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AI

July 3, 2025

Is IFT’s Launch of an AI Tool For Food Scientists an Indicator of Where Trade Associations Are Going in Age of AI?

Interesting news out of IFT First this week, the food scientist expo in Chicago, where the longtime trade association announced its own AI tool called CoDeveloper.

According to the announcement, CoDeveloper is a platform built for food scientists by food scientists, offering a suite of AI-powered tools to help them formulate new products, reverse-engineer existing ones, and tap into decades of peer-reviewed food science research. Branded as a “co-scientist” named Sous, the platform is designed to live alongside R&D teams and support early-stage development work.

It’s an interesting move for the group, and as far as I can tell, the first time a trade association in the food space (or possibly any industry) has launched its own AI tool to help practitioners do their jobs. It also raises a larger question: could this be a sign of where trade associations are headed as AI becomes more integral to how we work?

It would make sense. Trade associations have historically provided value through education, convening, standards development, and general promotion. In a future where most industries are driven in large part by AI, why wouldn’t these associations, especially science-focused ones like IFT, want to get in on the action?

Of course, there has been no shortage of efforts across the food industry to develop food AI models, whether that’s startups looking to sell their AI as a SaaS platform or big food brands creating AI tools to differentiate themselves. Whether an available-to-everyone AI food product development tool is something hyper-competitive CPG companies would be interested in is yet to be seen, but I am sure that it will be something most members of the IFT community will want to take for a spin around the block.

June 30, 2025

Study: AI-Powered Drones Fuel Advances in Precision Ag for Early Detection of Crop Stress

Early stress detection via precision agriculture just got a serious upgrade, according to new research out of the Hebrew University of Jerusalem. Led by Dr. Ittai Herrmann, the team developed a drone-based platform that blends hyperspectral, thermal, and RGB imaging with powerful deep learning technology to precisely identify nitrogen and water deficiencies in sesame crops.

Sesame, known for its resilience to climate variations, is rapidly growing in global importance. However, accurately identifying early-stage crop stress has historically posed a significant challenge, limiting the ability of farmers to respond quickly to potential catastrophic challenges. To tackle this, the researchers combined three advanced imaging technologies into a single drone system, creating a robust solution capable of decoding complex plant stress signals.

Hyperspectral imaging provides detailed spectral insights into plant chemistry, including nitrogen and chlorophyll levels, which are critical markers for plant nutrition. Thermal imaging spots subtle temperature changes in leaves that indicate water stress, while high-resolution RGB images provide clear visual context of overall plant health and structure.

What made this study cutting-edge was its use of multimodal convolutional neural networks (CNNs), an advanced AI approach that can unravel intricate data patterns and add context, which significantly enhances diagnostic precision. These advanced techniques unlocked the researchers’ ability to distinguish overlapping signals of plant stress, such as differentiating between nutrient and water deficiency, something that conventional methods often struggle to achieve. According to the researchers, by accurately pinpointing the exact stressor, farmers can now apply resources such as fertilizer and irrigation more strategically, reducing waste and environmental impact while increasing crop yields.

While other researchers have studied using advanced AI techniques with drones to aid in combatting stress in walnut and specialty crops, the use of deep multimodal CNN appears to be a leap forward in precision ag. It remains to be seen how quickly this technology reaches the farmer level, but given the challenges of climate change, its easy to envision that these types of advances in precision agriculture will be invaluable tools for farmers in the future to protect against climate-related crop stress.



June 12, 2025

Starbucks Unveils Green Dot Assist, a Generative AI Virtual Assistant for Coffee Shop Employees

While most companies across the food value chain are embracing AI in some form, one major player that’s been notably quiet is Starbucks.

From mobile ordering to Web3 experiments, and computer vision-powered bioauthentication to automated drink-making, the Seattle-based coffee giant has never shied away from tooting its own hard about tech-forward initiatives. But when it came to generative AI, the most hyped tech trend of the past few years, Starbucks had kept relatively quiet, leaving many to wonder what it was working on and when it might reveal its plans.

