Can you share your journey from working at NASA’s Jet Propulsion Laboratory to becoming the CTO of Standard AI?

When I was at The Jet Propulsion Laboratory, my work focused primarily on large scale data management for NASA missions. I got to work with incredible scientists and engineers, learning about how to conduct research from outer space. Not only did I learn a lot about data science, but also large-scale engineering project management, balancing risk and error budgets, and large-scale software systems design. My PhD work at the University of Southern California was in the area of software architectures for high performance computing, and I was able to see the application of that research first-hand.

What motivated the shift in Standard AI's focus from autonomous checkout solutions to broader retail AI applications?

Standard AI was founded seven years ago with the mission to bring autonomous checkout to market. While we succeeded in delivering the best-in-class computer vision only solution to autonomous checkout and launched autonomous stores, ultimately we found that user adoption was slower than anticipated and consequently, the return on investment wasn’t there for retailers.

At the same time, we realized that there were a number of problems the retailer experienced that we could solve through the same underlying technology. This renewed focus on operational insights and improvements allowed Standard to deliver a more direct ROI to retailers who are looking for opportunities to improve their efficiencies in order to offset the effects of inflation and increased labor costs.

How does Standard AI’s computer vision technology track customer interactions with such high accuracy without using facial recognition?

Standard’s VISION platform is designed to track shoppers in real space by analyzing video from overhead cameras in the store, distinguishing between humans and other elements in each video, and estimating the pose, or skeletal structure, of each human. By looking through multiple cameras at the same time, we can reconstruct a 3D understanding of the space, just like we do with our two eyes. Because we have very precise measurements of each camera’s position, we can reconstruct a shopper’s position, orientation, and even hand placement, with high accuracy. Combined with advanced mapping algorithms, we can determine shopper movement and product interaction with 99% accuracy.

How does Standard AI ensure the privacy of shoppers while collecting and analyzing data?

Unlike other tracking systems that use facial recognition to identify shoppers between two different video streams, when Standard is determining a shopper’s pose, we are just using structural information and spatial geometry. At no time does Standard’s tracking system rely on shopper biometrics that can be used for identification like the shopper’s face. In other words, we don’t know who a shopper is, we just know how shoppers are moving through the store.

What are some of the most significant insights retailers can gain from using Standard AI’s VISION platform?

Retailers can gain a number of insights using Stand’s VISION platform. Most significantly, retailers are able to get a better understanding of how shoppers are moving through their space and interacting with products. While other solutions give a basic understanding of traffic volume through a specific portion of a store, Standard records every shopper’s individual path and can distinguish between shoppers and store employees to give a better accounting of not just traffic and dwell, but the specific behaviors of shoppers that are buying products.