka can rapidly process large batches of reward candidates for more efficient training. The neural network then collects information about key statistics and improves the reward functions. In this way, AI self-improves,&#8221; the company explained.<\/p>\n<\/blockquote>\n<figure class=\"wp-block-video\"><video controls src=\"https:\/\/u1f987.com\/wp-content\/uploads\/humanoid.mp4\"><\/video><figcaption class=\"wp-element-caption\">Humanoid robot learns to run with Eureka. Data: Nvidia.<\/figcaption><\/figure>\n<p>In August Nvidia <a href=\"https:\/\/u1f987.com\/en\/news\/nvidia-posts-record-profit-as-a-new-computer-era-begins\">reported<\/a> record profit for the second quarter of fiscal 2024. Earnings per share were $2.70 as revenue more than doubled year over year to $13.5 billion.<\/p>\n<p>In October, the tech firm <a href=\"https:\/\/u1f987.com\/en\/news\/nvidia-and-foxconn-strike-partnership-to-accelerate-an-industrial-ai-revolution\">announced<\/a> a collaboration with Taiwan&#8217;s Hon Hai Technology Group (Foxconn), a Taiwanese electronics manufacturer, to accelerate an &#8216;AI industrial revolution&#8217; in the field of artificial intelligence.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Nvidia has made a significant leap in the agility of robots thanks to the AI tool Eureka, which trains mechanisms in complex skills such as turning a knob.<\/p>\n","protected":false},"author":1,"featured_media":86101,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"select":"1","news_style_id":"1","cryptorium_level":"","_short_excerpt_text":"","creation_source":"","_metatest_mainpost_news_update":false,"footnotes":""},"categories":[3],"tags":[438,1294,652],"class_list":["post-86100","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news-and-analysis","tag-artificial-intelligence","tag-nvidia","tag-robots"],"aioseo_notices":[],"amp_enabled":true,"views":"17","promo_type":"1","layout_type":"1","short_excerpt":"","is_update":"","_links":{"self":[{"href":"https:\/\/u1f987.com\/en\/wp-json\/wp\/v2\/posts\/86100","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/u1f987.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/u1f987.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/u1f987.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/u1f987.com\/en\/wp-json\/wp\/v2\/comments?post=86100"}],"version-history":[{"count":1,"href":"https:\/\/u1f987.com\/en\/wp-json\/wp\/v2\/posts\/86100\/revisions"}],"predecessor-version":[{"id":86102,"href":"https:\/\/u1f987.com\/en\/wp-json\/wp\/v2\/posts\/86100\/revisions\/86102"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/u1f987.com\/en\/wp-json\/wp\/v2\/media\/86101"}],"wp:attachment":[{"href":"https:\/\/u1f987.com\/en\/wp-json\/wp\/v2\/media?parent=86100"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/u1f987.com\/en\/wp-json\/wp\/v2\/categories?post=86100"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/u1f987.com\/en\/wp-json\/wp\/v2\/tags?post=86100"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}