{"id":23074,"date":"2024-03-12T10:55:26","date_gmt":"2024-03-12T09:55:26","guid":{"rendered":"https:\/\/ggba.swiss\/?p=23074"},"modified":"2024-03-12T11:00:48","modified_gmt":"2024-03-12T10:00:48","slug":"epfl-unveils-a-modular-ai-model-for-diverse-data-analysis","status":"publish","type":"post","link":"https:\/\/ggba.swiss\/en\/epfl-unveils-a-modular-ai-model-for-diverse-data-analysis\/","title":{"rendered":"EPFL unveils a modular AI model for diverse data analysis"},"content":{"rendered":"\n<p>In contrast to Large Language Models (LLMs) like OpenAI&#8217;s ChatGPT, which are built on vast textual databases, EPFL\u2019s new model, dubbed MultiModN, is tailored for the next-generation Multimodal Models (MMs) sphere. These MMs excel by learning from a variety of data types, yet smaller-scale models face hurdles, notably in handling non-random missing information without absorbing biased patterns. MultiModN emerges as a pioneering solution to this challenge.<\/p>\n\n\n\n<p>Developed under the stewardship of Professors Mary-Anne Hartley and Tanja K\u00e4ser, MultiModN is structured around numerous smaller, self-sufficient modules. This architecture allows for the selection and sequencing of modules based on available data, culminating in a highly adaptable and interpretable model. Tested across ten real-world tasks, including medical diagnosis support and academic performance prediction, MultiModN has demonstrated its robustness and interpretability, especially in scenarios marred by Missing Not At Random (MNAR) data.<\/p>\n\n\n\n<p>The model&#8217;s inaugural application focuses on enhancing clinical decision-making in resource-constrained environments. MultiModN&#8217;s inherent flexibility and bias-resistant learning mechanism make it ideally suited for healthcare settings where data gaps are prevalent due to economic or redundancy factors. By leveraging real-world clinical data without inheriting its biases, MultiModN aims to support medical personnel by adjusting its predictions based on the available inputs.<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">Aligning machine learning advancements with societal needs<\/h4>\n\n\n\n<p>Beyond publication, efforts are underway to translate MultiModN from laboratory to practical use, with collaborations between <a href=\"https:\/\/www.epfl.ch\/en\/\">EPFL<\/a>, Lausanne University Hospital (<a href=\"https:\/\/www.chuv.ch\/fr\/chuv-home\/\">CHUV<\/a>), and <a href=\"https:\/\/www.insel.ch\/fr\/\">University Hospital Bern<\/a>, focusing on diagnosing pneumonia and tuberculosis in low-resource regions. A comprehensive data collection initiative is also in progress, aiming to train MultiModN with real-world, multimodal data reflective of conditions in low-resource settings.<\/p>\n\n\n\n<p>This development represents EPFL&#8217;s continued commitment to aligning machine learning advancements with societal needs. Alongside <a href=\"https:\/\/actu.epfl.ch\/news\/epfl-s-new-large-language-model-for-medical-knowle\/\">Meditron<\/a>, another top-performing open-source LLM for clinical decision support, MultiModN embodies EPFL&#8217;s vision for responsible AI that fosters technological innovation across various societal sectors, underscored by the ethos of the new <a href=\"https:\/\/www.epfl.ch\/research\/domains\/ai\/\">EPFL AI Center<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Researchers at the EPFL have unveiled a groundbreaking machine learning model that could herald a new era in the versatility and application of artificial intelligence.<\/p>\n","protected":false},"author":6,"featured_media":23075,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"mc4wp_mailchimp_campaign":[],"footnotes":""},"categories":[839],"tags":[893,980,930,919,949,974,887],"class_list":["post-23074","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-tech-en","tag-artificial-intelligence","tag-big-data-en","tag-digital-health","tag-digital-transformation","tag-education-en","tag-ict","tag-software"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.2 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>EPFL unveils a modular AI model for diverse data analysis | GGBa<\/title>\n<meta name=\"description\" content=\"The EPFL has unveiled a machine learning model that could herald a new era in the versatility and application of artificial 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