The Verge describes using an AI "digital twin" to guide meals

In short: A writer at The Verge says she has been using an AI “digital twin” for about 100 days to predict how different foods may affect her blood sugar.

What's going on

The Verge published a first-person column by reporter Victoria Song about testing a “digital twin” for metabolism. A digital twin is a software copy of something real, like a flight simulator for your body.

In her routine, Song “feeds” the digital twin daily with health information, including body composition (a breakdown like body fat and muscle) from a smart scale. She also logs things like lemon water, medications, and sometimes blood pressure.

The system is built around metabolic data, especially glucose, which is blood sugar. It also uses a continuous glucose monitor, a small wearable sensor that tracks glucose throughout the day. The app then labels foods with simple colors that aim to predict her glucose response, like a traffic light, where green is best.

Song gives an example: protein cereal with milk shows up as “orange” if eaten alone, but “green” if she takes her daily walk after. She also notes that these tools could someday be used not just for food choices, but possibly for predicting how someone might respond to medicines.

What to watch

These tools depend on lots of personal health data, and they are still early. A key question is how accurate the predictions are for different people, and how clearly companies explain what the system can and cannot do.

Source: The Verge AI