How a neural network recognizes food in a photo
A photo of a plate turns into a number on the screen in a few seconds, and from the outside, it looks like a measurement.
Technology
How the things that count for you actually work: a dish recognized from a photo, the codes on a package, wristbands, scales and home tests. Where a device gives you a measurement and where it gives you a plausible guess.
Why AI confidently states incorrect figures
The unpleasant feature of machine responses is not that they can be incorrect—reference books and labels can be wrong too.
Barcode on packaging: what is encrypted in it and what is not
There is a persistent belief about barcodes: that you can supposedly tell the country where a product was made from the first digits, and verify its authenticity from the rest.
Chestny Znak and the square code on the packaging: what it shows
Next to the familiar stripes on packaging, there is increasingly a small square made of dots.
Where do apps get calorie and macronutrient data and why do the numbers differ
The same cottage cheese gets different calorie counts in two apps, and people usually assume one of them is wrong.
Calorie counting apps: how they work and where they go wrong
A calorie counter looks like a calculator, and people expect calculator-like precision from it.
Fitness trackers and calorie expenditure: why they measure heart rate but estimate calories
On a tracker screen, three numbers look equally reliable: heart rate, steps, and "calories burned.
Smart scales: what bioimpedance actually measures
Smart scales display body fat percentage, water percentage, muscle mass, bone mass, and "metabolic age.
Glucose monitoring without diabetes: what the sensor on your arm shows
A coin-sized sensor on the shoulder and a blood sugar graph on a phone are no longer exclusive to diabetes: people without a diagnosis are using them to "understand their reaction to food.
DNA test "tailored to your genome": what is known about nutrition based on genes
The promise sounds convincing: a saliva sample, two weeks of waiting, and a diet tailored to your heredity.
Microbiome tests: why two samples give different answers
An at-home microbiome test looks like a standard lab analysis: a test tube, a laboratory, and a report with percentages and a list of foods.
Pocket food scanners: what a beam of light can detect
A device the size of a keychain is held up to an apple, and sugar, protein, and calorie content appear on the screen.
AI nutritionist and nutrition chatbots: what can you trust
Asking a chatbot about your diet has become easier than making an appointment with a specialist, and the answer comes detailed, polite, and structured.
Plant-based and cultivated meat: what is in their composition
A pea-based patty and a beef patty look the same and sit side-by-side on the shelf, but they are different products in terms of composition.
Nutritional values in delivery apps: where the numbers in the dish card come from
In the dish card, below the photo, there are four numbers, and they look like a measurement.
From reading to doing. All of it starts in one place — knowing what is on the plate. Photograph it and the calories and macros appear on their own.
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This article is for general information. It is not medical advice, a diagnosis, or a prescription for treatment or a diet, and it does not replace a consultation with your doctor. If you have a health condition, are pregnant, take medication, or follow a diet prescribed to you, decisions about food belong with your doctor.
Figures from regulations, guidelines and studies are given as they stood when this article was prepared and may since have changed; check them against the primary sources. This article is not advertising, an offer, or individual advice, and neither the author nor the site owner is responsible for decisions taken on the basis of it.