A look at Google's Med-PaLM 2, an AI chatbot for answering medical questions and more; sources say testing began in April 2023 with the Mayo Clinic and others
Breaking: Foxconn walks away from a $19.5B joint venture with conglomerate Vedanta to produce semiconductors. Steve Dent / Engadget : Google is testing its medical AI chatbot at the Mayo Clinic Usama Jawad / XDA Developers : Your next medical consultation could be assisted by Google's AI chatbot Wes Davis / The Verge : Google's medical AI chatbot is already being tested in hospitals Danny D'Cruze / Business Today : AI doctors? Google already testing AI chatbots similar to Bard, ChatGPT in hospitals Analytics Insight : Google To Test AI Chatbot That Is Trained to Answer Medical Questions PCMag : Google's Medical Chatbot is Being Tested in Hospitals The Economic Times : Google testing AI chatbot to expertly answer medical questions Matthias Bastian / The Decoder : Google is field-testing its generative medical language model in a clinical setting Shweta Ganjoo / Techlusive : Google is testing a AI-model to answer all your health-related questions Twitter: Glenn Gabe / @glenngabe :
Context & Ripple Effects
Google had already expanded the underlying PaLM 2 model across its products, while Google Cloud and Mayo Clinic had partnered to test tools for chatbot and search applications. Med-PaLM 2 brings that model lineage into a hospital-testing setting rather than a general-purpose product rollout.
The development also sits alongside hospitals’ experiments with GPT-3 for answering online queries, making the focus on medical-question assistants part of an emerging operational use case rather than an isolated research project.
First-order effects
- Google and participating hospitals, including Mayo Clinic, can evaluate Med-PaLM 2 in real clinical environments, with hospital workflows and medical questions shaping what is tested.
- The Mayo relationship extends from a Google Cloud chatbot and search-app testing partnership to evaluation of a specialized medical assistant.
Second-order effects
- Hospital pilots make performance, workflow fit, and assurance central differentiators for medical AI vendors, rather than model capability alone.
- The tests add competitive pressure on providers of general-purpose models already being tried for patient-query work, including GPT-3 hospital experiments for online responses.
Third-order effects
- If hospital testing expands, medical AI assistants could become a distinct enterprise layer between general-purpose foundation models and frontline clinical workflows, with validation and deployment controls determining adoption.
- The pattern points toward healthcare buyers treating AI assistants as operational systems requiring ongoing evaluation, not simply as standalone chatbots.
The trend: Healthcare AI is moving from broad language-model demonstrations toward tightly scoped, institution-tested assistants embedded in clinical information workflows.