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The Spoon

Daily news and analysis about the food tech revolution

Robotics, AI & Data

Walmart Canada to Deploy First Automated Kiosks for Grocery Pickup

Walmart Canada is adding automated kiosk pickup to one of its stores in the Toronto area, which, the company says, will be the first of its kind in that country.

In a corporate blog post published yesterday, Walmart Canada outlined a number of moves the company is making to accelerate its e-commerce efforts, including:

  • Building out a 22,000 sq. ft. space inside the Scarborough West Supercentre that will automate online grocery picking and packing that is six times faster than manual order picking
  • Expanding grocery pickup to 60 more stores this year
  • Piloting “ring scanner” technology that allows workers to pick and scan items hands-free

But the new feature we are most interested in is the new automated grocery pickup. According to Walmart Canada’s blog post, these new automated kiosks will “serve as vending machines for online grocery orders and can serve up to five customers simultaneously.” To use the kiosk, customers pull into a dedicated parking spot, enter a code into the machine and their order will appear in under two minutes.

All of these new, automated features are being built in partnership with Dematic, and will launch later this year.

This isn’t the first automated kiosk we’ve written about. Albertsons debuted its own robot-powered kiosk for grocery pickup at a Jewel-Osco in Chicago. But to our knowledge, this is the first public mention of automated kiosk pickup from Walmart in North America.

In January, Walmart announced that it was partnering with Dematic, Fabric and Alert Innovation to deploy automated fulfillment centers to “dozens” of locations. Automated kiosks weren’t mentioned at that time, but it’s safe to assume that if Walmart Canada is testing them out, they will make their way to the U.S. at some point.

As we covered this week, a ton of resources are flowing into the online grocery sector. Smaller online grocery startups around the world are raising a lot of money, and big players like Walmart, Albertsons and Kroger are making big investments in their own e-commerce infrastructure.

The reason for this big push into grocery e-commerce is that online grocery sales hit $9.3 billion in January, and is projected to hit $250 billion and take up 21.5 percent of total grocery sales by 2025. Retailers are bolstering their e-commerce capabilities now, to accommodate the growth that is to come.

HungerRush Launches Its AI-based Text-to-Order Tech for Restaurant Chains

Restaurant management software company HungerRush announced today that it launched its artificial intelligence-driven text-to-order product.

Dubbed HungerRush TextAI, the new feature uses natural language processing to interpret and place orders that come in via SMS. The new product is the result of HungerRush’s acquisition of OrdrAI last December. In its press announcement today, HungerRush said that TextAI works better than traditional phone or other employee-assisted formats by virtually eliminating order errors.

Text AI also integrates with HungerRush’s overall suite of products that include POS, delivery management, online ordering, mobile app, reporting and management, payment processing, and loyalty program.

HungerRush’s TextAI product launch comes at an interesting moment for AI integration for restaurants. Artificial Intelligence-driven software grabbed headlines last year as Kea, Clinc and even Google all had products that used natural language processing to hold “conversations” with restaurant customers. The promise, of course is that AI can take over incoming customer orders, allowing humans to perform more food creation and order expediting.

But in a signal that AI might not work as well as had been predicted, news broke this week that McDonald’s may sell Dynamic Yield, the AI startup it acquired in 2019. Granted, Dynamic Yield’s implementation of AI is more about creating dynamic menus that improved upselling (e.g., it’s cold outside, the menu highlighted warm beverages), so it’s a bit apples to oranges when compared with text-to-order. But if McDonald’s reportedly couldn’t even get a 1 percent bump from its implementation of AI, that could impact how other restaurant chains perceive the overall value of AI.

That’s not to say restaurants will abandon AI altogether. All of these technologies are new, and, not for nothing, are being tested under the unusual conditions of a pandemic, which has us ordering more takeout and delivery. Restaurants, which are seeing diminished value in third-party delivery services, need to save money where they can. If AI-driven text-to-order can drive sales and help restaurants get more value out of their labor, then that will go a long way towards adoption.

