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Daily news and analysis about the food tech revolution

food AI

The Food & Retail AI Rollup Continues as Crisp Buys Shelf Engine

Crisp, a New York-based retail data company, has acquired Seattle-based startup Shelf Engine. Founded in 2016 by Stefan Kalb and Bede Jordan, Shelf Engine specializes in using machine learning to optimize ordering processes for perishable goods, with the goal of reducing costs and minimizing food waste. The platform is now in use across more than 7,000 stores. Terms of the acquisition were not disclosed.

Shelf Engine was one of the earliest adopters of AI technology in food retail aimed at reducing waste and optimizing fresh food ordering. Kalb, who launched a food distribution business at 23 and holds degrees in actuarial science and economics, developed the idea during a 2014 ski trip with his friend and engineer Bede Jordan, a former Microsoft HoloLens developer. The pair questioned why food industry processes and systems remained outdated:

“Could we create a platform that enables retailers to buy food and eliminate significant waste? Could we create a platform that eliminates redundant busywork between vendors and retailers? Could we create a more perfect marketplace?”

These questions led Kalb and Jordan to develop a product designed to drive the food industry towards greater efficiency through technology.

Kalb reflected on the deal on LinkedIn:

“What started as a side project with my good friend Bede turned into a platform that’s now in over 7,000 stores across the U.S., helping reduce millions of pounds of food waste. It’s been eight years of wild highs, humbling challenges, and so much growth.”

Crisp plans to integrate Shelf Engine’s advanced algorithms into its commerce platform. The company believes the integration will help its retailer customers optimize in-stock inventory, improve shelf management, and drive revenue in an increasingly margin-sensitive retail environment.​

“Joining forces with Crisp allows us to scale our proven technology and deliver greater value to retailers and their supplier partners,” said Kalb. “Together, we will set a new standard in forecasting and inventory management, helping our customers thrive even in challenging market conditions.”​

This news is yet another in a series of acquisition announcements for early pioneers who are building technology leveraging AI to optimize different parts of the food value chain. Earlier this month AI Palette was gobbled up by trend forecaster Global Data, and before that Spoonshot was acquired by Target. Like other buyers in these deals, Crisp provides predictive intelligence software and services and is buying Shelf Engine to improve their AI insights capabilities.

Unlike these previous deals, Crisp and Shelf Engine focus more on retail and supply chain commerce optimization, which is one of the areas that is seeing the greatest leaps forward in productivity and cost-reduction. My guess is Afresh, which is similar to Shelf Engine and remains independent following its $115 million in series B funding in 2022, may also be one of the next companies gobbled up as bigger software and supply chain players look to add AI capabilities to their products.

AI-Powered CPG Trend Forecaster AI Palette Gets Gobbled Up

AI Palette, a company that uses AI to help CPG brands anticipate consumer tastes ahead of market trends and better predict new product success throughout their lifecycle, announced today it was acquired by market research company GlobalData.

AI Palette launched within the last decade alongside a cohort of startups—including Analytical Flavor Systems, Tastewise, and Spoonshot—that began utilizing machine learning and big data analysis tools. These tools enabled CPG brands to move away from traditional product ideation and surveys, uncovering hidden insights more rapidly through AI. Like many similar startups, AI Palette started talking up their generative AI bona fides over the past couple of years.

“The integration of AI Palette supercharges our ability to help CPG brands innovate smarter and faster,” said Mike Danson, CEO of GlobalData Plc. “Together, we are setting a new standard for AI-driven intelligence in the consumer space.”

In some ways, this deal resembles Spoonshot’s acquisition a little over a year ago, when legacy market intelligence provider Target Research Group acquired the AI startup. GlobalData Plc, which places greater emphasis on pure data analytics than Target, is a company that has grown primarily through acquisition. From what I can see, AI Palette represents GlobalData’s first pure-play AI company deal.

With most major food-brand CTOs currently exploring—or being directed—to leverage AI, it seems likely that acquisitions of vertically specialized platforms will continue over the next 12-24 months. Consultancies and market intelligence providers will probably lead this trend as incorporating AI into intelligence toolsets becomes essential to maintaining relevance..

Can You Use AI to Create a Wi-Fi Powered Rolling Pin? Join Today’s Interactive Workshop to Find Out!

Last June at the Smart Kitchen Summit, Scott Heimendinger talked about today’s temptation among product builders to follow a similar path with AI as consumer product builders forged a decade ago when they added Wi-Fi connectivity to almost everything.

“There’s a temptation that’s especially prevalent in our industry, but in others as well, that when new technologies become available to the world, we want to kind of slap those on what we’re doing,” he said. “We slapped WiFi on a bunch of things, but the world does not need a WiFi-enabled rolling pin.”

This doesn’t mean Scott doesn’t embrace AI as an inventor and product builder to help make him more productive in doing his job. It’s the opposite, and the one-time technical lead for Modernist Cuisine and founder of one of the earliest consumer sous vide hardware startups in Sansaire leverages AI tools to assist across the product development process. From ideation to market research to writing code, Heimendinger tells me that AI is a crucial tool to help him do his job faster and more efficiently.

If you’re looking for ways to figure out how to use AI in your job, join us this morning for this month’s Food AI Co-Lab as Scott shows us how to leverage these tools as we, yes, build an imaginary new product in a Wi-Fi rolling pin and look to bring it to market.

Join us for today’s interactive workshop at 8:30 Pacific Time to learn how a successful product developer and inventor like Scott leverages AI to up his game as he shares practical tips for you to do the same. Scott will work through his process and show ways he leverages a variety of tools and offer tips for you to do just the same. And who knows, maybe you’ll come away with an idea for the next big product (just not an AI-rolling pin, ok?). Register now!

