{"id":22007,"date":"2025-03-13T10:05:05","date_gmt":"2025-03-13T08:05:05","guid":{"rendered":"https:\/\/forklog.com\/en\/google-deepmind-unveils-ai-for-robotics\/"},"modified":"2025-03-13T10:05:05","modified_gmt":"2025-03-13T08:05:05","slug":"google-deepmind-unveils-ai-for-robotics","status":"publish","type":"post","link":"https:\/\/forklog.com\/en\/google-deepmind-unveils-ai-for-robotics\/","title":{"rendered":"Google DeepMind Unveils AI for Robotics"},"content":{"rendered":"<p>Google&#8217;s AI division, DeepMind, has <a href=\"https:\/\/deepmind.google\/discover\/blog\/gemini-robotics-brings-ai-into-the-physical-world\/?utm_source=keywordsnippet&#038;utm_medium=referral\">introduced<\/a> new models for robot control based on Gemini 2.0.<\/p>\n<p>These models enable machines to interact with real-world objects, navigate their surroundings, and perform various tasks.<\/p>\n<p>Gemini Robotics is an advanced neural network that incorporates physical actions as output information for robot control. Gemini Robotics-ER is a model with enhanced spatial understanding.<\/p>\n<p>Both systems allow robots to perform a wide range of real-world tasks. The team has released a series of demonstration videos showing them folding paper, placing glasses in a case, and completing other tasks in response to voice commands.<\/p>\n<p><iframe loading=\"lazy\" width=\"560\" height=\"315\" src=\"https:\/\/www.youtube.com\/embed\/4MvGnmmP3c0?si=CrPPnWTRB4b9BhvR\" title=\"YouTube video player\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen><\/iframe><\/p>\n<p>DeepMind noted that during tests, the robots operated in conditions not included in the training data. Developers have released a scaled-down version of Gemini Robotics-ER, which other researchers can use to train their own robot control models.<\/p>\n<p>In March, the company Agibot <a href=\"https:\/\/forklog.com\/en\/news\/agibot-unveils-ai-for-humanoids\">launched<\/a> the AI Genie Operator-1 (GO-1) for humanoid robots, enabling rapid comprehension and task execution.<\/p>\n<p>Earlier, Figure <a href=\"https:\/\/forklog.com\/en\/news\/figure-unveils-revolutionary-ai-for-robots\">introduced<\/a> its own artificial intelligence, Helix, for integration with mechanical devices. According to its creators, the model is capable of &#8220;reasoning like a human.&#8221;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Google&#8217;s AI division, DeepMind, has introduced new models for robot control based on Gemini 2.0. These models enable machines to interact with real-world objects, navigate their surroundings, and perform various tasks. Gemini Robotics is an advanced neural network that incorporates physical actions as output information for robot control. Gemini Robotics-ER is a model with enhanced [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":22006,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"select":"","news_style_id":"","cryptorium_level":"","_short_excerpt_text":"","creation_source":"","_metatest_mainpost_news_update":false,"footnotes":""},"categories":[3],"tags":[438,1474,738,652],"class_list":["post-22007","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news-and-analysis","tag-artificial-intelligence","tag-deepmind","tag-google","tag-robots"],"aioseo_notices":[],"amp_enabled":true,"views":"15","promo_type":"","layout_type":"","short_excerpt":"","is_update":"","_links":{"self":[{"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/posts\/22007","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/comments?post=22007"}],"version-history":[{"count":0,"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/posts\/22007\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/media\/22006"}],"wp:attachment":[{"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/media?parent=22007"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/categories?post=22007"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/forklog.com\/en\/wp-json\/wp\/v2\/tags?post=22007"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}