{"id":30276,"date":"2022-09-02T06:00:00","date_gmt":"2022-09-02T13:00:00","guid":{"rendered":"https:\/\/insidebigdata.com\/?p=30276"},"modified":"2023-06-23T12:39:27","modified_gmt":"2023-06-23T19:39:27","slug":"research-highlights-interactive-continual-learning-for-robots-a-neuromorphicapproach","status":"publish","type":"post","link":"https:\/\/insidebigdata.com\/2022\/09\/02\/research-highlights-interactive-continual-learning-for-robots-a-neuromorphicapproach\/","title":{"rendered":"Research Highlights: Interactive continual learning for robots: a neuromorphicapproach"},"content":{"rendered":"\n

Title: <\/strong>Interactive continual learning for robots: a neuromorphic approach<\/a><\/p>\n\n\n\n

Overview: <\/strong>Researchers at Intel Labs<\/a>, in collaboration with the Italian Institute of Technology and the Technical University of Munich, have introduced a new approach to neural network-based object learning, specifically targeting future robotics applications such as robotic assistants that interact with unconstrained environments \u2013 in situations like logistics, health- or elderly care.\u202f <\/p>\n\n\n\n

The researchers developed new models that successfully demonstrated continual interactive learning on Intel\u2019s neuromorphic research chip measuring up to 175x lower energy to learn a new object instance with similar or better speed and accuracy compared to conventional methods running on a central processing unit (CPU). This research is a crucial step in improving the capabilities of future assistive or manufacturing robots using neuromorphic computing to enable them to adapt to the unforeseen and work more naturally alongside humans.\u202f <\/p>\n\n\n\n

Read the full paper HERE<\/a>, which was named \u201cBest Paper\u201d at this year\u2019s International Conference on Neuromorphic Systems (ICONS) hosted by Oak Ridge National Laboratory.\u202f\u202f\u202f <\/p>\n\n\n

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Sign up for the free insideBIGDATA newsletter<\/a>.<\/em><\/p>\n\n\n\n

Join us on Twitter: @InsideBigData1 \u2013 https:\/\/twitter.com\/InsideBigData1<\/a><\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

In this regular column we take a look at highlights for breaking research topics of the day in the areas of big data, data science, machine learning, AI and deep learning. For data scientists, it\u2019s important to keep connected with the research arm of the field in order to understand where the technology is headed. Enjoy!<\/p>\n","protected":false},"author":37,"featured_media":22835,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"footnotes":""},"categories":[526,115,87,180,210,56,77,84,1303,1],"tags":[284,861,770,96],"acf":[],"yoast_head":"\nResearch Highlights: Interactive continual learning for robots: a neuromorphicapproach - insideBIGDATA<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/insidebigdata.com\/2022\/09\/02\/research-highlights-interactive-continual-learning-for-robots-a-neuromorphicapproach\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Research Highlights: Interactive continual learning for robots: a neuromorphicapproach - insideBIGDATA\" \/>\n<meta property=\"og:description\" content=\"In this regular column we take a look at highlights for breaking research topics of the day in the areas of big data, data science, machine learning, AI and deep learning. 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Gutierrez is a Data Scientist with Los Angeles-based AMULET Analytics, a service division of AMULET Development Corp. He's been involved with data science and Big Data long before it came in vogue, so imagine his delight when the Harvard Business Review recently deemed \\\"data scientist\\\" as the sexiest profession for the 21st century. Previously, he taught computer science and database classes at UCLA Extension for over 15 years, and authored three computer industry books on database technology. He also served as technical editor, columnist and writer at a major computer industry monthly publication for 7 years. 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Gutierrez is a Data Scientist with Los Angeles-based AMULET Analytics, a service division of AMULET Development Corp. He's been involved with data science and Big Data long before it came in vogue, so imagine his delight when the Harvard Business Review recently deemed \"data scientist\" as the sexiest profession for the 21st century. Previously, he taught computer science and database classes at UCLA Extension for over 15 years, and authored three computer industry books on database technology. He also served as technical editor, columnist and writer at a major computer industry monthly publication for 7 years. Follow his data science musings at @AMULETAnalytics.","sameAs":["http:\/\/www.insidebigdata.com","https:\/\/twitter.com\/@AMULETAnalytics"],"url":"https:\/\/insidebigdata.com\/author\/dangutierrez\/"}]}},"jetpack_featured_media_url":"https:\/\/insidebigdata.com\/wp-content\/uploads\/2019\/06\/Data-Scientist-shutterstock_768047488.jpg","jetpack_shortlink":"https:\/\/wp.me\/p9eA3j-7Sk","jetpack-related-posts":[{"id":24771,"url":"https:\/\/insidebigdata.com\/2020\/07\/16\/research-highlights-singapore-researchers-look-to-intel-neuromorphic-computing-to-help-enable-robots-that-feel\/","url_meta":{"origin":30276,"position":0},"title":"Research Highlights: Singapore Researchers Look to Intel Neuromorphic Computing to Help Enable Robots That \u2018Feel\u2019","date":"July 16, 2020","format":false,"excerpt":"Today, two researchers from the National University of Singapore (NUS), who are members of the Intel Neuromorphic Research Community (INRC), presented new findings demonstrating the promise of event-based vision and touch sensing in combination with Intel\u2019s neuromorphic processing for robotics. 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