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The Spoon

Daily news and analysis about the food tech revolution

AI

Checkers To Roll Out AI-Powered Voice Tech to 267 Restaurant Drive-Thrus By End of 2022

This week restaurant chain Checkers & Rally’s announced a deal with Presto, a maker of restaurant technology, in which the drive-thru focused chain will roll out Presto’s AI-powered voice assistant technology chain-wide by the end of the year.

The announcement comes after early trials showed a 98% order accuracy for the voice assistant technology. And now, according to Checkers President and CEO Frances Allen, the chain plans to roll out Presto’s voice technology to all 267 store-owned and operated locations by the end of 2022. She also indicated that many franchise locations are expressing interest in the technology.

“We had a vision two years ago that we wanted what I would call ‘Alexa at the drive-thru,'” said Allen.

And now, with Presto, they have it. According to Allen, about 80% of the chain’s total business comes through a drive-thru, so the company’s management felt transitioning to a high-accuracy automated drive-thru could significantly impact the business.

“Anything we can do to improve operations, streamline for our guests and our employees, we wanted to do.”

You can hear the Presto voice assistant taking an order at a Checkers drive-thru in the video above. The Presto bot sounds, well, bot-like as it says “Welcome to Checkers, this drive-thru microphone is monitored and recorded for quality assurance.” In fact, the entire exchange sounds like something you might hear on an automated customer service line.

Expedite’s Kristen Hawley thought so too and asked during the press briefing if customers could access live humans at any point during the interaction.

“There are 2% of orders where the system says ‘you know, I don’t quite understand that,'” said Presto founder and CEO Rajat Suri. “If the person is insistent on talking to a staff member or operator, the system will escalate to the human in the restaurant.”

When asked if the broader rollout of Presto’s technology will result in a permanent reduction of headcount, Allen said no. Instead, she said, Presto’s technology helps fill roles left empty by the persistent shortage of workers the entire restaurant industry has been experiencing since the pandemic began.

“Our motivation is to fill the gap between the people that are available to us working in restaurants and where we need to focus that human labor,” said Allen. “In an ideal world, maybe we have five people at any shift right now. We probably have three or four available. And so this (Presto’s voice assistant) is like a fifth person that is coming in to help.”

“Our motivation here is not to replace people with robots.”

How Do You Train AI-Powered Checkout To Recognize A Product? In Vegas (& Elsewhere), You Throw It Like Dice

When it comes to training machine vision and AI-powered retail checkout systems, packaged goods and locally created food items are treated very differently.

That’s at least according to Mashgin, a maker of touchless checkout systems. Company spokesperson Toby Awalt said that’s because another store on the network has likely already added that bag of chips or candy bar to their 10 thousand plus item database.

Not so when it comes to locally made food items.

“CPG items, we have to do less and less because there’s enough overlap,” said Awalt, who gave us a walkthrough of the system at CES 2022. “But for dishes, we’ll do every time.”

According to Awalt, adding a new food menu item for a restaurant doesn’t take that since most cafeterias or restaurants only serve between 15 and 50 items.

“You can do that relatively quickly,” he said.

Still, a new packaged good has to be entered into the system now and then. Whenever that happens, the operator has to position the package in several different positions to give the system enough info to recognize the product whenever it shows up under the camera.

Mashgin’s Toby Awalt Rolls the Häagen-Dazs

“I actually do dice rolls with the product,” said Awalt, throwing a Häagen-Dazs ice cream bar onto the tray.

According to Mashgin, the company recommends the system capture 20 to 50 total positions of a product so it can recognize the product from various angles and also distinguish between different variations within the same product line (such as two different flavors of ice cream or potato chips).

You can watch a walkthrough of the Mashgin system below.

The Spoon checks out Mashgin's AI-Powered Checkout at CES 2022

How California’s New Food Waste Law Could Catalyze Interest & Investment in Tech-Powered Food Recovery Platforms

Starting next year, California’s Senate Bill 1383 will begin to require businesses and consumers to separate food waste from their garbage and put them into “green” bins for proper composting.

