[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"nav-categories":3,"article-there-s-a-humongous-problem-with-ai-models":70},{"data":4},[5,37,57,64],{"name":6,"slug":7,"categories":8},"Productivity","productivity",[9,13,17,21,25,29,33],{"id":10,"title":11,"slug":12},17,"Branding","branding",{"id":14,"title":15,"slug":16},19,"Marketing","marketing",{"id":18,"title":19,"slug":20},20,"Work","work",{"id":22,"title":23,"slug":24},34,"Community","community",{"id":26,"title":27,"slug":28},21,"For newbies","for-newbies",{"id":30,"title":31,"slug":32},24,"Investment","investment",{"id":34,"title":35,"slug":36},22,"Finance","finance",{"name":38,"slug":39,"categories":40},"Tech","tech",[41,45,49,53],{"id":42,"title":43,"slug":44},28,"Technology","technology",{"id":46,"title":47,"slug":48},32,"Artificial Intelligence","artificial-intelligence",{"id":50,"title":51,"slug":52},26,"Security and protection","security-and-protection",{"id":54,"title":55,"slug":56},31,"YouTube Blog","youtube-blog",{"name":58,"slug":59,"categories":60},"News","news",[61],{"id":62,"title":58,"slug":63},18,"quasanews",{"name":65,"slug":66,"categories":67},"Business","business",[68],{"id":69,"title":65,"slug":66},16,{"post":71,"published_news":92,"popular_news":159,"categories":230},{"title":72,"description":73,"meta_title":72,"meta_description":73,"meta_keywords":74,"text":75,"slug":76,"created_at":77,"publish_at":78,"formatted_created_at":79,"category_id":46,"links":80,"view_type":84,"video_url":82,"views":85,"likes":86,"lang":87,"comments_count":86,"category":88},"There’s a Humongous Problem With AI Models","A new study highlights a glaring hole in AI models' ability to learn new information: turns out, they can't!","Humongous Problem With AI Models, artificial intelligence","\u003Cp>Hello!\u003C/p>\n\n\u003Cp>A new study highlights a glaring hole in \u003Ca href=\"https://quasa.io/media/will-artificial-intelligence-gives-numerous-advantages-to-an-organization\">AI\u003C/a> models&#39; ability to learn new information: turns out, they can&#39;t!\u003C/p>\n\n\u003Cp>\u003Cpicture class=\"image-align-left\">\u003Csource srcset=\"https://cdn.quasa.io/photos/foto-20/aidata-2.webp\" type=\"image/webp\">\u003Cimg alt=\"There’s a Humongous Problem With AI Models\" class=\"image-align-left\" height=\"183\" src=\"https://cdn.quasa.io/photos/foto-20/aidata-2.jpeg\" width=\"275\" />\u003C/picture>According to the study, conducted by a team of scientists at Canada&#39;s University of Alberta and&nbsp;published this week&nbsp;in the journal&nbsp;\u003Cem>Nature\u003C/em>, AI algorithms trained via deep learning &mdash; in short, \u003Ca href=\"https://quasa.io/media/what-are-the-benefits-and-risks-of-artificial-intelligence\">AI\u003C/a> models like large language models built by finding patterns in heaps of data &mdash; fail to work in &quot;continual learning settings,&quot; or when new concepts are introduced to a model&#39;s existing training.\u003C/p>\n\n\u003Cp>In other words, if you want to teach an existing deep learning model something new, you&#39;ll likely have to retrain it from the ground up &mdash; otherwise, according to the research, the artificial neurons in their proverbial minds will sink to a value of zero. This results in a loss of &quot;plasticity,&quot; or their ability to learn at all.\u003C/p>\n\n\u003Cp>&quot;If you think of it like your brain, then it&#39;ll be like 90 percent of the neurons are dead,&quot; University of Alberta computer scientist and lead study author Shibhansh Dohare&nbsp;told&nbsp;\u003Cem>New Scientist\u003C/em>. &quot;There&#39;s just not enough left for you to learn.&quot;\u003C/p>\n\n\u003Cp>\u003Cpicture class=\"image-align-left\">\u003Csource srcset=\"https://cdn.quasa.io/photos/foto-20/aidata-1.webp\" type=\"image/webp\">\u003Cimg alt=\"There’s a Humongous Problem With AI Models\" class=\"image-align-left\" height=\"170\" src=\"https://cdn.quasa.io/photos/foto-20/aidata-1.jpeg\" width=\"297\" />\u003C/picture>And training advanced AI models, as the researchers point out, is a cumbersome and wildly expensive process &mdash; making this a major financial obstacle for AI companies, which burn through a ton of cash as it is.