IFA Smart Kitchen Roundup: Appliance Brands Try to Tap Into AI Zeitgeist With AI-Powered Food Recognition

This weekend at IFA, several big appliance brands used the show to tell the world that they are all in on AI, mainly through the integration of cameras into their ovens paired with software to enable personalized recipes and customized shopping lists.

Siemens showed off the iQ 700 oven has a built-in camera that recognizes over 80 different dishes and automatically adjusts to the ideal cooking settings. This feature allows users to place food, like a frozen pizza, in the oven and hit start for optimized cooking. The updated model offers more food recognition capabilities than previous versions and includes an optional steam function to achieve a crispy crust on baked goods.

Hisense debuted the Hi9 Series Oven, equipped with AI-powered InCamera technology for intelligent baking with over 140 pre-programmed recipes. The company also introduced a smart fridge in the Hisense Refrigerator PureFlat Smart Series, and its description sounds like they’ve been taking cues from Samsung and the Family Hub. The company described the fridge as “a home appliance control center” that “allows you to adjust temperature settings remotely through the ConnectLife app.”. The fridge also has AI-powered inventory tracking, though the company was light on details about how the tracking feature works.

Beko also let everyone know that they are trying to jam AI into as many things as possible, including their ovens. Like with HiSense and Siemens, they pointed to camera-assisted cooking in their ovens. From the release: “Beko brings AI-assisted camera technology to its Smart Home ovens, delivering a self-improving cooking experience for optimal results in the kitchen whatever the dish. With food recognition and cooking suggestions across more than 30 different food types, the new Beko Autonomous Cooking technology uses AI to finish cooking according to personalized browning levels.”

Ovens with cameras and food recognition aren’t exactly new, as we’ve been seeing this feature for the better part of a decade since June (RIP) debuted the technology. The appliance industry often displays a herd mentality, and clearly, the herd feels they’ve got to show off their AI chops, even if the technology is somewhat pedestrian at this point.

Electrolux Debuts Taste Assist AI on AEG Line

Not every new AI-feature introduction at IFA was tied to integrated cameras and image recognition. Electrolux introduced its AI Taste Assist feature on its AEG line of kitchen appliances. According to the announcement, AI Taste Assist will take recipes from the Internet, import them, and send cooking instructions to the oven, but not before it recommends ways to enhance and optimize the cook. In a demo on-stage by Electrolux at IFA, the company emphasized how the new feature was meant to overcome what they called the “cooking gap”, which they described as the limitations of existing recipes and the enhanced capabilities of modern cooking equipment. The feature that Electrolux primarily promoted to bridge this gap was steam cooking, a feature that was injected into a lasagna recipe in an on-stage demo of the Taste Assist feature by Christopher Duncan, Electrolux’s SVP of Taste for Europe.

One notable absence at Electrolux’s IFA new conference was GRO, the next-generation modular kitchen concept the company announced in June of 2022. All indications are that the Swedish appliance brand has not made any progress in commercializing GRO, probably partly due to the company’s struggles over the past couple of years. The company laid off approximately three thousand employees last year, and earlier this year, it saw the departure of its longtime CEO, Jonas Samuelson, as the company continued to struggle post-pandemic and in the fast of increased competition from Asian appliance brands.

SideChef Unveils AI Feature in App That Creates Step-by-Step Recipes From Photos of Food

SideChef recently introduced RecipeGen AI, a new beta feature that generates step-by-step recipes from a photo of any dish. Users can upload pictures of meals from restaurants or social media, and the app will provide a shoppable recipe based on the image.

From the release: “We are living in exciting times, where every inspiration can become a person’s reality,” says SideChef Founder & CEO, Kevin Yu. “At SideChef we’re excited to be the first to use AI to allow any home cook to make their food inspiration a reality for themselves and loved ones, with a single photo!

CNET writer Amanda Smith gave the app a test drive and came away with mixed feelings. While the app successfully identified many ingredients, it missed key components in some cases, such as sourdough focaccia and strawberry butter. It also occasionally added ingredients that weren’t in the dish, like bell peppers, leaving Smith feeling the accuracy was somewhat hit or miss.

Smith’s takeaway: Succes “depends on the recipe. It has a hard time with nuance and, like other AI tools, tends to make it up if it’s unsure. It’s a handy little app that could be used to inspire new ideas and ingredient concoctions or if you’re in a restaurant and don’t want to bother the waiter with dish details.”

Samsung Food Also Debuts AI-Powered Shopping Lists From Photos

SideChef isn’t the only smart kitchen company debuting photo-to-recipes/shopping lists powered by AI in their apps. At IFA last week, Samsung announced new AI-powered meal planning and food management features. The Vision AI feature now allows users to add ingredients to their Food List by simply taking a photo with their smartphone, expanding beyond the previous limitations of Samsung’s Family Hub smart fridge. This list can be used to suggest recipes, prioritize items nearing expiration, and automatically update after meals are cooked or ingredients are purchased.

Additionally, the company announced a new premium tier called Samsung Food+, a $7/month subscription service offers personalized weekly meal plans, tailored to users’ nutritional goals and dietary preferences, and tracks macronutrients and caloric intake. This premium tier also integrates more advanced AI functionality, allowing users to customize recipes and receive a full week of meal recommendations, helping reduce food waste and simplify grocery shopping by making the app a central hub for food management and meal preparation.

Jason Cohen Believes Generative AI-Powered Synthetic Data Will Transform CPG Development

Back in 2007, Jason Cohen was an aspiring political scientist studying in China. As it turned out, locals—and the Chinese government—weren’t too enthusiastic about political science students from America asking lots of questions.

