{"id":13120,"date":"2019-07-09T09:21:23","date_gmt":"2019-07-09T13:21:23","guid":{"rendered":"https:\/\/news.elearninginside.com\/?p=13120"},"modified":"2019-07-09T13:03:29","modified_gmt":"2019-07-09T17:03:29","slug":"udacity-is-developing-an-ai-to-turn-instructors-speech-into-deepfake-style-video","status":"publish","type":"post","link":"https:\/\/news.elearninginside.com\/udacity-is-developing-an-ai-to-turn-instructors-speech-into-deepfake-style-video\/","title":{"rendered":"Udacity Developed an AI to Turn Instructor&#8217;s Speech into Deepfake-Style Video, But Has No Plans to Use It"},"content":{"rendered":"<p class=\"p1\"><span class=\"s1\">Deepfakes\u2014the practice of using AI practices of deep learning and neural networks to create fake videos\u2014have been circulating on the internet since 2017. Many have grown alarmed recently with their increasing sophistication and the resulting implications for the spread of misinformation. Udacity, <a href=\"https:\/\/news.elearninginside.com\/is-udacity-in-trouble\/\">the nanolearning provider<\/a>, has recently sought to use similar technology to cut the time and effort needed to record and update online courses. On July 4, two former members of their AI development team, Byung-Hak Kim and Varun Ganapathi, released <a href=\"https:\/\/arxiv.org\/pdf\/1907.02253.pdf\">a paper on arXiv.org<\/a> presenting their work conducted at Udacity, which they call Lumi\u00e8reNet.<\/span><\/p>\n<p class=\"p1\"><span class=\"s1\">The main purpose of Lumi\u00e8reNet is to allow instructors to make important updates to their courses without needing to head back into the studio, along with a video production team, to re-record course segments. <\/span><\/p>\n<p class=\"p1\"><span class=\"s1\">If successful, the application would instead allow instructors merely to record audio of the updated material. Using the previously recorded images and the instructor\u2019s speech, Lumi\u00e8reNet could then recreate a video to use for the course.\u00a0<\/span><\/p>\n<h2><span class=\"s1\">Lumi\u00e8reNet Was Developed at Udacity, but the Company Has No Plans to Put It to Use<\/span><\/h2>\n<p>Since its development, Udacity has since walked away from using <span class=\"s1\">Lumi\u00e8reNet<\/span>. Kim and Gunapathi, furthermore, have left to start their own company.<\/p>\n<p>&#8220;Lumi\u00e8reNet was developed by Byung-Hak Kim and Varun Ganapathi, two independent researchers and former Udacity employees,&#8221; a spokesperson said via email. &#8220;While it&#8217;s true that Hak and Varun developed and tested the algorithm using Udacity content (Udacity provided the videos and instructors gave consent), the algorithm neither belongs to Udacity nor do we use [it] to develop our content. Udacity&#8217;s classroom content is filmed at Udacity&#8217;s studio and built in collaboration with expert instructors.&#8221;<\/p>\n<p class=\"p1\"><span class=\"s1\">The researchers differ from others creating AI applications to make video replications of real people in one notable way: Kim and Ganapathi decided it would be simpler and better to approximate their video recreations instead of making super realistic copies. <\/span><\/p>\n<p class=\"p1\"><span class=\"s1\">They describe the problem they\u2019re trying to solve as trying to \u201clearn a function to map from an audio sequence recorded by an instructor to video sequence.\u201d\u00a0<\/span><\/p>\n<p class=\"p1\"><span class=\"s1\">To go about solving this, they write, \u201c[W]e consider neural network modules as a randomly chosen instance of this problem based on this probabilistic generative model. A key advantage is that each neural network model represents a single factor which separates the influence of other networks that can be trained and improved independently.\u201d<\/span><\/p>\n<p class=\"p1\"><span class=\"s1\">With the audio and image inputs, Lumi\u00e8reNet uses three neural network models: <a href=\"https:\/\/aclweb.org\/anthology\/E17-1096\">BLSTM<\/a>, a <a href=\"https:\/\/jaan.io\/what-is-variational-autoencoder-vae-tutorial\/\">variational auto-encoder<\/a>, and the <a href=\"https:\/\/hackernoon.com\/remastering-classic-films-in-tensorflow-with-pix2pix-f4d551fa0503\">generative adversarial network known as Pix2Pix<\/a>.<\/span><\/p>\n<h3 style=\"text-align: center;\">Watch a video demonstration of <span class=\"s1\">Lumi\u00e8reNet <a href=\"https:\/\/vimeo.com\/327196781\">here<\/a>.