Demetria Raises $3M to Automate Coffee Bean Analysis

Demetria, a startup that promises to automate the analysis and grading of coffee beans, came out of stealth yesterday and announced that it has raised $3 million in seed funding. The round was led by Celeritas and a group of private investors including Mercantil Colpatria, the investment arm of Grupo Colpatria.

As coffee beans move through the supply chain, their quality has traditionally been judged by “cupping.” In this process, a human with proper certifications selects samples of beans and judges them based on factors like aroma, acidity and flavor. As you can imagine, this process is slow, wasteful, and because it’s done by experts, not globally available.

It also means that coffee bean quality and pricing is a subjective process, which can incorporate any number of human biases that can affect the prices paid to farmers and across the supply chain.

Demetria aims to automate this process by using near-infrared scanning and cloud-based artificial intelligence analysis to develop “digital fingerprints” of coffee beans. As green coffee beans move through the supply chain, they are analyzed with a near-infrared scanner to look for biochemical markers to match a bean’s profile with an industry standard set of quality metrics.

This means that bean quality can be quickly assessed with a handheld scanner and mobile phone. What’s more, beans do not have to be taken out of the supply chain to tested via cupping. Instead, they stay, reducing waste.

We’ve seen this type of AI-based scanning in the food supply chain elsewhere. Most recently, Driscoll’s announced that it was using Consumer Physics’ SCiO technology to scan berries for sweetness. Consumer Physics’ handheld scanner is one of the tools being used by Demetria.

Other companies in the space include AgShift and Intello Labs, both of which use computer vision and AI to assess food quality and bring objective grading to buyers and sellers.

In its press announcement yesterday, Demetria said it has successfully completed a pilot with Carcafe, the Colombian coffee division of agricultural commodity traders Volcafe/ED&F Man. Demetria said it is also working with Federación Nacional de Cafeteros (FNC), the Colombian National Federation for Coffee Growers, to develop apps that help farmers and their transaction points in the supply chain control and track bean quality, and price.

Technologies like Demetria’s can hopefully bring more fairness to the food supply chain by speeding up the process and standardizing the analysis so everyone gets paid a fair price.

Postmates X Spun Out of Uber to Become Serve Robotics

Uber has officially spun out its Postmates X division to become its own standalone company now called Serve Robotics. The news was first reported by TechCrunch and confirms rumblings about such a move reported back in January.

Uber acquired Postmates for $2.65 billion last year, which included the Postmates X robotics unit. The Serve delivery robot is an autonomous cooler-sized rover robot currently making deliveries around the West Hollywood neighborhood of Los Angeles.

According to TechCrunch, Serve Robotics has raised an undisclosed seed round of funding led by the VC firm Neo, with participation from Uber, Lee Jacobs, Long Journey Ventures, Western Technology Investment and other investors. Serve Robotics will be led by Ali Kashani, who headed up Postmates X, will have 60 employees, and will be headquartered in San Francisco, with offices in Los Angeles, and Vancouver, Canada.

Delivery robots like Serve are definitely on the rise as a number of startups come to market around the world. In the U.S. Starship, Kiwibot and Refraction all have robots making deliveries. In Russia there’s Yandex, in South Korea there’s Woowa Brothers, and in Turkey there’s Delivers AI. (For more, check out our Delivery Robot Market Report available to our Spoon Plus members.)

With all these robotic solutions plus other autonomous vehicle options, Uber doesn’t need to have its own full-stack robotic delivery solution. As I wrote last month:

“…as Uber CEO Dara Khosrowshahi recently explained on Kara Swisher’s Sway podcast, his company is in the networking business. Khosrowshahi doesn’t think Uber needs to create the technology uses, it just needs access to the best technology that allows it to facilitate deliveries and ridesharing. That’s one reason Uber offloaded its autonomous driving unit at the end of last year.”