Luckily for Cohen, that initial pushback from Chinese officials was the beginning of a circuitous path that would eventually lead him to tea and, surprisingly, to developing AI tools that help food brands accelerate their path to market. The Spoon recently caught up with Cohen to hear about his journey from the tea markets of Yunnan province to his current role at Simulacra Data.

A Serendipitous Start in the Tea Markets

Shortly after Cohen arrived in China as a young prodigy who had graduated high school early and was sent to study politics, things quickly unraveled.

“Turns out, blonde hair, blue eyes, and bad Chinese don’t really endear you to asking about the government in rural southwestern China,” Cohen said. With his political studies cut short, Cohen was drawn to the local tea markets, where he encountered Ji Hai, a fermentation master at the Communist-era tea conglomerate CNNP. It was here that Cohen’s fascination with tea took root.

“I started hanging out in the tea market, originally out of a mix of interest in practicing Chinese,” he said. “But pretty quickly, I realized there was something more going on here.” This unexpected immersion in tea tasting honed Cohen’s palate and laid the foundation for his future endeavors in understanding consumer preferences.

From there, Cohen went to live at the Makaibari Tea Plantation in India, where he continued to study tea. He then embarked on a long journey from Guangzhou, China, through Tibet and Nepal into India, visiting tea places and picking up odd jobs along the way.

Eventually, Cohen returned to the United States, where he attended Penn State on a political science fellowship. However, as in China, his interest in politics was pushed aside by his passion for tea. “Like everything I touch, it kind of spiraled out of control,” Cohen says, describing how a small research group he started evolved into a full-fledged tea research institute, where he did his studies in sensory science and artificial intelligence. Cohen’s research at the Tea Institute eventually became the basis for his first company, Gastrograph AI.

Gastrograph AI: A Pioneering Venture in Flavor Prediction

In 2011, Cohen took the learnings from the tea institute and used them to found Gastrograph AI. At the time, he thought he could build an AI model to predict consumer preferences based on flavor. Over time, Gastrograph built a proprietary dataset of over 100,000 product evaluations from 35 countries, which Cohen claims allowed the company to accurately forecast which flavors would appeal to specific consumer segments.

“We were building a foundation model for flavor,” Cohen explained.

As CEO, Cohen helped Gastrograph AI secure large CPG brands as customers, where the company’s model helped fine-tune their products to meet the tastes of different demographics. Around this time, Cohen observed that AI researchers began to build large language models using neural networks and deep learning, but he wasn’t yet convinced of the power of generative AI for CPG research.

“I had always been a skeptic of the use of traditional neural networks and deep learning models,” he said. “In consumer research, you deal with small, expensive, and difficult-to-collect data sets. You can’t just throw a deep learning model at it and expect good results.”

The Turning Point

Cohen’s skepticism about generative AI shifted as he observed the rapid advancements in new tools based on LLMs over the past couple of years. One particular tool that caught his eye was Midjourney, the generative AI tool that creates lifelike images with simple prompts.

“The moment that the switch flipped was with the release of MidJourney,” Cohen said. “If you can generate images based on a text prompt, you should be able to do that with tabular business data.”

Once Midjourney led Cohen to reconsider the potential of AI in consumer research, he began to think about how generative AI could enable companies to generate synthetic data for scenarios that would otherwise be too costly or time-consuming to study. “It became very, very clear to me in 2022 that generative AI was going to change what’s possible to achieve in consumer research,” Cohen said.

It wasn’t long after this realization that Cohen stepped back from his role at Gastrograph and founded Simulacra Synthetic Data Studio.

Simulacra: Redefining Consumer Research with Generative AI

According to Cohen, Simulacra uses AI in a significantly different way than what he and his team pioneered at Gastrograph; instead of relying on proprietary data, Simulacra uses a “bring your own data” model. This allows companies to input their existing consumer data into the company’s model, which then uses generative AI to create synthetic data for a wide range of scenarios.

“We built an AI that learns to build a synthetic data generation model on whatever data is uploaded,” Cohen said. He explained that this allows companies to simulate outcomes—from market reactions to new products to optimizing pricing strategies—without extensive market research. “It’s much more mathematically accurate. It’s much more correct for drawing direct statistical inference,” he said.

At the core of Simulacra’s technology is diffusion modeling, which Cohen describes as challenging conventional thinking about AI models. “Synthetic data generation turns a lot of what we think about models on its head,” he said. By treating all variables as both dependent and independent, Simulacra’s AI can create a more holistic and accurate model of consumer behavior.

The Impact of Generative AI on the Food Industry

Cohen believes that generative AI will have a profound impact on the food and consumer goods industries.

“We’ve seen the market fracture, and we’ve seen a greater number of consumer cohorts than there had previously been.”

Cohen believes that in a fast-changing market, traditional market research is often too slow and expensive to keep up with changing consumer preferences. Because of the rising cost of traditional research, companies are forced to rely on smaller studies with less statistical power, making decisions based on incomplete data or gut instinct. Simulacra, Cohen explains, offers companies a way to make data-driven decisions that are both accurate and affordable.

“That’s where Simulacra is really going to make an impact.”

Beyond Digital Twins

According to Cohen, there is a big difference between Simulacra’s approach and traditional digital twin technology. While digital twin technology typically involves creating exact virtual replicas of specific entities or datasets to model and predict behaviors, Simulacra uses survey data—ranging from hundreds to hundreds of thousands of observations—to synthetically generate new data or incorporate new knowledge. He believes this approach allows Simulacra to adjust and predict outcomes with more mathematical accuracy and statistical relevance. Rather than producing textual outputs like those from large language models (LLMs), Simulacra returns quantitative and categorical data that companies can use for rigorous statistical analysis.