The legislation, passed in 2016 by then-governor Jerry Brown and the California state legislature, also will begin requiring tier 1 food businesses (grocery retailers, food distributors, food service providers) to divert 20% of food destined to be thrown away to food recovery organizations by the year 2025.

While I think it’s a good thing that everyone in California – both consumers and businesses – will eventually be required to start composting, I’m more interested in how SB 1383 could catalyze interest in platforms that help put food destined for the waste bin on someone’s plate instead. After all, while composting is a net positive from a climate impact reduction perspective, it’s also the last stop on the food waste recovery and mitigation express. In other words, when food feeds someone instead of ending up as fertilizer, everyone wins.

Image Source: CalRecycle SB 1383 Overview

The timing is good for the law, partly because the pandemic has driven home the realization among businesses that it’s their responsibility to try and divert food to local food banks or other food recovery organizations as good corporate citizens. And of course, it also makes good business sense, since by redirecting food to food recovery organizations, these businesses can also claim these donations on their taxes.

As grocery retailers and other tier 1 food businesses ramp up their food diversion efforts, there are some organizations that could help them along the way. One of these companies is Goodr, which offers grocery retailers and other food-related organizations a tech platform and associated service to help them get excess food in the hands of food charities. Goodr sprang into action in its home market of Atlanta during the early days of the pandemic and showed it could really make an impact. Other organizations such as Quest also provide food diversion services and food waste audits.

One of the challenges of a food recovery program is just having the ability to track and manage potential food waste. There are a number of technology platform providers such as Afresh and Crisp that give grocery providers tools powered by machine vision, AI, and other cutting-edge technologies to better predict and manage fresh food inventories. There are even food robot companies like Simbe developing technologies to help assist in food waste reduction management.

Finally, there are marketplaces like Olio and Too Good to Go that enable grocery retailers, restaurants, and other organizations to list excess edible food for sale on a highly-discounted basis to local consumers. While food sold on these platforms will not count towards the company’s 20% food diversion requirement, using them will help a company reduce the overall amount of food wasted and help provide low-cost food to consumers.

But what I am most excited about is how SB 1383 could give rise to new solutions to help food retailers and foodservice providers waste less food. New regulations often serve as catalysts for innovation, giving large businesses a new reason to invest in core technology infrastructure. As SB 1383’s regulations begin to go into effect, innovators with good ideas for new technology to help companies reduce food waste and redirect excess food towards food insecure citizens will have a growing market opportunity for their solutions. This growing opportunity will likely attract more venture investment for a category that has, at least in the past, had a hard time convincing investors there was enough of a market to garner them a return on their investment.

Watch Nala Robotics’ Robot Chef in Action

A restaurant that can serve millions of different dishes, is open 24/7, and doesn’t close on holidays sounds like a dream, right? After three years in the making, Nala Robotics has made this dream a reality with its fully automated robot kitchen that opened on November 11th in Naperville, Illinois.

The first automated restaurant/kitchen by Nala Robotics is called One Mean Chicken, and it serves wings and fried chicken. It is manned by multiple robots powered by artificial intelligence and machine learning, which do not need human intervention to function. Without the need for humans, Nala’s restaurant can operate throughout the day and night, on holidays, and without social distancing considerations.

Watch this video to see the robots preparing food:

Recipes can be uploaded by the user to the recipes catalog, and the robots can learn to make any dish within just a few minutes. This easily gives restaurant concepts the opportunity to offer multiple cuisines under one roof.

Nala’s use of articulating robotic arms to do everything from prep, cook, and more while handling a variety of cookware and utensils is reminiscent of Moley’s chef robot, which the UK-based company announced general availability for last year. Unlike Moley, Nala is exclusively targeted for commercial foodservice applications, whereas Moley is targeted both towards high-end residential installations in addition to commercial applications.

