I used to think the best AI food logging flow would be simple: Take a photo, let the model identify...
I used to think the best AI food logging flow would be simple:
Take a photo, let the model identify the meal, confirm it, done.
That works surprisingly well for a lot of meals. But while building MetricSync, I learned the awkward product truth: the best input method changes depending on what is in front of the user.
A photo is great for a plate.
A barcode is better for packaged food.
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A London startup trained an AI on 4.1 million recipes across seven languages—and the whole thing is smaller than a song file.
