Episode Details
EPISODE INFO
- Released
- May 18, 2023
- Duration
- 42m
- Channel
- No Priors
- Watch on YouTube
- ▶ Open ↗
EPISODE DESCRIPTION
What if AI could revolutionize healthcare with advanced language learning models? Sarah and Elad welcome Karan Singhal, Staff Software Engineer at Google Research, who specializes in medical AI and the development of MedPaLM2. On this episode, Karan emphasizes the importance of safety in medical AI applications and how language models like MedPaLM2 have the potential to augment scientific workflows and transform the standard of care. Other topics include the best workflows for AI integration, the potential impact of AI on drug discoveries, how AI can serve as a physician's assistant, and how privacy-preserving machine learning and federated learning can protect patient data, while pushing the boundaries of medical innovation. 00:00 - Introduction 00:22 - Google's Medical AI Development 08:57 - Medical Language Model and MedPaLM 2 Improvements 18:18 - Safety, cost/benefit decisions, drug discovery, health information, AI applications, and AI as a physician's assistant. 24:51 - Privacy Concerns - HIPAA's implications, privacy-preserving machine learning, and advances in GPT-4 and MedPOM2. 37:43 - Large Language Models in Healthcare and short/long term use.
SPEAKERS
Sarah Guo
hostKaran Singhal
guestElad Gil
host
EPISODE SUMMARY
In this episode of No Priors, featuring Sarah Guo and Karan Singhal, No Priors Ep. 17 | With Karan Singhal explores google’s Med-PaLM 2 Aims to Safely Transform Healthcare With AI Karan Singhal, a lead researcher on Google’s Med-PaLM 2, explains how large language models are being adapted for high‑stakes medical use, with a focus on safety, accuracy, and responsible deployment. He traces the evolution from PaLM to PaLM 2 and Med-PaLM, detailing methods like instruction prompt tuning and improved pretraining objectives. The discussion digs into evaluation challenges, regulatory and privacy barriers, and why medical workflows can be a powerful testbed for AI alignment and safety research. Looking ahead, Singhal expects LLMs to raise the global standard of care, augment clinicians and scientists, and help solve key scientific and medical problems—if society can set realistic, benefit-aware safety bars.
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