Looking Ahead: The Future of AI in Consumer Research

As AI technology evolves, Cohen envisions a future where AI-driven consumer research—including synthetic data—is the norm rather than the exception. He predicts that tools like Simulacra will help companies reduce the high failure rates associated with new product launches by providing more reliable data and insights earlier in the development process.

Despite the transformative potential of this technology, Cohen is quick to dismiss concerns that using AI model and synthetic data will lead to consumer product homogenization.

“The idea that this technology is going to be a convergent force across different product development cycles, I don’t think that’s the case,” he said. Companies will still have different goals, constraints, and consumer segments, leading to diverse outcomes even when using similar technologies.

You can watch Cohen’s full interview below. If you’d like to hear him talk about Simulacra and meet him in person, he will be at the Food AI Summit on September 25th!

The Spoon Talks with Analytical Flavor Systems

The Food AI Weekly Bulletin: Will AI Fakery Make Restaurant Reviews a Thing of the Past?

Welcome to the Food AI Weekly Bulletin, our new weekly wrapup that highlights important happenings at the intersection of AI and food.

Nowadays, there’s a lot of noise around how AI is changing food, so we decided to create a weekly brief to bring you what’s important, decipher through all the noise, and deliver actionable insights. If you’d like to sign up for our weekly Food AI Weekly, you can do so here.

Highlights

Is AI Ruining Restaurant Reviews? A new study shows people cannot distinguish between real and AI-generated reviews.

AI Food Art Is Everywhere (And It’s Not Great for Freelancers) Generative AI tools like Midjourney and DALL-E are revolutionizing food imagery, but what does this mean for freelancers and creatives who traditionally provided these services?

First, Al Michaels. Next, How About an AI-powered Anthony Bourdain? The news of Al Michaels allowing AI to replicate his voice has almost everyone freaking out, but what does it mean for the future of AI-generated avatars of famous food personalities?

Swallowing A Robot. Endiatx has developed the Pillbot, a tiny robot that can be swallowed to explore the gastrointestinal tract, potentially revolutionizing diagnostics and personalized nutrition.

Food & Nutrition Centric LLMs Could Be an Investible Opportunity. VCs see potential in industry-specific AI models, particularly in the domains of biology, chemistry, and materials, as these specialized LLMs could offer unique investment opportunities.

Brightseed’s Forager AI Finds Novel Bioactives. Cranberry giant Ocean Spray teams up with Brightseed to uncover new bioactive compounds in cranberries.

Our Favorite AI Food Art of the Week. We’ll be making this a regular feature. If you’d like your art featured, submit it on our Spoon slack. 

We’re going to be exploring all of this at our Food AI Summit in September. Join us won’t you? Super Early Bird pricing expires at the end of this month.

Is AI Ruining Restaurant Reviews?

What happens when humans can’t tell real restaurant reviews from fake ones? The restaurant industry has begun asking itself this question as a tidal wave of fake AI reviews floods online sites.

According to Yale professor Balazs Kovacs, humans are already losing their ability to discern the real from the fake. Kovacs recently unveiled the results of a study demonstrating AI’s ability to mimic human-written restaurant reviews convincingly. For his test, Kovacs fed Yelp reviews into GPT-4 and then asked a panel of human test subjects whether they could tell the difference. At first, the results generated by GPT-4 were too perfect, so Kovacs then prompted GPT-4 to insert “

While this raises obvious concerns about the authenticity of online reviews and the trustworthiness of consumer-generated content, it shouldn’t be surprising. Figure 01’s human-like speech tics were creepy, but mostly because of how human its awkward conversation seemed. With typos and sub-par grammar—in other words, what we see every day on social media—it makes sense that AI-generated reviews seemed more human.

One potential workaround to this problem of AI-generated reviews is using AI to detect and notify us what fake content is, but early tests show that even AI can’t tell what is real and what is fake. Another suggestion is to require reviewers to have purchased a product to review it (similar to having Amazon labels whose reviews are from verified purchasers) and apply it to restaurants. My guess is that this will be the best (and potentially last) line of defense against the coming tidal wave of AI reviews.

AI Food Art Is Everywhere (And It’s Not Great for Freelancers)

One early application of generative AI, as it applies to food, is the creation of images. Midjourney, DALL-E, and other tools allow us to create instant realistic images with a few sentences. As a result, we’ve seen CPGs, food tech software companies, and restaurant tech startups jump on the generative art trend.

While that isn’t necessarily good news for actual artists (this WSJ article is a must-read about the impact of AI on freelancers and creatives), these tools have democratized professional-ish like photos and art for folks in the same way Canva made professional-style graphics and presentations available to anyone.

One company that’s benefitted significantly is Innit. The company, which focused in its early life on hiring celebrity chefs like Tyler Florence and spending tens of thousands on photo shoots for a recipe, is now whipping them instantly with generative AI for its Innit FoodLM.

While most Internet-savvy marketing types at food brands, restaurants, and other food-related businesses have at least learned to dabble in generative AI prompt engineering, that hasn’t stopped some from trying to create a business out of it. Lunchbox created an AI food image generator utilizing DALL-E as the underlying LLM over a year ago (the website has since gone dark), and just this week I got pitched on a new AI-powered food generator that wants to charge for its service (which is essentially a user interface to manage prompt engineering for an underlying LLM (which most likely is Midjourney or GPT-4). There’s likely a small lifespan for these types of services, but my guess is most marketing folks will learn to prompt engineers directly with popular image generators like Midjourney.

