Dev and Doc: AI For Healthcare Podcast

• #28 AI agents explained - Manus AI, computer control, Agentic workflows (healthcare)

  AI agents are here, but how did we get here in the first place? How do we build and leverage AI agents for high stakes domains like healthcare? In this episode of Dev and Doc, we go deep into the forest that is AI agents and computer control - starting from the "caveman" era of LLMs discovering tools, to cultivating intelligent models and agentic workflows. We dissect everyday agents like MANUS AI, and deep dive into how, where and when AI agents should be used. Are these agents hype or hope, is this actually the second deepseek moment?👋 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 :)Episode Timestamps:00:00 Highlight3:13 start / intro5:20 LLM's caveman era - tool usage6:46 Agents have autonomy and interact with environment11:15 workflows and agentic flows15:30 when should you be using an agent?24:27 vibe coding is like driving a car29:07 Demo - MANUS gathering financial trends, computer control35:55 Demo MANUS AI- website creation for Autism Assessment49:05 computer control factions- Freedom vs Process automation55:00 Autism website testing59:13 summary + endHosts:👨🏻‍⚕️Doc - Dr. Joshua Au Yeung - https://www.linkedin.com/in/dr-joshua-auyeung/🤖Dev - Zeljko Kraljevic https://twitter.com/zeljkokrFind us on:YT - https://youtube.com/@DevAndDocSpotify - https://podcasters.spotify.com/pod/show/devanddocApple- https://podcasts.apple.com/gb/podcast/dev-and-doc-ai-for-healthcare-podcast/id1751495120Substack- https://aiforhealthcare.substack.com/For enquiries:📧[email protected]:🎞️ Editor- Dragan Kraljević https://www.instagram.com/dragan_kraljevic/🎨Brand design and art direction - Ana Grigorovici https://www.behance.net/anagrigorovici027d

  --------  

  1:00:48
• #27 Exploring Claude Sonnet 3.7 for healthcare

  body{font-family:sans-serif;color:#fff;background:#121212;margin:0;padding:10px}p{margin:8px 0}h1{font-size:18px;margin:10px 0}.note{background:#535353;padding:10px;border-radius:4px;margin:10px 0}.timestamps span{color:#1DB954;font-weight:bold}a{color:#1DB954;text-decoration:none}Can Claude perform a range of complex clinical tasks? Dev and Doc are here to investigate.Claude sonnet 3.7 was released less than 48 hours ago, the model is highly intelligent and is one of the best we have seen in recent memory. Definitely passes the vibe check.We give some amazing examples of coding with claude with few shot prompts, and cover technical and clinical evaluations and share our first thoughts. We even tested claude to take a patient history!NB - PLEASE don't do this at home, obviously this is a demo and we do not in any way condone or recommend using an LLM as your doctor or healthcare provider, we are just demonstrating what the future could be. If you are sick, please seek a medical professional.👋 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 :)TIMESTAMPS00:00 start + highlights01:54 Introduction08:54 Benchmarks, state of the art14:44 guardrails, refusals, AI safety and catastrophic risks22:36 show and tell- great for coding and make video games!26:54 example hospital runner30:17 Medical use cases- clinical coding, biomedical entity extraction37:04 only medical example in Claude model card- still hallucinating citations38:37 making an anatomy app40:10 forecasting clinical diagnoses43:36 taking a medical history from a patient53:33 wrap up👨🏻‍⚕️Doc - Dr. Joshua Au Yeung - linkedin.com/in/dr-joshua-auyeung🤖Dev - Zeljko Kraljevic twitter.com/zeljkokrYT:youtube.com/@DevAndDocSpotify:podcasters.spotify.com/pod/show/devanddocApple:podcasts.apple.com/gb/podcast/dev-and-doc-ai-for-healthcare-podcast/id1751495120Substack:aiforhealthcare.substack.comFor enquiries - 📧 [email protected]🎞️ Editor - Dragan Kraljević instagram.com/dragan_kraljevic🎨 Brand design - Ana Grigorovici behance.net/anagrigorovici027d