Additionally, spinning off Serve Robotics means that Uber itself does not need to devote resources to figuring out the patchwork of state, county and city laws when it comes to actually getting commercial autonomous delivery vehicles on public sidewalks and streets. The flip side of that however, is that dealing with this patchwork of regulations is something Serve will have to do on its own.

Gatik Gets $9 Million (CAD) to Winterize its Autonomous Middle-Mile Delivery Tech

Gatik, which makes autonomous delivery vehicles for the middle-mile, announced today that it has received $997,706 million CAD (~$788,511 USD) from Ontario’s Autonomous Vehicle Innovation Network (AVIN) R&D Partnership Fun, along with $8 million CAD (~$6.32 million USD) in unspecified “industry contribution.” The new funding will go towards winterizing Gatik’s autonomous driving technology.

Gatik develops self-driving delivery trucks for the middle mile, which typically means between two points within a company’s network, e.g. between a warehouse and a store.

The Ontario government will help Gatik’s autonomous driving technology withstand inclement weather. Right now, a lot of self-driving pilots and tests happen in sunny climates such as Arizona, Texas and California. Bright, sunny weather makes it easier for self-driving vehicles to navigate because road conditions are dry and the surrounding environment is clearer for the vehicle’s systems to “see.”

But if self-driving technology is ever to reach mass market scale, it must be able to operate in all kinds of weather. Not only will autonomous vehicles need to “see” in rain and fog and snow, they will also have to safely drive on wet and icy roads. Another self-driving delivery startup that has “ruggedized” their vehicles for harsh conditions include Refraction, which operates out of Ann Arbor, Michigan.

Gatik already operates a small fleet of autonomous delivery trucks in Canada. Last November, Canadian grocery chain Loblaw started using a five Gatik trucks to run food between automated picking facilities and retail stores. Gatik, which is headquarted in Palo Alto, CA, has been expanding its Canadian presence. The company recently moved into a 12,000 sq. ft. research facility in Toronto and expects to double its workforce there over the coming year. As part of its funding arrangement, AVIN will help Gatik attract and retain engineering talent in Ontario.

Last month, the company debuted its first electric delivery vehicle, which has a range of 120 miles and takes only 1.5 hours to charge. The company will also be running two delivery routes for Walmart in Arkansas and Louisina. The Arkansas route will go completely driverless (i.e., no human backup) this year, and the Louisiana route will be the first to use Gatik’s electric trucks.

Operating only within the middle mile makes it easier for Gatik to bring its autonomous driving tech to market. By focusing on the middle mile, the delivery trucks only need to navigate between two fixed points. By avoiding consumer delivery (the so-called “last mile”), Gatik limits the number of variables its trucks will encounter on a given route.

This narrow, middle-mile approach combined with winterized driving capability could give Gatik a huge boost in getting to more markets quickly.

McDonald’s May Sell Part of Tech Company Dynamic Yield

McDonald’s is considering selling part of AI startup Dynamic Yield, which it acquired in 2019, according to a report from the Wall Street Journal. 

The original intention behind the $300 million Dynamic Yield acquisition was to install the company’s AI tech into self-service kiosks and drive-thru menu boards at McDonald’s locations. With the implementation, menus would become more technologically sophisticated, able to offer things like more personalized recommendations for customers. McDonald’s currently has Dynamic Yield implementations in the U.S., Canada, and Australia.

But as WSJ reports, after analyzing the Dynamic Yield platform, McDonald’s has found that the tech “hasn’t delivered the promised sales boost” originally hoped for at the time of the deal. The QSR mega-chain aimed for Dynamic Yield order suggestions to boost drive-thru sales by 1 percent in the U.S. Sources told WSJ that sales have fallen short of that target, and one franchisee said that “the return on investment is just not there.”

