{"id":437235,"date":"2026-09-16T01:54:11","date_gmt":"2026-09-16T01:54:11","guid":{"rendered":"https:\/\/www.newsbeep.com\/us-tx\/437235\/"},"modified":"2026-09-16T01:54:11","modified_gmt":"2026-09-16T01:54:11","slug":"ut-san-antonio-scientists-build-continuous-learning-ai-chip","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/us-tx\/437235\/","title":{"rendered":"UT San Antonio scientists build continuous learning AI chip"},"content":{"rendered":"<p class=\"sc-dLMFU sc-fHjqPf jbiTJv kYFPaL article-text\">SAN ANTONIO \u2013 With all the things artificial intelligence or AI technology can do, there is one thing it cannot do: remember. <\/p>\n<p class=\"sc-dLMFU sc-fHjqPf jbiTJv kYFPaL article-text\">\u201cIt\u2019s not able to retain knowledge that it has learned in the past,\u201d Dhireesha Kudithipudi, Ph.D, said.<\/p>\n<p class=\"sc-dLMFU sc-fHjqPf jbiTJv kYFPaL article-text\">Kudithipudi is the director of UT San Antonio\u2019s Matrix AI Consortium and the Neuromorphic Artificial Intelligence Laboratory (NUAI) Lab in the College of AI, Cyber and Computing.<\/p>\n<p class=\"sc-dLMFU sc-fHjqPf jbiTJv kYFPaL article-text\">She said when AI systems in use are programmed to learn new tasks, they can begin to override what it has previously learned. This phenomenon is known as \u201ccatastrophic forgetting.\u201d <\/p>\n<p class=\"sc-dLMFU sc-fHjqPf jbiTJv kYFPaL article-text\">Kudithipudi said it is critical that AI systems be able to recall previous knowledge it learned and gathered because the technology is being used more and more in critical environments like healthcare and exploration.<\/p>\n<p class=\"sc-dLMFU sc-fHjqPf jbiTJv kYFPaL article-text\">\u201cThe environment is constantly changing, and you need to be able to learn in that changing environment and still perform well,\u201d she said. \u201cBut what if your chip has forgotten what it has learned in the past, the decisions it\u2019s going to make are going to be dangerous in some scenarios and compromised in other scenarios.\u201d <\/p>\n<p class=\"sc-dLMFU sc-fHjqPf jbiTJv kYFPaL article-text\">For a decade, Kudithipudi has sought to come up with a solution, and within the last five years she and the members of her research and development team believe they may have it.<\/p>\n<p class=\"sc-dLMFU sc-fHjqPf jbiTJv kYFPaL article-text\">Their solution is the <a href=\"https:\/\/news.utsa.edu\/2026\/07\/genesis-the-ai-chip-that-doesnt-forget\/\" target=\"_blank\" rel=\"noreferrer nofollow noopener\" title=\"https:\/\/news.utsa.edu\/2026\/07\/genesis-the-ai-chip-that-doesnt-forget\/\">Genesis 2.0 AI chip<\/a>, designed with a continuous learning software or algorithm so the chip itself can keep learning throughout its lifetime.<\/p>\n<p class=\"sc-dLMFU sc-fHjqPf jbiTJv kYFPaL article-text\">Its design was inspired by how the human brain forms connections. <\/p>\n<p class=\"sc-dLMFU sc-fHjqPf jbiTJv kYFPaL article-text\">Nicholas Soures, Ph.D, is a member of the consortium who worked on the Genesis chip. Soures said working alongside neuroscientists on the team, they were able to look and replicate some features of the brain to build the algorithm.<\/p>\n<p class=\"sc-dLMFU sc-fHjqPf jbiTJv kYFPaL article-text\">\u201cWe started looking at spiking neural networks &#8230; and features such as metaplasticity and others, looked like a natural fit for a concept of a continued learning system in a platform that was already adaptable to energy efficient hardware,\u201d Soures said. <\/p>\n<p class=\"sc-dLMFU sc-fHjqPf jbiTJv kYFPaL article-text\">Fatima Tuz Zohora, Ph.D, was focused on finding the right device that could both run the continuous learning algorithm and also store what the chip learned.<\/p>\n<p class=\"sc-dLMFU sc-fHjqPf jbiTJv kYFPaL article-text\">\u201cWe use memristors, which are emerging memory devices, to perform continual learning &#8230; These devices are really compact,\u201d Tuz Zohora said. \u201cThey are nanoscale devices and arranged in a crossbar setting or in a crossover structure (and) can perform computation in the same substrate where the memory is stored. So this reduces data movement during continual learning and reduces energy consumption.\u201d<\/p>\n<p class=\"sc-dLMFU sc-fHjqPf jbiTJv kYFPaL article-text\">Vedant Karia, Ph.D, is also on the team for the Genesis 2.0 chip. Karia said the chip can be connected to any device and, if desired, it could be used as an additional accelerator at low power.<\/p>\n<p class=\"sc-dLMFU sc-fHjqPf jbiTJv kYFPaL article-text\">\u201cAll the high-energy, high-power computations that traditional systems do can be offloaded to this chip and can be done at a very low power. That was the main idea of this chip while developing,\u201d Karia said. \u201cSo it can be connected to any devices in, (for example) you take any healthcare devices or any robotics, you can connect them directly to the processor on them and then you are all set to go.\u201d <\/p>\n<p class=\"sc-dLMFU sc-fHjqPf jbiTJv kYFPaL article-text\">Karia said the chip is not ready go mainstream just yet, explaining that few more steps need to be completed before it is completely deployable for real-world application.<\/p>\n<p class=\"sc-dLMFU sc-fHjqPf jbiTJv kYFPaL article-text\">Kudithipudi said the progress of the Genesis 2.0 chip as it currently is took about five years, with the design and fabrication costing around $2 million.<\/p>\n<p class=\"sc-dLMFU sc-fHjqPf jbiTJv kYFPaL article-text\">Research and development of the chip has been funded through a grant by the Air Force Research Laboratory (AFLR).<\/p>\n<p class=\"sc-dLMFU sc-fHjqPf jbiTJv kYFPaL article-text\">Team members are excited and consider the Genesis 2.0 chip a major win in the evolution of true AI.<\/p>\n<p class=\"sc-dLMFU sc-fHjqPf jbiTJv kYFPaL article-text\">Read also:<\/p>\n<p>Copyright 2026 by KSAT &#8211; All rights reserved.<\/p>\n","protected":false},"excerpt":{"rendered":"SAN ANTONIO \u2013 With all the things artificial intelligence or AI technology can do, there is one thing&hellip;\n","protected":false},"author":2,"featured_media":437236,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[8],"tags":[4267,82,84,83,3621,3439],"class_list":["post-437235","post","type-post","status-publish","format-standard","has-post-thumbnail","category-san-antonio","tag-ai","tag-san-antonio","tag-san-antonio-headlines","tag-san-antonio-news","tag-technology","tag-utsa"],"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/us-tx\/wp-json\/wp\/v2\/posts\/437235","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/us-tx\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/us-tx\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us-tx\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us-tx\/wp-json\/wp\/v2\/comments?post=437235"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/us-tx\/wp-json\/wp\/v2\/posts\/437235\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/us-tx\/wp-json\/wp\/v2\/media\/437236"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/us-tx\/wp-json\/wp\/v2\/media?parent=437235"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/us-tx\/wp-json\/wp\/v2\/categories?post=437235"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/us-tx\/wp-json\/wp\/v2\/tags?post=437235"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}