  --------  

  58:03
• #26 Is it still worth doing a PhD in 2025? (Computer Science / Machine Learning)

  Is it still worth doing a PhD in 2025? Is the academic system broken in this publish-or-perish landscape? When is a PhD not worth pursuing? About this Episode In this Dev and Doc episode, Zeljko (now associate professor!) and Josh (doctor, PhD drop out) talk about the good and the bad of PhD life. They provide insight into the academic world with a focus on computer science and machine learning. 👋 Connect With Us! 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 :) 🎙️ Hosts 👨🏻‍⚕️ Doc - Dr. Joshua Au Yeung - LinkedIn 🤖 Dev - Zeljko Kraljevic - Twitter ⏳ Timestamps 00:00 - Start and highlight 01:42 - Intro 03:11 - What made you pursue PhD in the first place 05:05 - Industry or PhD first 10:00 - Positives - Moonshots 17:03 - Positives - Access to world experts and collaboration 20:55 - Positives - Open source and open science 24:49 - Positives - A good environment enables a smooth PhD 27:04 - Negatives - You are a one-man show 31:33 - Negatives - Publish or Perish 45:44 - Bring your research closer to the audience through blogs and other media, journals are legacy media 51:20 - Verdict - Is a PhD still worth it in 2025? 📢 Follow Us LinkedIn Newsletter YouTube Spotify Apple Podcasts Substack 📧 Contact Us For enquiries - [email protected] 🎞️ Video Production 🎬 Editor - Dragan Kraljević - Instagram 🎨 Brand Design & Art Direction - Ana Grigorovici - Behance

  --------  

  56:41
• #25 Testing Deepseek R1 on Complex Medical Tasks. Here's what we found. (GRPO explainer)

  Dev and Doc put Deepseek R1 to the test in a technical and clinical deep dive. 👋 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 :) 👨🏻‍⚕️Doc - Dr. Joshua Au Yeung - https://www.linkedin.com/in/dr-joshua-au-yeung/ 🤖Dev - Zeljko Kraljevic https://twitter.com/zeljkokr TIMESTAMPS 00:00 Highlights 04:36 Intro 08:29 response from OpenAI, Anthropic- model training costs, tightening restrictions on China, pricing wars 13:13 what an open-source deepseek means for the world. 15:38 Sam altman and Dario amodei feeling the pressure 23:10 TECHNICAL deep dive - RLHF, ppo, dpo 37:08 GRPO, R1s secret sauce 45:02 the aha moment, learning like a human? 50:25 deepseek R1 training and controversy 59:08 deepseek healthcare evaluation - Ethnic Bias 1:06:17 The diagnostic acid test (fail) 1:12:46 Coding clinical data / Medical billing (shout out SNOMED) LinkedIn Newsletter https://www.linkedin.com/build-relation/newsletter-follow?entityUrn=7216474068085026817 YT - https://youtube.com/@DevAndDoc Spotify - https://podcasters.spotify.com/pod/show/devanddoc Apple- https://podcasts.apple.com/gb/podcast/dev-and-doc-ai-for-healthcare-podcast/id1751495120 Substack- https://aiforhealthcare.substack.com/ For enquiries - 📧[email protected] 🎞️ Editor- Dragan Kraljević https://www.instagram.com/dragan_kraljevic/ 🎨Brand design and art direction - Ana Grigorovici https://www.behance.net/anagrigorovici027d

  --------  

  1:20:45
• #24 Significantly advancing LLMs with RAG (Google's Gemini 2.0, Deep Research, notebookLM)

  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 - [email protected] 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

  --------  

  57:46

Más podcasts de Ciencias

Podcasts a la moda de Ciencias

Acerca de Dev and Doc: AI For Healthcare Podcast