That wait is over. This week, at a 14,000-employee conference in Las Vegas, the company unveiled Green Dot Assist, a generative AI-powered assistant designed to help baristas and store managers streamline their operations.

So, what is Green Dot Assist? In short, it’s a Microsoft Azure-powered virtual assistant currently being piloted in 35 Starbucks locations. The app assists with a range of tasks, from training new employees on how to prepare specific beverages to supporting shift managers with dynamic scheduling in response to real-time changes, such as last-minute call-outs.

Green Dot Assist even troubleshoots hardware issues. In a demo video shared by Starbucks, a barista named Dave uses the assistant to diagnose an espresso machine that’s pulling inconsistent shots. The AI provides 3D visual guides and prompts Dave to submit a service ticket—an experience that blends visual diagnostics with conversational support.

Packaged in an iPad app (apparently, Microsoft couldn’t convince the coffee chain to use Surface devices), Green Dot Assist combines training, support, and efficiency tools, all powered by Azure’s generative AI capabilities.

Given Starbucks’ longstanding emphasis on employee training, an AI-powered employee training guide and assistant makes sense. But my guess is this is just the beginning. In the longer term, I expect Starbucks to leverage AI to further enhance operational efficiency, particularly given the significant shift in order mix towards mobile ordering, which has led to increased wait times and customer frustration. This next wave will likely include more advanced automation, as we’ve already started to see with the chain’s push to roll out its Clover Vertica machine nationwide this year and – possible – a new point of sale system announced this week at the company’s employee conference.

May 13, 2025

A Week in Rome: Conclaves, Coffee, and Reflections on the Ethics of AI in Our Food System

Last week, I was in Rome at the Vatican for a workshop on the ethical and social implications of artificial intelligence and automation in our food system.

The workshop was part of an ongoing three-year NIH-funded project focused on the ethics of AI in food. It took place at the Vatican’s Pontifical Academy for Life, the same institution that played a pivotal role in 2020 in getting Microsoft, IBM, and others to sign the Rome Call for AI Ethics, a cross-sector commitment to develop AI that “serves every person and humanity as a whole; that respects the dignity of the human person.”

I was invited to provide an overview of AI in the food system to help set the stage for the day’s conversations, which featured Michelin-starred chefs, Catholic priests, journalists, authors, and professors specializing in ethics, artificial intelligence, and more. I walked through some of the developments I’ve seen across the food system—in agriculture, next-gen food product development, restaurants, and the home. As I wrote recently for The Spoon, today “every major food brand has made significant investments — in people, platforms, products — as part of the AI-powered transformation.”

I posed questions like: What happens when AI dictates what we eat? Or if it engineers the “perfect sandwich”—something so addictive it floods demand and strains supply chains, as Mike Lee has imagined? What does it mean when a company builds a proprietary food AI trained on global culinary data? Does that dataset become the intellectual property of one corporation? And if AI can tailor nutrition down to the molecule, who controls those insights?

These are not just technical questions. They’re questions with deep implications for humanity.

One thing was clear throughout the day: everyone in the room recognized both the promise of AI as a tool for addressing complex challenges in the food system, and the risks posed by such a powerful, society-shaping technology. Among the questions raised: How do we balance the cultural and inherently human-centered significance of food—growing it, preparing it, sharing it at the family dinner table—with the use of AI and automation across kitchens, farms, and wellness platforms?

Above: The signed Rome Call for AI Ethics

As some attendees expressed, there’s a growing concern that the “soul” of food—its role in connection, tradition, and creativity—could be lost in a world where AI plays a central role.

For obvious reasons, being at The Vatican and in Rome at this time was a bit surreal, as the two days of the workshop and the Vatican came during the same week that the College of Cardinals gathered to select the next Pope after last month’s passing of Pope Francis.

As we wrapped up our discussions, the Conclave began. And just as I was leaving Rome, white smoke rose from the chimney of the Sistine Chapel, signaling that a new pope had been chosen.