First, Al Michaels. Next, an AI-Powered Anthony Bourdain?

The Internet freaked out yesterday when news broke that Al Michaels has agreed to let an AI copy his voice, and rightly so. First off, it’s creepy. Second, this is the exact thing was the main reason the Hollywood writers and actors guilds kept striking for so long, so I’m guessing the Hollywood creative community isn’t exactly happy with Al. And finally, it goes to show you that if you throw enough money at us humans, the temptation to cave to the bots will be too much.

My guess is we’ll eventually see AI-generated avatars of famous chefs. All it would take is for the estate of Julia Child or Anthony Bourdain to get a good enough offer and it won’t be long before we hear (and maybe see) their avatars.

Swallowing A Robot

According to Venturebeat, Endiatx has developed a microscopic robot that can traverse your body and is equipped with cameras, sensors, and wireless communication capabilities. The robot, called Pillbot, allowing doctors to examine the gastrointestinal tract and be used both for diagnostic and therapeutic purposes.

The company’s CEO, Torrey Smith, has taken 43 of these Pillbots and swallowed one live on stage, which can be seen here. If this technology actually works (and those pills can be made smaller because, holy cow, that’s a literal big pill to swallow), it’s not hard to imagine these being used to dial in and optimize personalized nutrition regimens.

Food & Nutrition Centric LLMs Could Be an Investible Opportunity

Business Insider asked some VCs what they’re bored by when it comes to AI and what they’re excited about. Not surprisingly, they talked alot about how it will be hard for startups to break through in foundational large language models, where big players like Open AI and Google play. And like any good VC looking at an early market they talked up up picks and shovels

Even as investors shift their focus to promising AI infrastructure startups, there may still be some opportunities for new LLM startups to win, especially when they’re trained for specific industries, explained Kahini Shah, a principal at Obvious Ventures.

“We’re excited about what we call Generative Science at Obvious, i.e, large, multi-modal models trained in domains such as biology, chemistry, materials,” she said.

Brightseed’s Forager AI Finds Novel Bioactives

Brightseed, a company that uses AI to accelerate bioactive and food compound discovery, announced that it has (in partnership with Ocean Spray) used its Forager AI to uncover novel bioactive compounds in cranberries. Forager identified multiple bioactives, such as terpenes, which Brightseed believes hold significant potential for human health. These findings, based on in silico analyses, will undergo further clinical validation and will be presented at the American Society of Nutrition’s NUTRITION 2024 conference.

This acceleration effect of new health-positive compounds is another example of the AI acceleration effect I wrote about yesterday. Things are beginning to move exponentially faster at every stage of the food value chain, which over time means our basic understanding of the rules underpinning what we do (such as food product development) gives way to entirely new rules that are rewritten in large part by AI.

Our Favorite AI Food Image of the Week: Hungry Monkey

We like looking at AI-generated food art and figured we’d show you some of our favorites on a weekly basis. 

If you’d like to submit your AI-created food art (or if you’ve found one you think we should feature, drop the image and the source/attribution (preferably a link) on our Spoon Slack.

Key Takeaways From The First-Ever Food AI Summit

Last week, we convened some of the leading voices in AI and food at the inaugural Food AI Summit in Alameda, California, to discuss how this technology is transforming the food industry.

The conversation spanned the entire food system, examining the impact of AI on farming, food development, restaurants, personal nutrition, and household use.

It’s All About The Data

Throughout the day, it became clear that one of the most significant drivers for achieving highly functional and powerful AI systems is building them around the right data. Once you’ve trained the AI on good data, the insights derived from these platforms will far surpass what was previously possible.

Erica Bliss, the Chief Operating Officer of Mineral, believes where AI will really excel is in aggregating ‘multimodal’ data into a unified, synthesized analysis.

“It’s about integrating satellite imagery, soil data, weather data, historical yield data, camera data, and scouting notes from someone walking the field. The real power is in aggregating diverse and complex data types,” she said.

The Biggest Advances Will Come From a Combination of Human Knowledge with AI

The question of whether AI can replace human knowledge and innovation was a recurrent theme throughout the day. Oliver Zahn, the CEO of Climax Foods, believes that AI will not replace human knowledge. Instead, he sees the combination of technology and humans as a game-changer.

“People have this romantic notion that we have an algorithm, and you just tell it to make whatever cheddar, egg scramble, and then it will just tell you exactly how to make it,” said Zahn. “It’s vastly more complicated than that. In many cases, the humans are actually much better than the algorithms. And in real life, I don’t think anybody will ever write an algorithm and create a data set that is rich enough to do that. The algorithms give us a little bit of an edge over traditional food science companies, and in some cases, they give us a bigger edge.”

Erica Bliss believes that while AI will increasingly help farmers at both a systemic and individual farm level, it will be the combination of AI and human knowledge that will form the “Iron Man suit” amalgamation of capabilities that will lead to transformational outcomes.

“There are things that humans are incredibly good at that AI is not good at,” said Bliss. “And so if you’re aiming to get the best yield forecast, it is really the human plus machine that’s driving a far better outcome.”

AI Will Power Much More Personalized and Accessible Health and Nutrition Advice

Noosheen Hashemi, CEO of January, which offers a personalized nutrition and glucose tracking platform, believes AI will empower individuals with chronic conditions like type 2 diabetes to better monitor and anticipate the effects of their diet.

“There are things we have done you simply cannot do without AI,” said Hashemi. “We can build a digital twin of a person using wearable data and user-reported data. We’re then able to predict their glycemic response to any of the foods in the 32 million food database. With AI, we can also give counterfactuals like ‘you ate this, but if you had eaten this, this would have been your response.'”

