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#06 Exploring Large multimodal models in healthcare - GPT-4V, Google PaLI-3 explained

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Manage episode 428686723 series 3585389
内容由Dev and Doc提供。所有播客内容(包括剧集、图形和播客描述)均由 Dev and Doc 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal
🤖Dev and doc👨🏻‍⚕️ introduces large multimodal models. ✨ The potential of LMMs combining text and images seem limitless, but what's the catch? Dev and Doc is a Podcast where developers and doctors join forces to deep dive into AI in healthcare. Together, we can build models that matter. 👨🏻‍⚕️Doc - Dr. Joshua Au Yeung - https://www.linkedin.com/in/dr-joshua-auyeung/ 🤖Dev - Zeljko Kraljevic https://twitter.com/zeljkokr 00:00 start 00:32 intro 02:20 what is multimodality? And what are the potentials? 09:43 Large multimodal models paper deep dive (radiology) 18:43 paper deep dive 2 (pathology) 20:40 large multimodal models technical overview, exploration of other LMMs 31:40 Foundational models explanation 35:18 the model transparency index 36:20 Google PaLI-3, light weight models vs large Foundational models 43:04 Summary 44:15 the problems and work to be done for LMMs - hallucinations, inconsistencies, biases, security 49:20 A call for better evidence generation and trials with LMMs 53:00 final points - improving visual spatial recognition, thoughts for future The podcast 🎙️ 🔊Spotify: https://open.spotify.com/show/3QO5Lr3w4Rd6lqwlfKDaB7?si=e7915d844994403e 📙Substack: https://aiforhealthcare.substack.com/ 🎞️ Editor- Dragan Kraljević https://www.instagram.com/dragan_kraljevic/ 🎨Brand design and art direction - Ana Grigorovici https://www.behance.net/anagrigorovici027d
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Manage episode 428686723 series 3585389
内容由Dev and Doc提供。所有播客内容(包括剧集、图形和播客描述)均由 Dev and Doc 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal
🤖Dev and doc👨🏻‍⚕️ introduces large multimodal models. ✨ The potential of LMMs combining text and images seem limitless, but what's the catch? Dev and Doc is a Podcast where developers and doctors join forces to deep dive into AI in healthcare. Together, we can build models that matter. 👨🏻‍⚕️Doc - Dr. Joshua Au Yeung - https://www.linkedin.com/in/dr-joshua-auyeung/ 🤖Dev - Zeljko Kraljevic https://twitter.com/zeljkokr 00:00 start 00:32 intro 02:20 what is multimodality? And what are the potentials? 09:43 Large multimodal models paper deep dive (radiology) 18:43 paper deep dive 2 (pathology) 20:40 large multimodal models technical overview, exploration of other LMMs 31:40 Foundational models explanation 35:18 the model transparency index 36:20 Google PaLI-3, light weight models vs large Foundational models 43:04 Summary 44:15 the problems and work to be done for LMMs - hallucinations, inconsistencies, biases, security 49:20 A call for better evidence generation and trials with LMMs 53:00 final points - improving visual spatial recognition, thoughts for future The podcast 🎙️ 🔊Spotify: https://open.spotify.com/show/3QO5Lr3w4Rd6lqwlfKDaB7?si=e7915d844994403e 📙Substack: https://aiforhealthcare.substack.com/ 🎞️ Editor- Dragan Kraljević https://www.instagram.com/dragan_kraljevic/ 🎨Brand design and art direction - Ana Grigorovici https://www.behance.net/anagrigorovici027d
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