In his first address, Pope Leo XIV made it clear that he is thinking deeply about AI’s role in society, so much so that he chose his name in homage to a previous pope who guided the Church through an earlier technological upheaval.

“… I chose to take the name Leo XIV. There are different reasons for this, but mainly because Pope Leo XIII, in his historic encyclical Rerum Novarum, addressed the social question in the context of the first great industrial revolution. In our own day, the Church offers to everyone the treasury of her social teaching in response to another industrial revolution and to developments in the field of artificial intelligence that pose new challenges for the defence of human dignity, justice and labour.”

Also present at the workshop was our friend Sara Roversi, founder of the Future Food Institute. The Spoon and Future Food Institute co-founded the Food AI Co-Lab, a monthly virtual forum where experts across disciplines explore the intersection of food and AI.

Sara, Tiffany McClurg from The Spoon, and I grabbed coffee at a small café in Rome to reflect on the workshop and what it means for our ongoing work. We launched the Food AI Co-Lab in early 2024 as a space to gather our communities and talk through how AI is impacting the food system. So far, much of the conversation has focused on education—helping people understand what AI is and how to thoughtfully implement it in their organizations.

But we all agreed: the world has changed rapidly since we began. Nearly everyone is now seriously considering how to integrate AI into their companies, institutions, or personal lives. And so, the Co-Lab needs to evolve too. Our hour-long sessions, often featuring guest speakers, have been great for tracking innovation, but now it’s time to elevate the conversation. Ethics. Labor. Equity. Sustainability. These aren’t side topics—they’re central to how AI will shape the future of food.

If the world feels more chaotic than ever, one thing is certain: we need to prepare for faster, more unpredictable change. At the first workshop two years ago, most attendees were just learning about AI. There was plenty of fear about a runaway system invading the food chain.

Today, there’s greater recognition that AI is inevitable and that it can be a powerful tool for solving some of the food system’s most complex problems. There was even a bit more optimism this time.

But above all, there’s a clear understanding that we still have a long road ahead to strike the right balance: embracing AI as a tool while preserving what makes food so deeply human, so critical to our culture, communities, and shared existence.

You can learn more about the Food AI Ethics project led by Cal Poly at San Luis Obispo [here]. If you’d like to join us for future Food AI Co-Lab events, you can sign up via our LinkedIn Group or The Spoon Slack. We’ll keep you updated on upcoming events and speakers.

April 28, 2025

From Starday to Shiru to Givaudan, AI Is Now Tablestakes Across the Food Value Chain

Back in the early days of the cloud computing revolution, my former employer, GigaOM, hosted perhaps the biggest and most influential conference on the topic called STRUCTURE.

One of the phrases that has stuck with me from those days is “data is the new oil,” which I heard declared from the STRUCTURE stage more than a handful of times. At the time, big data technologies were leveraging machine-learning-driven analytics tools to create new correlations and insights from disparate datasets faster than ever before. Those who controlled the data — and could mine it effectively — wielded enormous power.

Now, nearly two decades into the cloud era and three years after the AI “big bang” sparked by the launch of ChatGPT, those early days seem almost quaint by comparison. New AI-powered tools and companies are emerging every day. While much of the “data is the new oil” rhetoric back then felt like spin, today we’re seeing real, transformative progress, especially in new product development.

Food is no exception.

Take the news from Shiru this past week. The company, which uses AI to sort through plant-based food building blocks, announced that it had scaled its first AI-discovered products: OleoPro and uPro. These new approaches to identifying proteins — particularly oleogel structurants (structured fat systems) — are designed to support large-scale production.

As Shiru CEO Jasmin Hume put it:

“This moment is a turning point not just for Shiru, but for the food industry. Even though oleogels have been explored for years (there are over 500 publications on them in the last decade), commercially scaled examples have been elusive — until now. Our AI platform helped us identify the right proteins, but that was only part of the story. Our team then engineered a scalable and entirely new process for producing those proteins with the precise performance attributes required to succeed in real-world formulations.”