Looking forward, Ari Tulla of Elo Health thinks AI-powered coaches could make healthcare much more personalized and accessible.

“Today, we live in a world where a doctor has 10 minutes to half an hour a year for you,” said Tulla. “What if you could have a bot or somebody that can talk to you like your personal trainer at the tune of 30 to 50 hours a year? That could have a very big impact.”

AI Will Have An Impact at the Macro and Hyperlocal Levels

David Lee, the CEO of Inevitable Tech, believes that AI will not only address the challenges of increased production due to a rising global population and climate change but also aid in making individual farms more financially sustainable.

“Around forty percent of farms break even or do any kind of variable profit, which means most farms operate at a constant loss,” said Lee. “AI isn’t just about serving these big global problems like food security. I can also address the very individualistic, local problem, which is to create financial sustainability, local and specific, to the unit of a farm anywhere in the world.”

The First-Ever Food AI Summit Could Be The Start of Something Big

During his comments, Ari Tulla commented on the event itself, believing it could be the beginning of something big.

“I’ve been at those events where there are a hundred people in the room, and you know this is the beginning of something,” said Tulla. “Ten years from now, some of us will look back and say, ‘I was at the first Food AI Summit.'”

We sure hope so! Thanks again to our speakers, sponsors, and attendees for making the first Food AI Summit a huge success!

Want to Try AI-Powered Cheese & Sausage? Join Us on October 25th at the Food AI Summit

So, what does food designed by AI taste like?

Next week at the Food AI Summit, you’ll have a chance to find out! That’s because not only will we have sessions by founders, inventors, and executives exploring how to bring food to our plates using the latest in artificial intelligence, but we’ll also get a chance to taste it!

After a full day of sessions that includes leaders from Pepsi, Afresh, ReFED, Chefman, Innit, Mineral and more, we’ll network and sample food from Shiru and Climax Foods! The founders of both companies will be on hand to talk about the process behind developing AI-powered plant-based food, so you will definitely want to stick around and join us!

You can check out the full-day agenda and great list of speakers over at the Food AI Summit page. If you’d like to join us, use the coupon code SPOON at checkout for $100 off tickets.

We’ll see you next week!

With the Launch of Samsung Food, Samsung Hypes AI & Consolidates Food Features Acquired Over the Years

Over the years, Samsung has acquired and launched several products in an effort to become the king of the tech-powered kitchen.

First, there was the launch of the Family Hub refrigerator, the company’s attempt to create a smart fridge built around the company’s own operating system and packed with technology like fridge cams to identify food and help you with your shopping.

Then, there was the acquisition of Whisk, an intelligent food and shopping app that helped pioneer the shoppable recipe space. Whisk had not only amassed an extensive food database, which would ultimately become a foundation for some of Family Hub’s (now Bespoke Family Hub) shopping and recipe capabilities, but it also served up the foundational ‘Food AI’ that is now being pushed to the forefront by Samsung.

Then, there were various attempts to use AI through automation in the kitchen, as the company announced (and never released commercially) different cooking and kitchen-task robots at CES.

And we can’t forget that Samsung also took some of the smart home technology from its SmartThings smart home group (another Samsung acquisition) and paired it with Whisk’s recipe intelligence to create SmartThings Cooking, a guided cooking app.

This leads us to this week, in which Samsung announced what amounts to packaging up this collected knowledge and technology – save for (at least for now) the robotics – into a newly expanded app and platform called Samsung Food. Samsung Food, which the company describes as “a personalized, AI-powered food and recipe platform,” looks like a significant step forward for the company’s efforts to build a centralized digital food management app. It also is a logical move to consolidate much of the collected efforts under the Samsung brand after the company had collected a variety of platforms that served as a foundation for what we see today.

Let’s take a look at precisely what the company unveiled. In the announcement, Samsung detailed four primary areas of activity for Samsung Food: Recipe Exploration and Personalization, AI-Enhanced Meal Planning, Kitchen Connectivity, and Social Sharing.

For recipe exploration, Samsung looks like it’s essentially using what was an already somewhat evolved feature set in Whisk. Samsung says that it can save recipes to a user’s digital recipe box anytime and from anywhere, create shopping lists based on their ingredients, and is accessible via Family Hub. In addition to mobile devices, users can access Samsung Food with their Bespoke Family Hub fridges, which will provide recipe recommendations based on a list of available food items managed by the user and shoppable recipe capabilities.

With the Personalize Recipe function, Samsung Food looks like it builds on the personalization engine created by Whisk and plans to take it further through integration with Samsung Health. According to the announcement, by the end of this year, Samsung plans to integrate with Samsung Health to power suggestions for diet management. This integration will factor in info such as a user’s body mass index (BMI), body composition, and calorie consumption in pursuit of their health goals and efforts to maintain a balanced diet.

The AI-Enhanced meal planning feature looks like a longer-view planning feature that consolidates personalized recipe recommendations, and it will no doubt similarly benefit from the integration of Samsung Health.

With Connected Cooking, Samsung has rebranded and extended the features of the SmartThings Cooking app, adding new devices like the BeSpoke oven and incorporating some of the same guided cooking features.

And, of course, a consolidated food-related platform from Samsung wouldn’t be complete without a social media component. My guess is the Social Sharing feature – which will allow users to share with their community – is the least necessary addition to the app and will ultimately not be all that successful, as consumers will continue to use mainline social apps (TikTok, Instagram, Facebook) for their food-related social sharing.

