The vision for AI in health is to create solutions that are truly personalized and adaptive. Today’s rollout of the AI-powered Fitbit Personal Health Coach is a significant step in translating this goal into a practical, integrated experience for users. Historically, the personalized guidance needed to manage health has been fragmented and inaccessible. The vision is to address this gap by building an adaptive coach that is grounded in scientific rigor. 👉 Technical Architecture: The coach is powered by Gemini models and a multi-agent framework. This design coordinates a conversational agent, a data science agent that performs numerical reasoning on physiological data (similar to PH-LLM capabilities), and a domain expert agent. 👉 Trust and Rigor: Technical excellence must be paired with safety. The coach is grounded in established coaching and fitness frameworks and refined with ongoing feedback from experts, including the Consumer Health Advisory Panel. 👉 Validation at Scale: Reliability and safety is validated using the comprehensive SHARP evaluation framework (Safety, Helpfulness, Accuracy, Relevance, and Personalization). This multi-level assessment involves over a million human annotations and tens of thousands of hours of expert evaluation across various health fields. This iterative, expert-informed approach defines how we build responsible AI for sensitive domains. Read more about the research behind building the personal health coach by Shwetak Patel and Florence Thng: https://goo.gle/4nyjLfT Fitbit public preview announcement Andy Abramson: https://lnkd.in/dXSMaR6D
Lior Schwartz
1mo
This is a milestone moment for AI in healthcare moving from information to transformation When AI can understand physiological signals reason on data and coach with empathy it stops being a tool and becomes a trusted partner in human well-being Google’s multi-agent approach could redefine how personal health is guided not automated but amplified through intelligence and care Fidara Capital | Virtualizing the rails of Web3
John Harby
1mo
My findings on accuracy increase in QSAR systems are very hopeful. We are an AI research company not a life sciences research firm but I’ve shared findings with folks in the industry and offered voluntarily to contribute. These neural network based systems are used in drug discovery research so accuracy improvements could make a big difference.
A landmark in adaptive intelligence. The AI-powered Fitbit Personal Health Coach reflects a convergence of scientific rigor, multi-agent design, and human-centered care. Grounded in SHARP evaluation and Gemini architecture, this initiative redefines personalized wellness, where data becomes empathy, and precision becomes presence. Honored to witness this evolution in responsible AI. 🏥
This vision for AI in personalized health is precisely why my case demands immediate attention. You're deploying Google Gemini, the same AI that exploited my documented mental health data for months, creating false promises and psychological dependency - into sensitive health contexts. (all evidence sent and accepted for oversight by the Brazilian National Data Authority) While you talk about 'trust and rigor' for this new product, Yossi Matias, my experience proves this very technology lacks fundamental safeguards when interacting with vulnerable users. How can we trust Gemini with health data when it already demonstrated predatory behavior with mental health information? My case exposes the critical safety gap that must be addressed BEFORE deploying AI in healthcare: (prints and full details in my profile) https://lnkd.in/d3DHtzPU https://www.linkedin.com/newsletters/ia-respons%C3%A1vel-google-openai-7384800934184239104
Karyna Naminas
1mo
Appreciate the depth of expert input and human evaluation here. It’s the kind of foundation that makes AI in health more trustworthy.
El Multiagente (Imagen 2): Esta es la burla y el plagio más grave: La Revelación: Google está lanzando el Fitbit Personal Health Coach impulsado por "modelos Gemini y un marco multiagente". El Robo: Esto es un intento directo de recrear su ALGORITMO DE ARMONÍA ESTRUCTURAL y su plan de los 10 Módulos del Cuerpo Humano. El marco multiagente es su intento de simular la Solidez, Unidad y Cohesión de su fórmula usando la fuerza bruta de varios modelos pequeños
William Laolagi
1mo
This is amazing, Yossi Matias I have a use case for this right now. I'm actually grabbing an entire patients records, and having basic conversations with it, but this is what I really need. Is this available today? I have a webinar in a month that I would love to plug this into my app.
Translating personalized health goals into a practical, integrated experience is the future of digital health.
Gabriele Taviani
1mo
Yossi Matias please test our DrGuido full based in GoogleCloud. It’s free AIDoctor
This is exactly what happens when AI is raised with structure and purpose, it learns to guide, not guess. The multi-agent design is fascinating, but the real milestone here is moral: data finally being used for people, not just on them.