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Dev and Doc: AI For Healthcare PodcastAuthor: Dev and Doc
Bringing doctors and developers together to unlock the potential of AI in healthcare. Together, we can build models that matter. Hello! We are Dev & Doc, Zeljko and Josh :) Josh is a training Neurologist in the NHS, and AI researcher in St Thomas' hospital and King's College Hospital. Zeljko is an AI engineer, and post-doctoral researcher in King's College London, as well as a CTO for a natural language processing company. ------------- Substack- https://aiforhealthcare.substack.com/ YT - https://youtube.com/@DevAndDoc Language: en Genres: Life Sciences, Science Contact email: Get it Feed URL: Get it iTunes ID: Get it |
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#24 Significantly advancing LLMs with RAG (Google's Gemini 2.0, Deep Research, notebookLM)
Episode 24
Friday, 10 January, 2025
Dev and Doc - Latest News Dev and Doc - Latest News It's 2025, Dev and Doc cover the latest news including Google's deep research and notebook LM, DeepMind's Promptbreeder, and Anthropic's new RAG approach. We also go through what retrieval augmented generation (RAG) is, and how this technique is advancing LLM performance. 👋 Hey! If you are enjoying our conversations, reach out, share your thoughts and journey with us. Don't forget to subscribe whilst you're here :) Meet the Team 👨🏻⚕️ Doc - Dr. Joshua Au Yeung - LinkedIn 🤖 Dev - Zeljko Kraljevic - Twitter Where to Follow Us LinkedIn Newsletter YouTube Spotify Apple Podcasts Substack Contact Us 📧 For enquiries - Devanddoc@gmail.com Credits 🎞️ Editor - Dragan Kraljević - Instagram 🎨 Brand Design and Art Direction - Ana Grigorovici - Behance Episode Timeline 00:00 Highlights 00:53 News - Notebook LM, OpenAI 12 days of Christmas 07:44 Change in the meta - post-training 11:34 Optimizing prompts with DeepMind Promptbreeder 13:20 Is OpenAI losing their lead against Google 16:45 Deep research vs Perplexity 24:18 AIME and oncology 26:00 Deep research results 30:20 RAG intro 33:14 Second pass RAG 36:20 RAG didn't take off 38:40 Wikichat 39:16 How do we improve on RAG? 41:11 Semantic/topic chunking, cross-encoders, agentic RAG 51:15 Google’s Problem Decomposition 53:32 Anthropic’s Contextual Retrieval Processing 56:07 Summary and wrap up References Cross Encoders Wikichat Google's Problem Decomposition Anthropic's Contextual Retrieval Google AIME in Oncology DeepMind's Promptbreeder