According to Ajay Sunkara, the founder and CEO of Nala Robotics, “Being AI-powered, the robotic chef gets better and better every single day. The more it cooks, the more it’s going to learn and master these recipes.”

Restaurants around the country have been facing major labor shortages in 2021 due to the aftermath of the pandemic, and over 25 percent have reported that they are struggling to hire line cooks. Automated kitchens like Nala, and others such as Mezli, Spyce, and Cala may prove to be a viable solution to these ongoing shortages.

Nala Robotics will soon open two more restaurant concepts in the same location as One Mean Chicken (in Naperville’s Mall of India). The next to be launched will be Nala’s Thai 76 (Thai food) and then Surya Tiffins (South Indian food). In 2022, Nala plans to open 10 restaurant locations, and then 100 locations by 2024.

Carrefour Teams With AiFi to Launch Cashierless Convenience Store in Paris

French retail giant Carrefour announced today the company has teamed up with AiFi, a maker of machine-vision powered checkout tech, to launch a cashierless convenience store called Carrefour Flash.

Unlike Amazon Go or other cashierless platforms that require an app, smart shopping basket, or biometric check-in, AiFi’s technology utilizes a network of cameras on the retailer’s ceiling that monitors a shopper as they move through the store and pick items up off the shelves for purchase. The computer vision’s AI creates a keypoint tracking system that creates a unique digital avatar for each customer. The system identifies each avatar by measuring the unique distance between the customer’s elbow and their hand. Because the system doesn’t require a unique biometric identifier such as a palm, facial or retinal scan, it ensures customer privacy despite using biometric tracking.

As the customer picks up items around the store, the AiFi system creates a virtual shopping cart. The system utilizes a network of 60 HD cameras and over 2000 sensors built into store shelves to track a shopper’s activity and assign it to their avatar. Once done, the customer walks up to a payment terminal to see their shopping basket and total bill within a few seconds.

This move by Carrefour is just the latest example of a retailer embracing tech that frees shoppers of checking out via a cashier. The wave of cashierless shopping formats, which kicked off in earnest with Amazon’s launch of their Amazon Go store in Seattle in early 2018, has only picked up steam over the past year and a half. One reason for the surging interest is the growing expectation from customers for low-contact ways to shop during the pandemic. The other primary driver is persistent labor shortages as food retailers deal with the high turnover of frontline workers; cashierless store concepts give them a way to operate without hiring and training new cashiers.

The Carrefour innovation team incubated and fine-tuned the new concept over the past year at the company’s headquarters in Massy, France. At launch, the new Paris store will have a total of 900 items for sale.

You can get a sneak peek of Carrefour Flash in the video below:

Shopping in a flash with Carrefour Flash powered by AiFi

With Food Scan, Snapchat is the Latest Company Trying to Create a ‘Shazam for Food’

Last week, Snapchat became the latest company to add an AI-powered food scanning and recognition feature to their product. Called Food Scan, the new feature enables Snapchat users to scan food items and get recipe suggestions and other information about the food.

Here’s how it works:

Snapchat users can scan food by opening up the AR bar within Snapchat from the main camera menu option. From there, they choose to scan and click a picture of the food item. Snapchat’s AI will process the image and suggest a recipe from partner Allrecipes, as well as serve up other information, such as a Wikipedia page, about with the item.

According to Snapchat, the feature has access to over 4 thousand recipes and can process up to 1500 ingredients. However, based on my own attempts, the product may need to add a few more items to the list to be helpful.

When I scanned Campbell’s Cream of Celery Soup, it offered up recipes for Campbell’s bacon soup. A scan of Adam’s peanut butter resulted in recipes for tahini. The closest match came from a scan of a navel orange, which resulted in a Wikipedia page for a mandarin orange and recipe recommendations for mandarin orange cake and mandarin orange salad.

