Eli Gorovici loves to take friends sailing on the Mediterranean. As the new pilot of Trigo, a Tel Aviv-based startup, he’s inviting the whole retail industry on a cruise to a future with AI.
“We aim to bring the e-commerce experience into the brick-and-mortar supermarket,” said Gorovici, who joined the company as its chief business officer in May.
The journey starts with the sort of shopping anyone who’s waited in a long checkout line has longed for.
You fill up your bags at the market and just walk out. Magically, the store knows what you bought, bills your account and sends you a digital receipt, all while preserving your privacy.
Trigo is building that experience and more. Its magic is an AI engine linked to cameras and a few weighted shelves for small items a shopper’s hand might completely cover.
With these sensors, Trigo builds a 3D model of the store. Neural networks recognize products customers put in their bags.
When shoppers leave, the system sends the grocer the tally and a number it randomly associated with them when they chose to swipe their smartphone as they entered the store. The grocer matches the number with a shopper’s account, charges it and sends off a digital bill.
And that’s just the start.
An Online Experience in the Aisles
Shoppers get the same personalized recommendation systems they’re used to seeing online.
“If I’m standing in front of pasta, I may see on my handset a related coupon or a nice Italian recipe tailored for me,” said Gorovici. “There’s so much you can do with data, it’s mind blowing.”
The system lets stores fine-tune their inventory management systems in real time. Typical shrinkage rates from shoplifting or human error could sink to nearly zero.
AI Turns Images into Insights
Making magic is hard work. Trigo’s system gathers a petabyte of video data a day for an average-size supermarket.
It uses as many as four neural networks to process that data at mind-melting rates of up to a few hundred frames per second. (By contrast, your TV displays high-definition movies at 60 fps.)
Trigo used a dataset of up to 500,000 2D product images to train its neural networks. In their daily operations, the system uses those models to run millions of inference tasks with help from NVIDIA TensorRT software.
The AI work requires plenty of processing muscle. A supermarket outside London testing the Trigo system uses servers in its back room with 40-50 NVIDIA RTX GPUs. To boost efficiency, Trigo plans to deliver edge servers using NVIDIA T4 Tensor Core GPUs and join the NVIDIA Metropolis ecosystem starting next year.
Trigo got early access to the T4 GPUs thanks to its participation in NVIDIA Inception, a program that gives AI startups traction with tools, expertise and go-to-market support. The program also aims to introduce Trigo to NVIDIA’s retail partners in Europe.
In 2021, Trigo aims to move some of the GPU processing to Google, Microsoft and other cloud services, keeping some latency- or privacy-sensitive uses inside the store. It’s the kind of distributed architecture businesses are just starting to adopt, thanks in part to edge computing systems such as NVIDIA’s EGX platform.
Big Supermarkets Plug into AI
Tesco, the largest grocer in the U.K., has plans to open its first market using Trigo’s system. “We’ve vetted the main players in the industry and Trigo is the best by a mile,” said Tesco CEO Dave Lewis.
Israel’s largest grocer, Shufersal, also is piloting Trigo’s system, as are other retailers around the world.
Trigo was founded in 2018 by brothers Michael and Daniel Gabay, leveraging tech and operational experience from their time in elite units of the Israeli military.
Seeking his next big opportunity in his field of video technology, Gorovici asked friends who were venture capitalists for advice. “They said Trigo was the future of retail,” Gorovici said.
Like sailing in the aqua-blue Mediterranean, AI in retail is a compelling opportunity.
“It’s a trillion-dollar market — grocery stores are among the biggest employers in the world. They are all being digitized, and selling more online now given the pandemic, so maybe this next stage of digital innovation for retail will now move even faster,” he said.
As businesses and schools consider reopening around the world, they’re taking safety precautions to mitigate the lingering threat of COVID-19 — often taking the temperature of each individual entering their facilities.