The Dynamic Yield platform is just one piece of technology McDonald’s franchisees have called into question recently. Despite the chain’s aggressive push towards digital ordering and all the accompanying technological changes, franchisees have pushed back on how much they must pay for all this tech. Ernst & Young is currently conducting an audit of these technology fees, while franchisees have paused all non-essential communication with McDonald’s corporate.

Still, missed sales targets and franchisee tensions don’t spell the end of Dynamic Yield’s platform as part of Mickey D’s operations. McDonald’s said it would keep parts of the company, including those that service the chain’s drive-thrus and kiosks. While details are few and far between, McDonald’s shift towards stores with more drive-thru lanes and less dining room space suggest Dynamic Yield’s tech will continue to provide at least some value going forward. 

McDonald’s is currently “exploring” the sale of a portion of Dynamic Yield. There is no set timeframe for a deal, and it is entirely possible that no deal at all will happen.

Cecilia.ai Mixes Chatbot Capabilities with Its Robot Bartender

The robot bartenders we’ve covered so far at The Spoon are either just autonomous, articulating arms (Glacierfire), or high-volume vending machines (Rotender). Cecilia.ai, the latest entrant in the autonomous cocktail-making space, went live today and “she” is serving drinks a twist.

In addition to automated drink-pouring, Cecilia.ai features chatbot functionality to have a “conversation” with a customer. Cecilia looks like something out of a Vegas. The machine sports a big screen with a CGI female bartender. Walk up to Cecilia and start talking to order your drink. The Cecilia.ai website provides a sample conversation that goes something like this:

CUSTOMER: Hi there.

CECILIA: Hello there, what can I get you to drink?

CUSTOMER: Any recommendations?

CECILIA: My favorite is the Rusty Ale, but it’s a bit strong.

CUSTOMER: Do you have something sweeter?

CECILIA: Sure! Try the Green n’ Tonic.

And… scene.

According to website, Cecilia can make 120 drinks per hour (with reduced chit-chat), offers conversational script customization to fit a location, hundreds of available mixes and hold 70 liters (it doesn’t specify booze or mixer ratios). Voice control means ordering is contactless, and the large screen can be used for advertising purposes.

We’ve reached out to the company to find out more details like pricing and availability, and will update this when we hear back.

There are actually a number of robot bartenders coming to market right now. In addition to the aforementioned Glacierfire bar and Rotender robot, MSC Cruises is installing a robot bartender on one on of its ships, Macco’s robot is serving beer in Spain, and Makr Shakr continues to sell its robot bartender solution.

One reason for all this automated mixology is probably, like so many other things, the pandemic. Having hundreds of strangers yell out their orders into the faces of human bartenders isn’t such a great idea any more, thanks to COVID. A robot bartender eliminates that vector of human-to-human transmission. But another reason is that robot bartenders are machines that can crank out drinks around the clock without taking a break, and they do so without spilling or overpouring (which may suck for customers but is good for a bar’s bottom line).

From what we can gather, Cecilia isn’t aimed at high-volume nightclubs and bars, but instead is more for hotels, airports, VIP lounges, etc. This makes sense since a crowded bar blasting music in the background would make it difficult for Cecilia to hear a patron order a Patron with only their voice.

The only question that remains is whether sage wisdom and funny anecdotes are programmed into her chatbot capabilities.

Honeycomb.ai Helps Those with Allergies Eat at Restaurants Through AI

Vancouver, Canada-based Honeycomb.ai opened up its artificial intelligence (AI)-based web app this week to help diners with food allergies and specific diets navigate restaurant menus. The first version of the service is currently available for users in the U.S., Canada, and Australia.

From Honeycomb.ai’s website, a user can select from 29 different allergies or dietary preferences (only two filters can be picked at the same time). Then, after selecting a specific city, the website populates restaurants in the area and menu items that are acceptable based on the selected criteria. I spoke with Honeycomb co-founder Tamir Barzilai by phone this week to learn more about how the company’s algorithm functions. Tamir said the Honeycomb.ai team spent four years training the algorithm to learn what menu items are typically acceptable for different allergies and dietary preferences. Using the name, category, description, and any available metadata of a restaurant menu item found online, the algorithm is able to predict what ingredients will be found in it.