Here at The Spoon, we’ve written a lot over the years about attempts by companies to create a ‘Shazam for food.’ Big tech companies such as Microsoft, Pinterest, and Google have been at work at this for some time, as have appliance brands like Samsung and Whirlpool. Part of the reason so many have dedicated resources to building augmented reality and AI products for food recognition is, quite simply, because food is one of the easiest product categories to recognize and create databases around. But it’s also because food recognition unlocks numerous commerce, health and nutrition tracking, and kitchen management scenarios if done right.

Snapchat’s new Food Scan feature, while pretty rudimentary at this point, clearly has designs on building potential revenue through shoppable recipes and product recommendations. However, I can also see it becoming a broader food-related augmented reality recommendation tool that suggests, similar to Alexa’s new What to Eat skill, restaurants, meal kits, and other potential monetizable recommendations.

IBM Partners With McDonald’s, Acquires McD Tech Labs to Automate Drive-Thru Orders

Over the summer, McDonald’s announced that it was trialing automated ordering at 10 Chicago, Illinois locations. Now, it appears that we will be seeing automated ordering at more locations sooner than later. Today, IBM announced that it has partnered with McDonald’s to continue to develop automated drive-thru orders and acquired its proprietary McD Tech Labs. The financial details of the acquisition were not disclosed.

McDonald’s acquired Apprente, a voice technology company, in 2019, and shortly after developed McD Tech Labs based on Apprente’s tech. This technology uses artificial intelligence to process drive-thru orders and then sends the order to the kitchen, where it is fulfilled by staff.

What is the benefit of using an AI-powered ordering system? In the trial run at the Chicago locations, McDonald’s found an 85 percent accuracy rate with orders and about 20 percent of orders needing staff assistance. AI can also help reduce customer wait time and free up employees to assist elsewhere in the restaurant.

In addition to the acquisition of McD Tech Labs, IBM will assist in the continued development of the Automated Order-Taking (AOT) technology and work on additional languages and dialects.

Consumers have traditionally voiced a certain degree of hesitancy in interacting with artificial intelligence. However, in Datassential’s AI & Menus report, it found that 43 percent of consumers found voice ordering technology unappealing initially, but after experiencing it, 68 percent were satisfied with the tech.

McDonald’s operates nearly 14,000 locations throughout the U.S, and it was not disclosed when a large rollout of the AOT technology might occur. IBM stated in the press release that it will help the quick-service chain accelerate the deployment of the AOT technology across different markets.

Soft Robotics Wants To Give Your Food Robot Good Eye-Hand Coordination

Football wide receivers that can catch the ball well are said to have soft hands. Food robots who use too much force grabbing delicate produce are, well, just being robots.

But now, robot system designers can turn their food robot into a veggie-shuffling Jerry Rice with the new mGrip “hand” from Soft Robotics.

The mGrip is part of a new SoftAI product suite from Soft Robotics that robot designers can add to existing systems to optimize them for handling food like meat and produce in high-volume environments. In addition to a food-grabbing hand, the SoftAI suite includes a “perception module” that pairs cameras with machine vision software that the company says will add “eye-hand coordination” to industrial robots. The on-board processing of the perception module uses machine learning to understand how to categorize and segment different types of food.

Robotics has long been used for tasks like packing food, but only in highly structured environments. Often, this meant using humans as part of the process to do things like sorting. However, advances in machine vision over the past couple of years have meant machines can essentially replace the need for humans to do some of the tasks they’ve been needed for in the past. With an off-the-shelf product like SoftAI, what companies like Amazon have probably spent millions to build now becomes more turnkey.

Beyond high-volume warehousing applications, I can also see how a platform like SoftAI could be used in more consumer-facing food robotic systems. For example, first-generation robotic food kiosks often used off-the-shelf robotic arms that required lots of customization to make them work. With new food-optimized plug-in hardware like SoftAI, small teams could accelerate their time to market and dedicate their time to other engineering problems.