\u003C/p>\n\n\u003Cp>&quot;When the network is a large language model and the data are a substantial portion of the internet,&quot; reads the study, &quot;then each retraining may cost millions of dollars in computation.&quot;\u003C/p>\n\n\u003Ch4>\u003Cstrong>Obstacles Course\u003C/strong>\u003C/h4>\n\n\u003Cp>This phenomenon of plasticity loss is also a major moat between current AI models and the imagined &quot;artificial general intelligence,&quot; or a theoretical AI that would be considered generally as intelligent as humans.\u003C/p>\n\n\u003Cp>After all, in human terms, this would be like if we had to fully reboot our brains from scratch every time we took a new college course, lest we nuke most of our neurons.\u003C/p>\n\n\u003Cp>\u003Cpicture class=\"image-align-left\">\u003Csource srcset=\"https://cdn.quasa.io/photos/foto-20/aidata-8.webp\" type=\"image/webp\">\u003Cimg alt=\"There’s a Humongous Problem With AI Models\" class=\"image-align-left\" height=\"169\" src=\"https://cdn.quasa.io/photos/foto-20/aidata-8.jpg\" width=\"300\" />\u003C/picture>If there&#39;s any bright spot for \u003Ca href=\"https://quasa.io/media/artificial-intelligence-and-humans-as-partners-of-work-can-it-be-done\">AI \u003C/a>companies? Excitingly, the study authors were able to create an algorithm with the power to randomly revive certain damaged or &quot;dead&quot; AI neurons, which showed some success in countering the plasticity problem.\u003C/p>\n\n\u003Cp>Still, as it stands, a practical solution is still out of reach.\u003C/p>\n\n\u003Cp>&quot;A solution to continual learning is literally a billion-dollar question,&quot; Dohare told&nbsp;\u003Cem>New Scientist\u003C/em>. &quot;A real, comprehensive solution that would allow you to continuously update a model would reduce the cost of training these models significantly.&quot;\u003C/p>\n\n\u003Cp>Thank you!\u003Cbr />\nJoin us on social media!\u003Cbr />\nSee you!&nbsp;\u003C/p>","there-s-a-humongous-problem-with-ai-models","2024-10-14T13:54:11.000000Z","2024-10-14T12:30:00.000000Z","14.10.2024",{"image":81,"image_webp":82,"thumb":83,"thumb_webp":83},"https://cdn.quasa.io/images/news/n2zehPPHfF11e4ghl2nlCSFm6xlROmmVh6YVTPyf.webp",null,"https://cdn.quasa.io/thumbs/news-thumb/images/news/n2zehPPHfF11e4ghl2nlCSFm6xlROmmVh6YVTPyf.webp","small",1339,0,"en",{"id":46,"title":47,"slug":48,"meta_title":47,"meta_description":89,"meta_keywords":89,"deleted_at":82,"created_at":90,"updated_at":91,"lang":87},"Artificial Intelligence, ai, ml, machine learning, chatgpt, future","2024-09-22T08:08:27.000000Z","2024-09-23T12:49:38.000000Z",[93,108,120,133,146],{"title":94,"description":95,"slug":96,"created_at":97,"publish_at":98,"formatted_created_at":99,"category":100,"links":101,"view_type":84,"video_url":82,"views":106,"likes":86,"lang":87,"comments_count":86,"is_pinned":107},"GitHub’s AI Agent Tsunami: 275 Million Commits a Week, 14 Billion Projected for 2026 — And the Platform Is Starting to Crack","GitHub just hit numbers that would have sounded like science fiction twelve months ago.","github-s-ai-agent-tsunami-275-million-commits-a-week-14-billion-projected-for-2026-and-the-platform-is-starting-to-crack","2026-04-17T17:10:50.000000Z","2026-04-20T11:57:00.000000Z","20.04.2026",{"title":58,"slug":63},{"image":102,"image_webp":103,"thumb":104,"thumb_webp":105},"https://cdn.quasa.io/images/news/XZTYmDGdaBEeRqB4Fv56AeOVoRtMa9PgoABzA3uj.jpg","https://cdn.quasa.io/images/news/XZTYmDGdaBEeRqB4Fv56AeOVoRtMa9PgoABzA3uj.webp","https://cdn.quasa.io/thumbs/news-thumb/images/news/XZTYmDGdaBEeRqB4Fv56AeOVoRtMa9PgoABzA3uj.jpg","https://cdn.quasa.io/thumbs/news-thumb/images/news/XZTYmDGdaBEeRqB4Fv56AeOVoRtMa9PgoABzA3uj.webp",15,false,{"title":109,"description":110,"slug":111,"created_at":112,"publish_at":113,"formatted_created_at":99,"category":114,"links":115,"view_type":84,"video_url":82,"views":42,"likes":86,"lang":87,"comments_count":86,"is_pinned":107},"Time’s Up for SaaS: Grow Faster or Disappear","The public markets have spoken — and the verdict is brutal. 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