{"id":168159,"date":"2025-10-14T10:27:15","date_gmt":"2025-10-14T14:27:15","guid":{"rendered":"https:\/\/www.bu.edu\/eng\/?p=168159"},"modified":"2026-01-29T10:33:00","modified_gmt":"2026-01-29T15:33:00","slug":"illuminating-energy-efficient-ai","status":"publish","type":"post","link":"https:\/\/www.bu.edu\/eng\/2025\/10\/14\/illuminating-energy-efficient-ai\/","title":{"rendered":"Illuminating Energy-Efficient AI"},"content":{"rendered":"<p><em>by A.J. Kleber<\/em><\/p>\n<p><span style=\"font-weight: 400;\">With the meteoric rise of AI technologies over the last few years, and their rapid integration across diverse industries and societal infrastructures, concerns over their immense energy requirements have come into sharp focus for users and researchers alike. Deep Neural Networks (DNNs) and large language models (LLMs), some of the most influential models on the market today, are trained and deployed in data centers powered by specialized silicon-based hardware such as graphics processing units (GPUs), and their booming energy demands have been well-publicized. Experts are scrambling to find options to mitigate or amend this unsustainable drain on global resources.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">To address this critical issue, Professor Ajay Joshi is exploring the development of novel electro-photonic computing architectures that could perform as well or better than conventional electronic GPUs. Supported by a <\/span><a href=\"https:\/\/www.nsf.gov\/awardsearch\/showAward?AWD_ID=2520334&amp;HistoricalAwards=false\"><span style=\"font-weight: 400;\">$1.5M grant<\/span><\/a><span style=\"font-weight: 400;\"> from the NSF, titled <\/span><i><span style=\"font-weight: 400;\">ASCENT: Heterogeneously Integrated Electronic Photonic AI Accelerators (HIEPAA)<\/span><\/i><span style=\"font-weight: 400;\">, he is investigating the use of light-based computing for energy-efficient AI hardware.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Light is a far more efficient medium for data transmission than electricity, and recent advances in integrated electronic-photonic systems have shown significant promise. Joshi\u2019s approach incorporates an electro-optical metamaterial called thin-film lithium niobate (TFLN) into silicon photonic chip platforms, in order to produce analog optical modulators; devices which will greatly increase the speed of computing\u00a0 from that of traditional silicon-based electronic devices, while also decreasing data loss. He plans to design new architectures and circuit techniques to achieve efficient, highly accurate AI computation using low-precision building blocks, a concept <\/span><a href=\"https:\/\/www.bu.edu\/eng\/2024\/09\/24\/analog-neural-networks-nature-communications-publishes-ece-researchers-blueprint-for-precision\/\"><span style=\"font-weight: 400;\">previously explored<\/span><\/a><span style=\"font-weight: 400;\"> by his research group and published in <\/span><i><span style=\"font-weight: 400;\">Nature Communications<\/span><\/i><span style=\"font-weight: 400;\">.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">With these innovations, the future of AI could be bright indeed.<\/span><\/p>\n<p><span style=\"font-weight: 400;\"><img loading=\"lazy\" src=\"\/eng\/files\/2022\/06\/ajay.joshi_.jpg\" alt=\"Professor Joshi headshot\" width=\"149\" height=\"149\" class=\"alignleft wp-image-118738\" srcset=\"https:\/\/www.bu.edu\/eng\/files\/2022\/06\/ajay.joshi_.jpg 600w, https:\/\/www.bu.edu\/eng\/files\/2022\/06\/ajay.joshi_-150x150.jpg 150w, https:\/\/www.bu.edu\/eng\/files\/2022\/06\/ajay.joshi_-300x300.jpg 300w, https:\/\/www.bu.edu\/eng\/files\/2022\/06\/ajay.joshi_-550x550.jpg 550w, https:\/\/www.bu.edu\/eng\/files\/2022\/06\/ajay.joshi_-100x100.jpg 100w\" sizes=\"(max-width: 149px) 100vw, 149px\" \/><a href=\"https:\/\/www.bu.edu\/eng\/profile\/ajay-joshi\/\">Professor Ajay Joshi<\/a> leads the Integrated Circuits, Architectures, and Systems Group at Boston University. His accolades include multiple Google Faculty Research Awards, Best Paper Awards, and a 2012 NSF CAREER AWARD. He also serves as CEO and co-founder of CipherSonic Labs, a start-up dedicated to data privacy technology development, and the recipient of a 2024 BU Technology Development Ignition Award.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Supported by a $1.5M NSF grant, Professor Ajay Joshi is exploring the development of novel electro-photonic computing architectures that could perform as well or better than conventional electronic GPUs.<\/p>\n","protected":false},"author":18241,"featured_media":168157,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[236,257,1148,1429,287,317,977,240,907],"tags":[1121,728,730,731,1403,1402],"_links":{"self":[{"href":"https:\/\/www.bu.edu\/eng\/wp-json\/wp\/v2\/posts\/168159"}],"collection":[{"href":"https:\/\/www.bu.edu\/eng\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.bu.edu\/eng\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/eng\/wp-json\/wp\/v2\/users\/18241"}],"replies":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/eng\/wp-json\/wp\/v2\/comments?post=168159"}],"version-history":[{"count":1,"href":"https:\/\/www.bu.edu\/eng\/wp-json\/wp\/v2\/posts\/168159\/revisions"}],"predecessor-version":[{"id":168160,"href":"https:\/\/www.bu.edu\/eng\/wp-json\/wp\/v2\/posts\/168159\/revisions\/168160"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/eng\/wp-json\/wp\/v2\/media\/168157"}],"wp:attachment":[{"href":"https:\/\/www.bu.edu\/eng\/wp-json\/wp\/v2\/media?parent=168159"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.bu.edu\/eng\/wp-json\/wp\/v2\/categories?post=168159"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.bu.edu\/eng\/wp-json\/wp\/v2\/tags?post=168159"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}