You can see the mGrip and the SoftAI perception module in the video below.

Soft Robotics Introduces SoftAI™ - Accelerating the Adoption of Robotics in Food Processing

Food Tech Patent Watch: Patent Reveals Eatsa’s Robotic Meal-Assembly Machine

Remember Eatsa?

You know, the automat-like bowl food restaurant that was re-spun as a fast-growing (but more boring) restaurant marketing tech company called Brightloom?

I do, mainly because I loved the place. After I visited one in New York City, I wrote that the restaurant could be the future of fast-casual dining.

As it turns out, some – including maybe Eatsa’s investors – didn’t agree with me. I say that because starting in 2019, they phased out the cubbies, changed their name, took money from Starbucks, and, from the looks of it, dropped big plans for automating the back of house with meal assembly robots.

I say that because Eatsa (now Brightloom) holding company Keenwawa, Inc. was issued a patent last month for a meal-making robot. The patent, a continuation patent for one first issued to the company in 2019, shows a system that assembles meals by dispensing different ingredients stored in canisters into bowls and then shuttles the assembled meals off to the cubbies in the front of house.

Drawing of The Eatsa Meal Assembly Machine From Patent Filing

From the patent:

The automatic food preparation and serving apparatus may also comprise the food dispensing mechanism configured to dispense the ingredient from the plurality of food canisters into the bowl or food receptacle, under program control of the one or more processors.

The patent goes into excruciating detail about the system, complete with dozens of images outlining the canisters, the dispensing system, the conveyor belt, the bowls, and even the touchscreen user interface (which looks a lot like those deployed in the actual Eatsa restaurants for consumers to choose their bowls).

The list of inventors on the 60-page plus patent includes the former automation and engineering team for Eatsa, as well as Dave Friedberg, the one-time Climate Corp founder who incubated the company as part of what would eventually become The Production Board holding company.

I have to wonder if Eatsa-now-Brightloom’s owners are looking to license or sell the technology or even revive their ‘eatsa-inside’ strategy. After all, the recent news that Sweetgreen had acquired Spyce to help do exactly what Eatsa did – make food bowls – shows that some restaurants see a future in automated meal assembly.

Time will tell. For now, however, you can take a look back at the Eatsa ordering and cubby system below.

Food Tech Patent News Roundup

The First Patent Awarded to an AI System is in Food

While I thought that artificial intelligence systems will do most everything at some point, I assumed an AI being awarded a patent was one we could sleep on for a few years more.

I was wrong. In the July edition of the Patent Journal, an AI system named DABUS was awarded a patent for an innovation called “food container based on fractal geometry” for a system with interlocking food containers.

This Quartz Africa article describes DABUS’s creator:

DABUS (which stands for “device for the autonomous bootstrapping of unified sentience”) is an AI system created by Stephen Thaler, a pioneer in the field of AI and programming. The system simulates human brainstorming and creates new inventions. DABUS is a particular type of AI, often referred to as “creativity machines” because they are capable of independent and complex functioning. This differs from everyday AI like Siri, the “voice” of Apple’s iPhones.

DABUS’s inventor Thaler submitted the patent application listing DABUS as the inventor since the AI conceived and created the food storage system entirely. He submitted it to patent offices worldwide, including the US, which rejected him because, among other reasons, the US patent office only awards patents (for the time being) to human inventors. However, the South Africa patent office apparently had no such restrictions when it surprised many with an award of a patent.

In retrospect, it shouldn’t be that surprising AI are creating patentable ideas. AIs already write novels and movie scripts, so why not invent novel things like food containers and get them patented?

I’m looking forward to when we see AI start innovating on novel food. We’ve seen what an impact AI had in vaccine development, so it’s not too much of a stretch to see how it could start making a difference on the bioengineering front for foods.

A Patent Awarded for Many Container Within Container Scenarios For Food Storage, Cooking, and More

A fairly wide-ranging patent titled “Multi-function compact appliance and methods for a food or item in a container with a container storage technology” (US011104502) has been awarded to an Edward Espinosa from Spain for a system that enables a variety of container within container use-cases.