Fever is a common warning sign for the virus (and the seasonal flu), but manual temperature-taking with infrared thermometers takes time and requires workers stationed at a building’s entrances to collect temperature readings. AI solutions can speed the process and make it contactless, sending real-time alerts to facilities management teams when visitors with elevated temperatures are detected.
Central California-based IntelliSite Corp. and its recently acquired startup, Deep Vision AI, have developed a temperature screening application that can scan over 100 people a minute. Temperature readings are accurate within a tenth of a degree Celcius. And customers can get up and running with the app within a few hours, with an AI platform running on NVIDIA GPUs on premises or in the cloud for inference.
“Our software platform has multiple AI modules, including foot traffic counting and occupancy monitoring, as well as vehicle recognition,” said Agustin Caverzasi, co-founder of Deep Vision AI, and now president of IntelliSite’s AI business unit. “Adding temperature detection was a natural, easy step for us.”
The temperature screening tool has been deployed in several healthcare facilities and is being tested at U.S. airports, amusement parks and education facilities. Deep Vision is part of NVIDIA Inception, a program that helps startups working in AI and data science get to market faster.
“Deep Vision AI joined Inception at the very beginning, and our engineering and research teams received support with resources like GPUs for training,” Caverzasi said. “It was really helpful for our company’s initial development.”
COVID Risk or Coffee Cup? Building AI for Temperature Tracking
As the pandemic took hold, and social distancing became essential, Caverzasi’s team saw that the technology they’d spent years developing was more relevant than ever.
“The need to protect people from harmful viruses has never been greater,” he said. “With our preexisting AI modules, we can monitor in real time the occupancy levels in a store or a hospital’s waiting room, and trigger alerts before the maximum occupancy is reached in a given area.”
With governments and health organizations advising temperature checking, the startup applied its existing AI capabilities to thermal cameras for the first time. In doing so, they had to fine-tune the model so it wouldn’t be fooled by false positives — for example, when a person shows up red on a thermal camera because of their cup of hot coffee..
This AI model is paired with one of IntelliSite’s IoT solutions called human-based monitoring, or hBM. The hBM platform includes a hardware component: a mobile cart mounted with a thermal camera, monitor and Dell Precision tower workstation for inference. The temperature detection algorithms can now scan five people at the same time.
Double Quick: Faster, Easier Screening
The workstation uses the NVIDIA Quadro RTX 4000 GPU for real-time inference on thermal data from the live camera view. This reduces manual scanning time for healthcare customers by 80 percent, and drops the total cost of conducting temperature scans by 70 percent.
Facilities using hBM can also choose to access data remotely and monitor multiple sites, using either an on-premises Dell PowerEdge R740 server with NVIDIA T4 Tensor Core GPUs, or GPU resources through the IntelliSite Cloud Engine.
If businesses and hospitals are also taking a second temperature measurement with a thermometer, these readings can be logged in the hBM system, which can maintain records for over a million screenings. Facilities managers can configure alerts via text message or email when high temperatures are detected.
The Deep Vision developer team, based in Córdoba, Argentina, also had to adapt their AI models that use regular camera data to detect people wearing face masks. They use the NVIDIA Metropolis application framework for smart cities, including the NVIDIA DeepStream SDK for intelligent video analytics and NVIDIA TensorRT to accelerate inference.
Deep Vision and IntelliSite next plan to integrate the temperature screening AI with facial recognition models, so customers can use the application for employee registration once their temperature has been checked.
IntelliSite is a member of the NVIDIA Clara Guardian ecosystem, bringing edge AI to healthcare facilities. Visit our COVID page to explore how other startups are using AI and accelerated computing to fight the pandemic.
FDA disclaimer: Thermal measurements are designed as a triage tool and should not be the sole means of diagnosing high-risk individuals for any viral threat. Elevated thermal readings should be confirmed with a secondary, clinical-grade evaluation tool. FDA recommends screening individuals one at a time, not in groups.