<\/span><\/h3>\n<p class=\"p1\"><span class=\"s1\">The authors consider this a simplification of other research, such as the now-notorious <a href=\"https:\/\/grail.cs.washington.edu\/projects\/AudioToObama\/siggraph17_obama.pdf\">2017 study that deepfaked former President Barack Obama<\/a><\/span>, which they cite in their paper.<\/p>\n<p class=\"p1\"><span class=\"s1\">The researchers also decided to approximate other key motions, such as blinking, and eye and hair movement.<\/span><\/p>\n<p class=\"p1\"><span class=\"s1\">To test out their deep learning function, the authors recreated a course video shoot. They brought in an instructor to record a 4+ hour video. They then took the audio and ran it through their application to compare results.<\/span><\/p>\n<h2>Initial Tests Went Well<\/h2>\n<p class=\"p1\"><span class=\"s1\">In their paper, Kim and Gunapathi report positive findings with several attributes of their AI. It\u2019s especially successful when the instructor faces the camera head on. But they also struggled in other areas. Hands and fingers were especially difficult and tended to blur together when they were folded together.\u00a0<\/span><\/p>\n<p class=\"p1\"><span class=\"s1\">While this work was created to improve course production, the authors acknowledge in their introduction that they need to exercise caution using their AI for other reasons.<\/span><\/p>\n<p class=\"p1\"><span class=\"s1\">\u201cEven though our approach is developed with primary intents to support agile video content development which is crucial in current online MOOC courses, we acknowledge there could be potential misuse of the technologies,&#8221; the authors write. &#8220;Nonetheless, we believe it is crucial synthesized video using our approach requires to indicate as synthetic and it is also imperative to obtain consent from the instructors across the entire production processes.\u201d<\/span><\/p>\n<p>Kim and Gunapathi left Udacity to form their own AI startup in April. Read the full paper <a href=\"https:\/\/arxiv.org\/pdf\/1907.02253.pdf\">here<\/a>.<\/p>\n<p><em>Featured Image: TechCrunch, Flickr.<\/em><\/p>\n<p>Correction July 9: A previous version of this article stated that Gunapathi and Kim currently work at Udacity. The two researchers left the company to form their own startup in April. A previous version also indicated that Udacity owned the software. While <span class=\"s1\">Lumi\u00e8reNet<\/span> was developed by the company, it does exercise ownership over the software.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Deepfakes\u2014the practice of using AI practices of deep learning and neural networks to create fake videos\u2014have been circulating on the internet since 2017. Many have grown alarmed recently with their increasing sophistication and the resulting implications for the spread of misinformation. Udacity, the nanolearning provider, has recently sought to use similar technology to cut the [&hellip;]<\/p>\n","protected":false},"author":11,"featured_media":13231,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[5,6],"tags":[],"class_list":["post-13120","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-articles","category-editors-picks"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.6 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Udacity Developed an AI to Turn Instructor&#039;s Speech into Deepfake-Style Video, But Has No Plans to Use It - eLearningInside News<\/title>\n<meta name=\"description\" content=\"Udacity, the nanolearning provider, has recently sought to use AI technology to cut the time and effort needed to update online courses.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/news.elearninginside.com\/udacity-is-developing-an-ai-to-turn-instructors-speech-into-deepfake-style-video\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Udacity Developed an AI to Turn Instructor&#039;s Speech into Deepfake-Style Video, But Has No Plans to Use It - 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After studying English at McGill University in Montreal, he went to work full time as a freelancer while living abroad in countries such as Greece, New Zealand, and Vietnam. His journalism has been published by CKUT 90.3 FM, Montreal Rampage, Potent, and HNGN. He has also produced a series of audio interviews concerning Canadian poetry for Vallum: Contemporary Poetry. His latest work is Code Burst, a podcast that investigates a free coding bootcamp in the Appalachian region of the U.S. that seeks to retrain ex-coal miners for jobs in the tech industry, along with the promise learning to code offers more broadly. 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