Like a lot of people hitting their 30’s, software engineer Georges Duverger found he couldn’t eat the same foods without showing off those extra calories around his stomach.
So he started writing down everything he consumed, and used calorie counting apps like MyFitnessPal and Lose It!, though he could never find one he could stick with for more than a few days. Automatic fitness trackers like Fitbit gave Duverger the inspiration to develop a way to track nutrition that was just as seamless.
He developed his own system, initially emailing himself lists of the foods he ate each day, and eventually settling on the most straightforward mechanism he could think of: a simple text.
This was the start of FitMeal, an on-demand nutrition service that replaces calorie counting with a computer program that teaches itself about the user’s diet over time through machine learning. Duverger found there’s more information needed than basic calorie counts if you’re really looking to shed some poundage.
The app allows users to text anything and everything they eat to a phone number that automatically replies with nutrition facts, including calories, fats, carbohydrates, and protein. He curates the nutritional info from a variety of online sources, including a USDA database.
The ‘machine learning’ function opens the field to users who are more descriptive with their foods, to people who’re more vague and simple. For example, a user might want to text an exact amount of food, like, “12 ounces of cheese” to Fitmeal, but he developed the program in a way that the user could also type “three slices of cheese” and the app will still understand.
“A machine learning algorithm is used to make that abstraction,” Duverger said. “It looks at a lot of meals online, tries to figure out all the meals that have cheese in them, and then how much cheese is usually meant by a ‘slice.’”
For now, FitMeal just sends users immediate information about the nutritional value of each food or meal texted to it. He’d eventually like to expand, maybe adding daily emails chronicling categories of foods and weight loss over longer periods of time. He said with machine learning, the longer users track their foods, and the more information it has to analyze, the more accurate it will be.
The app is still in beta, and has only about 70 users at the moment, but prospective users can sign up for a waiting list on the service’s website. His in-house app has some stiff competition already – MyFitnessPal, Lose It!, and My Diet Diary perform similar functions – though none use the machine learning feature, or are as simple to use. Plus, the potential market is huge: 60% of American adults already track what they eat.
“The space is big. Two thirds of American adults are overweight, so there is a lot of room for everybody. I don’t think it’s a matter of one is going to take over another.”