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Google Gemini proves a better health coach than humans

Google researchers introduce the Personal Health Large Language Model, a version of Gemini fine-tuned to reason on data from wearables.

These devices provide a “rich and longitudinal source of data” for personal health monitoring that is “passively and continuously acquired” from inputs including exercise and diet logs, mood journals and sometimes even social media activity, the Google researchers point out. Meanwhile, when asked a question about what type of muscular contraction occurs in the pectoralis major “during the slow, controlled, downward phase of a bench press.” Given four choices for an answer, PH-LLM correctly responded “eccentric.” “Our study shows that PH-LLM is capable of integrating passively-acquired objective data from wearable devices into personalized insights, potential causes for observed behaviors and recommendations to improve sleep hygiene and fitness outcomes,” the researchers write.

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