If you’ve ever tried to log your food intake with an app, you probably have realized the following:
Manual food logging with an app is a pain.
Food logging apps are often inaccurate because they require users to estimate portion size, ingredients, etc.
Food logging apps have cumbersome onboarding processes, ask for a lot of personal info, and usually try to upsell users into premium subscriptions.
For these reasons, I have not used a food-logging app for more than a few weeks, but that may soon change with GPT Food Cam. What is GPT Food Cam? In a few words, it’s a free food-logging app that lets you snap each meal or snack with your smartphone camera and uses AI to estimate calories. The app, which can be downloaded from the iOS App Store, doesn’t ask you to take a survey or require a subscription, and, from what I can tell within a day of use, it is really pretty darn good.
That’s my description, but what does Raj Singh, the longtime entrepreneur who is the visionary behind the app, have to say about it? According to Singh, who posted recently about the app on LinkedIn, GPT Food Cam is different from other food logging apps in three primary ways:
Instant Camera Access: The app opens straight to the camera, allowing users to quickly capture their meals without navigating menus. “I wanted it to be fast and low friction,” Singh said. “In social settings, it’s less intrusive to quickly snap a photo.”
Calorie Ranges Instead of Exact Figures: Singh said that because AI has its own limitations and portion sizes vary, the app provides a calorie range. “By presenting a range, it’s mostly right,” Singh said. “The goal is to build the habit of food logging and become a more mindful eater.”
Free and Unobtrusive: Unlike many apps that require subscriptions or bombard users with ads, GPT Food Cam is entirely free and supported by occasional, non-intrusive advertisements. “Right now, ads are making four times the revenue of the AI costs,” Singh said in a phone interview with The Spoon. “This allows us to keep the app free and potentially expand its features and availability to more countries.”
After working with a food coach who encouraged him to send photos of his meals for feedback, Singh sought a convenient digital solution to continue the practice. However, he found existing apps lacking—either too complex, costly, or both.
“They were designed for the 5% who need precision, but I wanted something simple, free, and for the other 95%,” Singh said.
According to Singh, GPT Food Cam leverages Gemini Flash, a fast and cost-effective AI model, to analyze images and estimate calorie content. Users simply snap a photo of their meal, and the app processes the image to provide an approximate calorie range.
“A lot of this is prompt engineering,” Singh explained. “We use ‘chain-of-thought’ prompting, where we break down the AI’s task into specific steps. The prompt instructs the AI to look at what’s in the picture, consider each ingredient independently, estimate serving sizes based on context—like whether it’s in a bowl or on a plate—and then estimate the calories of each item before adding them up.”
Singh emphasized that while AI isn’t perfect—with about 95% accuracy—it’s sufficient for promoting mindful eating. “AI has consistently been 95% accurate,” he said. “It’s great for recommendations and suggestions, but when it comes to critical workflows, it might get things wrong 5% of the time. For food logging, where precision isn’t as critical, this level of accuracy is acceptable.”
The creation of GPT Food Cam came after a serendipitous conversation with a friend. Singh’s friend, Zvika Ashkenazi, mentioned that his son, Ben Ashkenazi, was seeking an unpaid summer internship and wondered if Singh could mentor him. Singh soon began working with Ben, and six weeks later, GPT FoodCam was born.
“Ben is graduating from ASU in Computer Science in December,” Singh said. “He taught himself React, iOS development, and more this summer with minimal help from my network. He built this end-to-end.”
While GPT Food Cam emerged just in the last couple of months after Singh’s epiphany and Ben Ashkenazi’s coding work, Singh has been toying with the idea of a low-friction app to track food intake for a decade. In 2009, he tried to develop a similar application but soon realized the technology wasn’t mature enough.
“In 2009, I tried to create this exact app,” said Singh, who is currently the head of product for Mozilla’s Solo after the browser company acquired his startup Pulse in 2022. “It wasn’t good enough, and so we pivoted into a recipe company, which became Allthecooks.” Allthecooks would go on to become the number one recipe community on Android in 2010, with 30 million users, and would later be acquired by Cookpad.
Unlike then, “the tech is now here, making GPT Food Cam a reality,” Singh said. “Advancements in AI and image recognition have finally caught up with the vision I had over a decade ago.”
With the technology to make friction-free food logging a reality, Singh told me he wants to disrupt the food logging industry by offering a free, low-friction app, but he thinks it can do so with little involvement from him going forward.
“I build some things for fun. At the onset of a new project, I’m like, ‘This is not gonna make money, but the world needs it,’ or, ‘This is gonna be my next business, and I’m leaving where I’m at.’”
Singh made it clear he is happy at Mozilla and, in fact, used the product he conceived of building for Mozilla (Solo, an AI website builder) to create the website for GPT Food Cam. From here, he will let Ashkenazi run with the product, even if he periodically suggests some ideas to make it successful.
“I think it can be very, very disruptive. People are paying $10 a month for apps they don’t need to. This app can encourage better habits without the cost and complexity.”
Singh said he is also considering expanding the app’s capabilities and reach. With the ad revenue already exceeding the AI costs by a four-to-one margin, there’s potential to increase daily usage limits (currently, users are limited to six snaps a day) and make the app available in more countries.
Selfishly, I hope he and Ashkenazi succeed because, from what I’ve seen so far, I think the app is, in fact, potentially disruptive, and I hope to keep on using it. Who knows, maybe Ashkenazi (with a little help from Singh) can put their app on a similar journey we saw with Marco Arment’s Overcast app, which originally was a passion project that emerged from Arment’s annoyance with the current state of podcast apps to become the most user-friendly podcast app (and most popular, outside of Apple’s podcast app) in the world.
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{URL}https://thespoon.tech/ive-seen-the-future-of-food-logging-apps-and-its-gpt-food-cam/{/URL}
{Author}Michael Wolf{/Author}
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{Keywords}AI,News,Robotics, AI & Data,food logging,GPT Food Cam{/Keywords}
{Source}POV{/Source}
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