But it’s not just next-generation ingredient discovery. New CPG brands are also using AI to decipher early consumer signals and connect the dots before anyone else can launch the next big product. One example is Starday, a startup that recently raised $11 million. Starday uses AI to sift through millions of data points from social media feeds, surveys, point-of-sale data, and more to identify emerging opportunities in food that could lead to future hits.

“Imagine if you had 10,000 consumer insights folks that are watching every video on internet, typing up what’s being said, tagging it, and then kind of building these regression models around how these trends are happening,” said Starday CEO Chaz Flexman in a recent interview with The Spoon. “We’re trying to do that on steroids. We take in about 10 million pieces of content every week, which is very significant.”

In the early big data heyday, companies could look at things like trending tweet mentions. Today, companies like Starday are able to dive into video content, extract context much faster, and build predictive intelligence to guide new product development.

Shiru and Starday are just two examples making headlines recently about how AI is reshaping the food industry. Others are innovating across different parts of the food value chain — from manufacturing optimization (Keychain) to intelligent automation (Chef Robotics), all the way back to the farm with companies like Agtonomy.

Even century-old flavor companies are getting into the act. This past week, Givaudan announced Myromi, a handheld digital aroma delivery device that leverages an AI platform called ATOM.

In short, AI is enabling both startups and established players to move much faster.

And they’re going to have to. In the current MAHA moment in the US, companies are urgently reevaluating ingredient lists and being forced to replace ingredients like food dyes and sugars. This new urgency is adding to what many had already been doing as they see climate change slowly but surely impacting how and what they can source for their products.

Back in 2010, there was a lot of talk about using big data to create better products, but no one was seriously using AI to build food products at that point (heck, Watson, after all, hadn’t even become a chef.) Today, every major food brand has made significant investments — in people, platforms, products — as part of the AI-powered transformation.

In other words, if data is the new oil, it’s now clear that AI is the engine of innovation that is accelerating and driving change across every part of the food system.

April 17, 2025

Join Us Today as We Discuss How Artificial Intelligence Will Impact Culinary Creation

Admit it: you’ve probably played around with making recipes using AI. At this point, most of us have.

If you’re like me, the early results were… rough. But over time, general-purpose LLMs have become surprisingly good at whipping up recipes. Still, there’s a long way to go before AI becomes a true sous chef in our kitchens, and plenty of questions remain about where this is all going.

To help us explore what’s next in this month’s edition of our Food AI Co-Lab, we’re joined by two people who’ve been working at the intersection of AI and cooking for nearly a decade: James Briscione and Lav Varshney, co-creators of Chef Watson—the world’s first culinary AI. Their latest project, CulinAI, is an AI-powered app designed to create personalized meal plans.

Want to join the conversation, ask questions, and see where AI cooking is headed? Register for today’s Food AI Co-Lab here.

April 14, 2025

ClearCOGS Raises $3.8M its AI-Powered Forecasting Software That Helps Restaurants Reduce Waste

AI-powered restaurant forecasting startup ClearCOGS has raised $3.8 million in an oversubscribed seed round led by Closed Loop Partners, with participation from Myriad Venture Partners and Hearst’s Level Up Ventures. The funding includes $2.3 million in new capital and the conversion of $1.4 million in pre-seed investments. The company’s software provides predictive analytics to assist operators in making decisions around food prep, ordering, and staffing, with an emphasis on reducing food waste and improving operational efficiency.

Company CEO Matt Wampler told The Spoon that he came up with the idea of ClearCOGS during the pandemic. He’d been being laid off and was exploring coding and analytics, when he discovered his cousin who ran a Jimmy John’s franchise was still using a decade-old Excel forecast. Wampler wondered if AI could help create a better predicitve forecasting tool, and before long he had teamed up with Osa Osarenkhoe to build a solution that uses machine learning and time-series forecasting that currover 100 million data points a day.