One example is a food container within a larger food storage appliance (i.e., a fridge) sending information on status such as freshness, etc. Another is the refrigerator with a microwave oven in one of the compartments.

The patent describes various technologies such as NFC, Bluetooth, voice control, machine vision via an internal camera, and more to enable the container systems to communicate with the appliance. In addition, the system describes the use of smart tags that communicate freshness data from within storage drawers.

I’ve long called for innovations in the core design of the fridge since they’ve largely been the same for the past 100 years, and it looks like Espinosa has definitely given the refrigerator a rethink.

Whirlpool’s Solid State Cooking Patent

Schematic for Cooking System With Directed RF Energy

It’s been a loosely held secret in the appliance industry that Whirlpool has been tinkering around in the solid-state cooking area for a while. This patent describing a system with multi-regional cooking via RF signals shows they are also trying to accumulate IP in the market. At this time, only Miele has commercialized a consumer solid-state cooking appliance, but hopefully, soon, we’ll see a next-generation microwave from a mass-market brand like Whirlpool.

Forget Watching TV. Sony Wants Your TV To Watch You (and Monitor Your Eating)

The couch in front of our TV is a sacred no-judgment zone, the place where we wear sweats, eat pizza, and binge-watch Cobra Kai on Netflix.

But what if the TV watched and, well, judged us? That’s the dystopian future Sony is thinking about, at least if US patent number 11,081,227 is any indication.

Called “Monitoring and reporting the health condition of a television user,” the patent describes a television with embedded cameras and sensors that monitor everything a person while slouched on the couch, including tracking the food they eat. The patent was awarded to Sony on August 3rd of this year.

So why is Sony looking to invade the safe space on our couch? According to the patent, the thinking is a TV like this could monitor the health of the TV viewer by recording activities such and eating habits and look for any signs of a potential impending health problem.

Illustration of Remote with Biometric Sensors from Sony Patent #11,081,227

From the patent:

People spend a significant number of hours sitting in front of a television (TV). They may have a hidden health problem or a diminishing health condition. The system monitors one or more health vitals of the user such as heart rate, etc. While sitting in front of the TV, they may behave in an unhealthy manner. For example, they may eat too much while watching a TV program. The system may also monitor the types of food a person eats while watching TV.

The patent describes a system that would use a camera embedded in the TV to log a person’s food consumption and monitor eating patterns such as chewing speed, posture, and how fast they eat. The system would also identify the type of food, estimate portion size, and take a guess at how many calories are consumed. All that info could be synced with biometric monitoring (the patent suggests a heartbeat sensor in the remote) to paint a profile of a person’s health and how their TV watching habits impact it.

So who needs a TV to monitor their food intake? I guess if one consumes lots of empty calories while sitting in front of the tube, this might prod them to change their habits. But on the other hand, do we really need a TV to tell us we’re eating poorly?

And then there’s the problem of consumer privacy. Some of you may remember the controversy a few years back about a few lines in the terms of service or a Samsung smart TV that suggested the company might capture conversations and sell them to third parties. I can only imagine what people might think about cameras on their TV watching their every move.

In Sony’s defense, this isn’t close to being an actual product. Patents are oftentimes just corporate thought experiments, where R&D managers with budgets to burn ask what if? The likelihood of Sony actually building their big brother TV is probably pretty low.

Probably. But maybe someday they will, and if they do, it’ll be interesting to see if consumers are ok with the idea of a TV watching them, trying to make them better people. But hey, if you’re really watching Cobra Kai and downing whole quarts of ice cream every Friday night, maybe you could use the help of your Sony 70″ 4K OLED TV to help perform a little self-care.

