Abstract: In recent years, the field of AI has been revolutionized by the emergence of Transformers and Large Language Models. However, perhaps nowhere is their impact likely to be more profound than in the biomedicine where they have the potential to act as care multipliers, help improve our understanding of biology and solve the burden of diseases. In this talk, I will introduce recent works from my team at Google AI, Med-PaLM, Med-PaLM 2, Med-PaLM M and AMIE which I believe are key milestones towards such a future. Med-PaLM and Med-PaLM 2 were the first AI systems to obtain passing and expert level scores on US Medical License exam questions respectively, a long standing grand challenge in AI. Med-PaLM M was the first demonstration of a generalist, multimodal, biomedical AI system. More recently, two recent studies highlight AMIE's promising capabilities. In a double-blind, randomized study, AMIE performed competitively against Primary Care Physicians in text consultations. Additionally, a separate study demonstrated AMIE's significant assistive potential for clinicians facing complex diagnostic challenges.

I will outline the motivation, principles and technical innovations underpinning these systems. Finally, I will sketch out a vision for how we might be able to leverage such powerful systems to help scale world class healthcare to everyone and make medicine a humane endeavor again.

Speaker Bio: Vivek Natarajan is a Research Scientist at Google leading research at the intersection of large language models (LLMs) and biomedicine. In particular, Vivek is the lead researcher behind Med-PaLM and Med-PaLM 2, which were the first AI systems to obtain passing and expert level scores on US Medical License exam questions respectively. Med-PaLM was recently published in Nature and has been featured in The Scientific American, Wall Street Journal, The Economist, STAT News, CNBC, Forbes, New Scientist among others. More recently, Vivek also led the development of Med-PaLM M, the first demonstration of a generalist biomedical AI system and AMIE, a research AI system, which surpassed Primary Care Physicians on multiple axes pertaining to diagnostic dialogue including diagnostic accuracy, clinical communication, empathy and rapport building with the patient.

Over the years, Vivek's research has been published in well-regarded journals and conferences like Nature, Nature Medicine, Nature Biomedical Engineering, JMLR, CVPR, ICCV and NeurIPS. It also forms the basis for several regulated medical device products under clinical trials at Google, including the NHS AI award winning breast cancer detection system Mammo Reader and the skin condition classification system DermAssist. Prior to Google, Vivek worked on multimodal assistant systems at Facebook AI Research and published award winning research, was granted multiple patents and deployed AI models to products at scale with hundreds of millions of users.