Delighted to see our real-world clinical study of a conversational diagnostic AI system published in @TheLancet, alongside coverage in @nytimes last week. Looking back, AI in medicine might feel inevitable but it actually takes deliberate, uncertain leaps to get there. I have been fortunate to be part of two such moments. The first was early 2022 (pre ChatGPT) when @alan_karthi and I got access to our first @Google LaMDA and PaLM models. That convinced us to go all in on LLMs in medicine, sparking the Google Brain moonshot leading to Med-PaLM. The second moment leading directly to this Lancet study, was late summer 2023. @taotu831 showed me the early AMIE models he was training with our self-play loop, targeting our upcoming OSCE study with patient actors, later published in @Nature 2025. At that exact time, I was navigating a personal health condition. Testing myself, the consultation the AI performed was so natural and clinically sound that I was convinced it was ready for the real world. So I reached out to Alan and together with the team we asked how we could test this in the real world quickly, safely and responsibly. We needed a prospective clinical trial with a safety endpoint and all roads led to @AdamRodmanMD at @bethisraellahey @harvardmed . Adam was incredibly gracious with his time kicking off our first discussions in the fall of 2023. But clinical trials take a long time; years of painstaking work. There are so many critical people and moments that make them happen, far beyond the glitzy PR materials and the main authors. - For example, a discussion with @greg_corrado sparked the design of the oversight setup underpinning the safety layer in the study. - Kavita Kulkarni (now at BioHub) spent months negotiating the initial contracts with BIDMC; it was uncharted territory for both organizations. - @_khaledsaab (now rocking at OpenAI!) working tirelessly to improve the AI, together with @taotu831, @apalepu13, @RyutaroTanno, @ckbjimmy, @valentinlievin, @elahevedadi and many more folks. - @Mysiak, Alessio Orlandi, Petar Sirkovic and team sharing the seamless serving infrastructure they built for Co-Scientist, which we could re-use for much of this study. - @SSaraMahdavi making sure the study team was well organized :) This is just to name a few. Prospective trials are a massive team sport and I am proud of what our teams achieved. While the AI's clinical reasoning was strong, seeing the patient trust, safety, and satisfaction data, with ZERO safety stops from our supervising physicians, is what truly stands out. At the same time, this is still a stepping stone. We are moving from AI as a tool to an active care team member - a guardian angel amplifying clinicians and staying with patients throughout their health journey. More to come soon, and as always, a pleasure to work with so many great folks across @GoogleDeepMind , @GoogleResearch and @bethisraellahey . Paper - NYT -

Grok 4.7 is officially out. Handles longer tasks and checks its work more carefully. Same pricing as 4.6, but with stronger results across coding, terminal work, engineering and clinical reasoning benchmarks. Terminal-Bench went from 20.3% to 38.0%.

Grok 4.6 just broke into the Top 3 on the Artificial Analysis Healthcare & Medical Index Grok 4.6 (high) scores 50 - just ONE point off the top score of 51 It outperforms GPT-5.6 Sol, Kimi K3 and Gemini 3.7 Flash This index measures how models actually handle healthcare and medical work: • Medical and health knowledge • Clinical reasoning • Patient documentation • Non-hallucination • Agentic workflows Healthcare is one of the highest-stakes domains you can test an AI on And Grok is now competing at the very top of it