Tamir said that the algorithm is able to do about 90 percent of the work, but there is still some information that needs to be entered manually by the restaurant. After the algorithm makes its predictions, a restaurant must sign up on the Honeycomb platform to verify the accuracy of those menu predictions and add in additional ingredients that the algorithm may not be able to pick up on. For example, if a dish was cooked in butter, but the restaurant’s menu description does not directly state this, so a restaurant would add this to the database for a more complete breakdown of ingredients. Additionally, restaurants can add Honeycomb.ai’s plug-in feature directly to their website to help users find menu items suitable for their diets.

In the U.S., it is estimated that around 32 million people experience food allergies, while 36 percent of Americans follow some type of specific diet. In addition to Honeycomb.ai, there are various companies taking different approaches to make dining out with a food allergy or dietary preferences a more streamlined process. SevenRooms, a company focused on back-of-house restaurant tech, enables restaurants to track customer data to remember important things like food allergies and preferences. Nima, producers of handheld peanut and gluten detectors, conducted gluten and peanut tests on dishes at major restaurant chains and created a map of all “Nima-tested” restaurants.

Honeycomb.ai is currently available as a website and iOS app. The iOS app will be updated with a new version shortly, and the company will also be launching an app for Android in the next few months.

Future Acres Kicks Off $3M Equity Crowdfunding Campaign for its Ag Robotics Platform

Future Acres, a new startup developing a robotic platform for farms, announced today that it has launched an equity crowdfunding campaign that aims to raise $3 million.

The first product that Future Acres is building is Carry, a self-driving robot meant to, as the name suggests, carry crops around a farm. Carry uses GPS, computer vision and machine learning to autonomously navigate a farm (it can also be tele-operated), and can lug 500 lbs. of crops across all types of terrain and inclement weather. The electric robot has a 7 – 10 hour battery life and can travel 6 – 10 miles on a full charge.

Introducing Future Acres

If this sounds familiar, that’s because Carry is similar to Augean Robotics’ Burro, which also autonomously hauls up to 500 lbs of food and gear around the farm.

Future Acres is also looking beyond the simple act of carrying things and towards developing a true autonomous platform that can be used to perform other tasks around the farm like precision spraying, disease detection and, eventually, crop picking.

Farms in the U.S. face labor shortages caused by factors such as COVID restricting the movement of migrant labor and a patchwork of differing state and federal labor laws. Even if a farm is able to secure all of the workers it needs, that work is still hard and done under harsh conditions like extreme heat.

This is where farm automation can help. By automating some of the less skilled work involved with harvesting, such as carrying bushels around, human workers can focus on more delicate tasks such as picking, or coordinating logistical processes.

Right now, Future Acres has one prototype currently being tested. With the new funding it raises, the company will focus on developing the next version of Carry. Future Acres CEO, Suma Reddy, told me by phone last week that the company will work with farms to figure out what business model(s) work best, but right now, the Carry system costs between $800 and $1,200 a month for the hardware and software.

PIX Moving Raises Pre-Series A Round of Funding for Self-Driving “Skateboard” Chassis

PIX Moving, a Chinese company that makes chassis for self-driving vehicles, announced at the end of last week that it has raised a Pre-Series A round of funding. Details in the English-language press release provided to The Spoon didn’t provide a specific dollar amount, only saying it had raised “tens of millions” in Chinese Yuan. The only investor listed in this round is Guizhou Transportation Planning Survey&design Academe Co., ltd.

Dubbed the “skateboard,” PIX’s chassis can be used to power a number of different types of low-speed autonomous vehicles. Most relevant to Spoon readers, restaurant or third-party delivery companies could use affix lockers on top of PIX’s skateboard to make a mobile automat, or a grocer could create a temperature-controlled store on wheels.