When ClearCOGS participated in our first virtual Food AI Summit a couple of years ago, Osa and Matt had started experimenting with leveraging large language models (LLMs) like those from OpenAI to create an interface for their forecasting tool. I asked Matt how those experiments with LLMs had gone.

“We did a whole big thing with it… It didn’t go well,” said Wampler. “And it wasn’t from a technical standpoint. It was from the standpoint of the restaurant brands we were talking to… they were like, ‘Look, my general manager can either just get on and play with your AI bot and it’ll tell them, or you can just send it to them? Just send it to them.’”

Wampler said the LLM interface wasn’t the problem. It was just that operators didn’t want to interact with it at all. Instead, they just wanted the answers delivered to them, simply and directly, through email and integrations with solutions from Toast or SevenRooms. This experience reaffirmed Wampler’s belief that proprietary forecasting (and not LLM-powered conversational AI) is where ClearCOGS can deliver the most value.

“LLMs are kind of a commodity at this point. Proprietary data sets are what really matters… You still have to be able to provide a fundamental business value before that AI is really helpful.”

While many platforms offer dashboards or raw analytics, ClearCOGS focuses on delivering direct, decision-ready insights to restaurant managers. This is central to how he differentiates the company:

“If you’re a brand, you probably have 20 or 30 questions that you have to answer every day… We go really deep on those and provide a systematic way of delivering those to your operators every day.”

With the new capital, ClearCOGS plans to accelerate its product development and customer acquisition efforts, with an emphasis of better positioning itself in the food service sector. The company currently serves a customer base of 100 brands in four countries, and Matt says they plan to continue building a lean team, prioritizing automation and AI over headcount.

March 28, 2025

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.

March 12, 2025

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..

March 6, 2025

McDonald’s is Creating Virtual ‘AI Managers’ for Its Restaurants

Want some AI with your Big Mac? McDonald’s is about to serve it up in a big way.

According to a story in the Wall Street Journal today, McDonald’s is undergoing a technology overhaul across its 43,000 restaurants, implementing internet-connected kitchen equipment, AI-driven drive-throughs, and tools for managers. McDonald’s is partnering with Google Cloud to deploy edge computing technology, allowing restaurants to analyze data locally rather than sending it to the cloud. This setup helps predict equipment failures—such as fryers or ice cream machines—before they occur and ensures order accuracy through AI-powered cameras.

We’ve written quite a bit at The Spoon about McDonald’s experimentation with AI at the drive-thru, but this story shows they are looking to use generative AI for customer interaction and beyond, including exploring generative AI virtual assistants to handle managerial tasks.

From the WSJ: Edge computing will also help McDonald’s restaurant managers oversee their in-store operations. The burger giant is looking to create a “generative AI virtual manager,” Rice said, which handles administrative tasks such as shift scheduling on managers’ behalf. Fast-food giant Yum Brands’ Pizza Hut and Taco Bell have explored similar capabilities.

This story comes just a day after Taco Bell talked up their own AI initiatives, including their ‘Byte by Yum’ AI tool designed to assist restaurant managers with tasks such as labor and inventory management. The AI can manage schedules, assist with drive-through orders, and suggest operational changes based on competitor activity, aiming to optimize employee efficiency without reducing labor costs.

February 27, 2025

Join Us Today as We Explore Future Scenarios of an AI-Powered Food System

Ever think about all the different scenarios that AI could ultimately unleash on our food system?

Us too, so we decided to invite noted food futurist Mike Lee to talk about it on our latest edition of the Food AI Co-Lab.

Join us today at 8:30 Pacific to explore the different scenarios that AI could unleash upon us.

In this session, we’ll discuss

  • AI & Regenerative Food Systems – How can technology help restore biodiversity, improve soil health, and create more resilient agricultural ecosystems?
  • Personalized Nutrition & Food Sovereignty – Can AI make food systems more inclusive, culturally relevant, and tailored to individual health needs while ensuring accessibility for all?
  • Circular Economy – How can AI-driven solutions reduce food waste, optimize supply chains, and create more efficient, closed-loop food systems?
  • Ethics & AI in Food – As technology advances, how do we ensure that food innovation remains fair, transparent, and truly benefits people and the planet?