The company also teased expanded computer vision capabilities in 2024 in the announcement. The company’s Vision AI technology “will enable Samsung Food to recognize food items and meals photographed through the camera and provide details about them, including nutrition information.”

Overall, I’m impressed with the overall cohesiveness and trajectory of what I see in Samsung Food. I think it’s a sign that Samsung – despite having the occasional misstep and strategic vagueness around their food vision – looks like they remain committed to becoming the leader of the future kitchen, something that they started way back in 2016 with the launch of the Family Hub line.

Delivery Giants DoorDash and Uber Eats Join The Rush to Integrate AI Into Ordering Platforms

Over the last six months, we’ve watched as seemingly every quick-service restaurant chain jumped on the AI freight train, integrating new generative AI technology into apps, chatbots, and voice ordering tools to expedite the customer experience.

Now, it looks like food-ordering platforms DoorDash and Uber Eats are taking their turn to roll out AI tools.

This week we learned of DoorDash’s AI-powered voice ordering, which the company is rolling out as part of its merchant solutions portfolio. At first available in select markets, the new AI voice agents will be the first point of contact for restaurants leveraging DoorDash’s white-label voice-order platform. The company says AI voice ordering can take orders in different languages.

The AI will be trained on each operator’s menu and make personalized upsell recommendations. DoorDash makes clear that live human agents will be standing by to jump in if additional support is needed.

And, courtesy of Bloomberg, we also learned this week that Uber Eats is working on a new AI-powered chatbot for its food-ordering app. Techcrunch writes the new AI chatbot will ask users about food budgets and preferences and help them place an order. The Uber Eats AI chatbot news comes a month after DoorDash confirmed it is also working on an AI chatbot.

The news of AI-powered tools by the two delivery giants comes after a string of AI rollouts on the quick service front. This spring, Wendy’s announced it was working with Google to develop an AI for its drive-thru called FreshAI, and early this month, White Castle announced it was working with SoundHound to develop a drive-thru AI.

As I mentioned in my writeup of the food AI workshop ethics workshop, one of the first areas I expect to see AI and automation impact food is on the front lines of quick service. The historically low pay and high turnover for these jobs make them low-hanging fruit when it comes to AI tool integration, particularly for order taking, which is often the biggest bottleneck and the most easily automated part of the entire food purchase process.

We’ll be talking AI and how it will change the restaurant business at our Food AI Summit on Oct 25th in Alameda. Get your ticket today to join the conversation!

I Attended a Workshop on the Impact of AI on The Food World. Here’s What We Discussed

Last month, I headed down to San Luis Obispo to participate in a National Science Foundation-funded project analyzing the impact of automation and AI on the food system. I’d been invited to participate in a workshop headed up by Patrick Lin and Ryan Jenkins, professors at Cal Poly and the project leads.

The workshop was the first for the four-year project exploring the social and ethical impacts of automation and artificial intelligence in kitchens. The project endeavors to draw out the wide-ranging implications of this technology, exploring both the impact on commercial environments like restaurants and how automation could impact the longstanding tradition of home cooking and family meals.

“This project will help to draw out the hidden and very broad impacts of technology,” said Lin at the time of the project’s announcement. “By focusing on the trend of robot kitchens that’s just emerging from under the radar, there is still time for technical and policy interventions in order to maximize benefits and minimize harms and disruptions.” 

The two-day workshop included a cross-section of academic types, chefs and food service professionals, journalists, and technology experts. It was the first of three workshops across continents to gather insights and work towards producing a report and academic curriculum centered around the intersection of food and automation and AI.

The workshop, structured as a giant whiteboard session, included expert presentations and facilitated conversations. During and after each presentation, the participants shared their thoughts on potential impacts – both direct and cascading effects – that could result from the introduction of AI in its various forms over time. While much of the conversation focused more heavily on AI in the form of automation – i.e., cooking robots – AI in other forms, such as generative AI, was also discussed.

Below are some of the key themes discussed during the two days, as well as a few of my thoughts now that I’ve had time to think through the issues since the workshop.

I’d also love to hear your thoughts on this critical topic, so please send them along!

Finally, we’ll be discussing many of these same issues at the Food AI Summit on October 25th. If this is an issue critical to you and your company, make sure to join us!

Atrophying Cooking Skills

One of the concerns raised during the workshop was the potential loss of cooking skills and culinary knowledge as we rely increasingly on automation and AI to make our meals. While it was generally recognized that robotics could take over repetitive and tedious cooking tasks, some wondered if handing over the cooking process to machines could lead to a general loss of competency in culinary arts and a homogenization of meals produced by highly automated cooking.

It’s easy to see how highly automated food prep would be extremely popular; some would hand the entire process over to the machine. However, there’s a good chance that handing off the mundane parts of cooking would give home cooks, chefs, or food workers more time to focus on creating the special touches that often make a meal great. As we have seen with the advent of digital design and art tools, there’s a possibility that those who love making food could use technology to take their work to the next level.

The Loss of Together Time

Another concern raised across the two days was the impact on shared family time by handing over meal prep and cooking to robots. Parents and other caregivers often use time in the kitchen to share lessons to help children develop motor skills, understand their heritage and develop self-confidence. Over-automation of cooking could disrupt this transfer of knowledge. Cooking has also shown many positive mental health benefits for those involved.

I think these are valid concerns, as there is a real risk of losing some of the benefits of the shared cooking process due to automation. After all, there’s no replacement for a grandchild spending time with their grandma learning how to make her special cookies and the sharing of family history that comes along with such an activity.

However, a few counterpoints. First, no one says the act of hand-making that special recipe has to be a victim of technology, and, in some ways, I think the kitchen will prove to be one of the areas where some families will insist on preserving the art and act of doing the actual cooking themselves.