According to today’s press announcement, 23 types of vehicles have been developed using PIX’s platform, and vehicles have been delivered to roughly 100 customers around the world. To help speed up production of its skateboard, PIX has also developed Lightsaber, a 3D metal printing manufacturing system that removes the need for molds.

When we last checked in with PIX, the company was still navigating the various regulations around self-driving vehicles in China and the U.S., though the company had deployed vehicles to private campuses in both countries.

While self-driving vehicles still have a number of hurdles to overcome before they go mainstream, they have gotten much closer to hitting the road, as it were, over the past year. Last year, Nuro’s self-driving pod-like vehicle got approvals from the federal and California governments to operate on public roads. More recently, Gatik, which builds autonous delivery trucks for the middle mile, announced that it would operate two of its routes without human drivers this year.

As it moves closer to market, PIX said it will use its new funding to mass produce its vehicles for a variety of applications.

Mars Wrigley Launches Mobile Robotic Kiosk at ShopRite

The impulse aisle in the checkout line has long been the bane of many parents’ grocery shopping trips. While cashiers scan items and parents wait to pay, racks of candy and treats are within arm’s reach of bored kids sitting in carts.

But if you thought tempting kids with treats out checkout was rough, wait until there’s a shiny new robot wandering the grocery aisles, offering up candy.

Mars Wrigley and Wakefern Food Corp. announced last week that they are working with robot company Savioke to deploy a mobile robotic vending kiosk at ShopRite store in Monroe, NY.

According to Kiosk Marketplace, the robot, dubbed “Smiley,” plays music and dances (doing the robot, we assume) (sorry!), while offering up treats and such for sale.

There aren’t a ton of details, such as how many treats Smiley can hold, or the mechanics of how the treats are dispensed and paid for. (We reached out to Mars Wrigley for more information.)

We’ve seen these types of robots before. Self-driving robots can wheel around inside existing retail spaces to act as promotional, err, vehicles, or direct avenues. In China, FANBOT is already scurrying around cinemas, malls and hotels, selling drinks, snacks and more. And Pudutech’s robot, which is basically a series of shelves on wheels, cruise around grocery stores in Japan and the Netherlands, showcasing items that are on sale.

At the risk of tooting my own horn too loudly, automated mobile kiosks was a trend I said to look out for in 2021. So I think we’re going to see a lot more robots roaming store aisles trying to sell us stuff. Maybe their LED faces will need to show a scowl though, to keep the kids away.

MyFitnessPal Adds AI Scanning Technology to iOS for Tracking Calories

MyFitnessPal this week announced the launch of its new AI-powered scanning feature that automates some of the process of identifying and tracking the ingredients in a user’s food items. The company has partnered with Passio, which provides computer vision for companies through its AI platform, to develop this new feature.

If you’ve ever tried using a food tracking app or website, you’ll know what a pain it is to enter every single ingredient of each meal and snack you consume. With MyFitnessPal’s scanning feature, a user selects the Meal Scan feature in the app, then holds their phone’s camera over the food. The AI scanning tool is able to identify the food, both the type and the amount of it, through the combination of Passio’s food recognition technology and MyFitnessPal’s massive database of 14 million foods.

This feature can help users avoid having to search for each ingredient and food within the database, but it is not yet fully automated. After scanning the food, the user must confirm the foods and amounts the app has identified. After confirming, calories, fat, protein in the food is calculated and this information will be automatically added to the user’s food diary.

That being said, using computer vision for tracking food can still save a user a lot of time, and MyFitnessPal is not the only company using something like this. Bite.ai is another company that has a free food tracking app, and it uses a similar technology that applies computer vision to identify food that is then added to the user’s food diary.

MyFitnessPal’s scanning technology is currently available on iOS, and it will be made available for Android phones in the near future. The MyFitnessPal app is free, but only those who are premium members for $9.99/month will have access to the scanning feature.