Sama Provides the Data to Fight Food Waste and Power Cashierless Checkout

When we talk about artificial intelligence (AI) in food tech, it’s often about the end result: Cashierless checkout, crop assessment, autonomous vehicles, etc. But one thing that these solutions and any other using AI need is is good data. Sama is a company in the good data business, and it has built a platform that provides training data that other companies can use to speed up the development of their AI models.

I spoke with Wendy Gonzalez, CEO of Sama, this week by video chat. She outlined some of the food tech use cases for her company’s technology, such as fighting food waste. “If you’re in a restaurant or hotel, catering service. A lot of that food gets wasted,” Gonzalez said. Sama is working with a company called Orbisk that provides a device for commercial kitchens that uses computer vision to analyze the food being thrown away. For example, if Orbisk sees a lot of mac and cheese is being tossed because no one is taking it, that kitchen can know not to make as much of it, and by extension save money by ordering less of the ingredients to make mac and cheese. (Winnow is another company that takes this same approach.)

For its part, Orbisk had a thousands of images of different types of food for its system to recognize. Sama came in and provided structure and taxonomy to that data. In other words, Sama labeled all the images of mac and cheese accordingly to train Orbisk’s AI to automatically recognize mac and cheese. The result, according to Sama, is that Orbisk’s system can reduce food waste in commercial kitchens by as much as 70 percent.

Gonzalez said that Sama’s system is also being used in other fields like cashierless checkout. In that setting, Sama is helping train those computer vision systems to recognize packaged goods, which is more complicated than people think. A cashierless checkout system needs to not only recognize a package of Oreos, but a package of Oreos in different lighting conditions, different angles or when the view is partially blocked. Sama provides all of that data.

Sama is also being used to train AI systems on early crop disease detection, automated crop harvesting, and soil condition monitoring.

Sama is among a number of players in the data space including AI.Reverie, which uses synthetic data to create images virtually to train AI models, and Nvidia, which is also using synthetic data to train robots to navigate around a kitchen.

As AI plays a bigger role in our everyday lives, there will be a growing need for more good data to train those AI systems. And the end result is that we’ll all be talking about good data more often.

Danone Expands Brightseed Partnership to Uncover Hidden Healthy Compounds in Plants

Danone and Brightseed announced an expanded partnership today that will have the food and beverage giant using Brightseed’s Forager artificial intelligence platform to uncover more phytonutrients from additional plant-based ingredients.

Brightseed’s technology studies plants on a molecular level to identify and catalog previously unknown compounds that could have health benefits. For example, earlier this year Brightseed announced that it had discovered in pre-clinical trials that the bioactive compounds N-trans caffeoyltyramine (NTC) and N-trans-feruloyltyramine (NTF) found in black pepper can help with the clearance of fat accumulated in the liver. After these initial findings through Brightseed’s AI, the company will move forwards to confirm the results through clinical trials to determine efficacy as well as other factors such as dosage and administering the compounds.

Danone first teamed up with Brightseed in June of last year to study potential new benefits of soy. (Danone owns the Silk brand.) According to today’s press announcement sent to The Spoon, Brightseed’s Forager discovered 10 times more bioactives than previously known and 7 new health areas. As these findings are confirmed by more clinical data, brands like Danone benefit because they can tout additional health benefits around their products, but consumers benefit because there are then more plant-based tools to fight different ailments.

What’s interesting about companies in the AI space like Brightseed, Spoonshot, and Journey Foods is how they are shortening the discovery period for food companies looking to create new products. Before machine learning and artificial intelligence, food manufacturers had to first hypothesize about how particular ingredients might work together, or the health benefits of an ingredient. After that guess, they would run physical tests in a lab to see if they were remotely close in their hypothesis. If they were wrong, they’d have to start all over again from scratch. AI helps shrink that time by doing a lot of that guesswork up front quickly in a computer before any lab time is needed.

The whole space is very new, but Danone expanding on its partnership with Brightseed is a vote of confidence for the technology and should lead to more brands jumping into the use of AI and computational biology.