You can watch it below or join us on our interactive Livestream to ask Mike questions!

Exploring Future Scenarios of an AI-Powered Food System

November 6, 2024

The Idea of Food ‘Teleportation’ Isn’t New—But AI Is Finally Making Distributed Digital Food Replication a Reality

Over the past decade, there’s been no shortage of attempts to better understand, map, and recreate food and its properties with the click of a mouse.

From new data ontologies to a proliferation of digital noses, we’ve seen incremental steps toward an envisioned world where the fundamental building blocks of food can be better understood. However, in the past year, there has been a rapid acceleration in our collective ability to digitize various properties of food, largely driven by advances in AI.

The latest example of this comes from Osmo, which recently announced its development of the ability to digitally “teleport” a scent by using AI to digitize and re-materialize it.

Scent Teleportation

As the company’s CEO, Alex Wiltschko, explained:

“We select a scent to teleport and introduce it to a machine called the GCMS (Gas Chromatography-Mass Spectrometry). If it’s a liquid, we inject it directly; if it’s a physical sample, like a plum, we use headspace analysis, trapping the scent in the air around the object and absorbing it through a tube. The GCMS identifies the raw data, which can be interpreted as molecules, and uploads it to a cloud. There, it becomes a coordinate on our Principal Odor Map — a novel, advanced AI-driven tool that can predict what a particular combination of molecules smells like. This formula is sent to one of our Formulation Robots, which treats it as a recipe and mixes different scents to replicate our sample.”

In other words, Osmo breaks down the building blocks (molecules), creates a map, and then sends this digital map to an essence “printer” that re-creates it.

This announcement comes just weeks after leaders of NotCo’s scent and flavor AI team shared research on their new generative AI that creates scent and flavor formulations. Here’s how Aadit Patel, NotCo’s head of product, described the model:

“The system takes your prompt—such as ‘an ocean scent on a breezy summer day on a tropical island’—and creates a novel chemical formulation of that scent in one shot.” The model then generates a corresponding fragrance formula. According to Patel, the model is built on a “natural language to chemical composition” framework, tokenizing molecules to create a system capable of understanding and generating novel combinations.

With years of work focused on digitally understanding, quantifying, mapping, and reproducing scents, flavors, and food building blocks, what is allowing these latest efforts to make such significant leaps?

In a word (or two): AI. In the past, creating a facsimile of a flavor or scent took thousands of hours, relying on trained experts to work in a lab or kitchen, drawing on years of expertise. Now, AI is expediting that process with orders of magnitude more efficiency, often leaving the expert to provide a final sign-off to ensure the AI-created formula meets standards for proximity to the desired result, as well as checks for safety, cost feasibility, and more.

For the record, Osmo isn’t the first company to discuss “teleporting” a formula for digital recreation. In 2018, Japanese startup Open Meals made headlines with its “sushi teleportation” demo, essentially sending 3D printing instructions to create a sushi-like meal. We also saw Cana’s ambitious attempt to make a Star Trek replicator (though, as it turns out, investors weren’t quite ready to enter the food teleportation age).

All of this follows years of efforts to quantify and understand food digitally, including the creation of ontologies for the Internet of Food and early attempts to use AI to analyze food. But over the past couple of years, there’s no doubt that parallel advances in AI (especially in large language models) and breakthroughs in food, olfactory, and chemical science are ushering in a world where true food “teleportation”—or, more accurately, the ability to understand and synthetically recreate food, flavors, and scents—has arrived.

I’m excited to see where this all goes. To manifest the vision laid out in science fiction over the years and imaginative product concepts like that of Open Meal required a true digital understanding of the molecular building blocks of food. With AI, we are closer than ever to that understanding, and the products we’ll see built in the coming decade will not only create some mind-blowing consumer experiences but also possibly fundamentally change how food and beverage products are made and distributed.

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