And as the world becomes more digital and automated, kitchens may be a refuge for many who find the hands-on nature of making food therapeutic and fulfilling. In other words, the kitchen may be the last true ‘maker space’ left in our homes, and many will look to protect and preserve that.

Finally, average meal times shrank 5% between 2006 and 2014, a much smaller decline than we’ve seen in meal prep times as the advent of ready-to-eat meals has become more popular over the past few decades. While automation may result in faster meals, people could spend nearly as much time – or maybe more – sitting around the dinner table.

A Loss of Authenticity, Creativity, and Happy Accidents

With AI, there’s a chance recipe creation algorithms may rely too heavily on existing data patterns and therefore lack originality. There was also the concern that AI systems may limit opportunities for spontaneous creativity and the type of “happy accidents” that often lead to new recipes. One workshop participant gave an example of mistakes leading to important new dishes, like the croissant.

There was also concern that using AI to generate meal plans or recipes could result in over-standardization and homogenization, particularly if the AI systems rely too narrowly on popular recipes, which could also reduce culinary diversity.

It’s a valid concern that AI systems will generalize based on limited data sets, often creating recipes or meal plans based on popular or trending food concepts. Anyone who listens to algorithm-generated playlists by Spotify or Pandora can attest to some off-note song recommendations, and I can see how that could easily be the case with food and recipe generation. However, good technology products allow humans to reject recommendations and fine-tune algorithms, which may allow for more personalized recommendations based on a particular user’s preferences.

There’s also a real possibility that AI could lead to new and intriguing food combinations. Chef Watson and other AIs have been able to create unexpected but interesting recipes based on intelligence built into the algorithms around flavor compounds. If a restaurant or home chef can leverage heretofore inaccessible deep insights based on science and flavor research built into AI systems to create their next masterpiece, the results could be exciting.

As for the impact on cultural diversity, I think it’s important to recognize that AI systems are known to have bias problems, often hewing more closely to the worldviews of their creators and their preferred datasets. Because the world of food is one of the most important pathways for under-represented voices to connect with broader audiences, it will be critical for us to guard against the loss of accessibility and equality in the culinary world as AI and automation tools become more commonplace.

However, food AIs could be built to emphasize unique and emerging food cultures, which could be a savvy move since millennials and younger generations celebrate new food discoveries, often from cultures outside their home markets. Also, many of the creators of new food automation technology are often from markets outside our own, emphasizing food types different from our traditional fare.

This is just a few of the themes discussed during the workshop. Other themes, such as job loss and the economic impacts of automation, were also explored in detail, and I’ll have more thoughts on that later this week.

Innit Debuts FoodLM to Power More Contextually Relevant Answers from Generative AI Platforms

Today Innit, a startup best known for its shoppable recipe and smart kitchen software solutions, announced the release of FoodLM, a software intelligence layer that helps power more contextually relevant food-related answers from generative AI large language models (LLMs).

The new platform, which itself is not a new LLM, is instead a software intelligence layer built to plug into existing LLMs to do pre and post-processing of queries to help provide better answers around a variety of food-related topics.

From the announcement:

FoodLM enables powerful semantic search for retailers to go beyond keywords and understand intent. Brands can provide consumers with highly personalized AI assistance from product selection through preparation and cooking. For health providers supporting patients with chronic diseases such as type 2 diabetes, FoodLM provides powerful science-backed assistance for healthy eating and food as medicine.

Innit CEO Kevin Brown described FoodLM as a “vertical AI” expert layer that can integrate into popular LLMs such as OpenAI’s GPT4 or Google’s PaLM. Brown compared FoodLM to what Google has done with Med-PaLM, which is Google’s medical knowledge layer that provides focused answers that are so contextually smart around medical information that it has started to pass the medical exams.

“You’re going to need the pairing of an LLM with expert training and expert systems to narrow it down for certain functions where it’s essential to be accurate,” Brown said.

The biggest concern with LLMs today is their tendency to hallucinate. Brown says that integrating with a vertical knowledge layer increases the likelihood of more relevant and accurate answers, ultimately leading to more trust in these systems.

“Food queries are one of the top use cases for LLMs, helping with tough problems like helping to manage people’s diets,” said Brown, “But only if you can trust them. If you can trust these systems and ensure they reflect key dietary and health factors, it becomes much more valuable.”

According to the company, answers are pre-processed and post-processed through FoodLM’s focused computation models, which it calls validators. The different validators within FoodLM include:

  • Nutrition & Diets: Analyzes more than 60 diets, allergies, lifestyles, and health profiles to provide detailed recommendations tailored to individual needs.
  • Health Conditions: Provides dietary guidelines, product scoring, and content specifically designed for conditions such as type 2 diabetes or hypertension.
  • Personalized Shopping: Automated grocery purchases, incorporating personalized scoring and selection of over three million grocery products worldwide.
  • Culinary & Cooking: Advanced logic to ensure that AI-generated recipes follow culinary guidelines and are cookable. Seamlessly integrates with smart kitchens, featuring automated cooking programs.

For now, Brown says FoodLM will be used by its partners through custom integrations via API. Over time, he sees the system as having a more approachable user interface where the system is used via a SaaS model.

From my perspective, FoodLM makes lots of sense for Innit. While we’ve already seen similar moves from some data-service and SaaS providers in the food space, Innit’s offering goes further and has more granular breakouts to provide specific contextualized offerings to power food-related services for their CPG, appliance, and health/wellness industries.

If you’re interested in the intersection of food and AI, make sure to check out The Spoon’s Food AI Summit, which is on October 25th in Alameda, California.