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Francois Chaubard

CEO, Focal Systems
I'm the CEO of Focal Systems, an AI company that builds Deep Learning Computer Vision solutions to automate brick and mortar retail. Focal Systems works with 15+ of the largest retailers in the world and our technology is deployed in stores on three continents. Prior to founding Focal Systems in 2015, I worked at Apple as a Deep Learning Researcher and as a Missile Guidance Algorithm Engineer at Lockheed Martin. I attended Stanford University where I earned two master degrees in CS and EE.
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  • Posted on: 08/16/2019

    New site wants to make independent grocery jobs into careers

    One of the biggest challenges for all retailers in the current environment is the ability to attract and retain associates that are willing to work a minimal amount of daily/weekly hours at the low end of the pay scale. Flexibility to not only allow but to enable associates to work simultaneously at multiple retailers will provide the associate with a more predictable wage and the retailer a much stronger candidate. To do this retailers must be willing to share schedules among each other to avoid the "this job comes first" mentality. Many of the WFM solution providers have this capability but it is very rarely used because of concerns of competitors getting sensitive information. Having a secure third party platform that contains only shared associate data could be one possible solution. Another major factor in the ability to retain a steady PT associate is the ability to offer benefits. Once shared resources are adopted, this platform could also open the door for a shared benefits package across retailers to take allow the 40 hour associate across multiple retailers the same benefit types as the FT associate in one retailer.
  • Posted on: 08/13/2019

    Grocers develop their own tech responses to Amazon Go

    The challenge for larger format grocery stores versus the smaller Go convenience model is twofold. As other commenters have referred to, there will still likely be a need for cashiers to handle weighted items. This could be mitigated by adding sensors to the carts, but the amount of use a typical shopping cart sees during the day would likely require regular recalibration. Bloomberg has an in-depth article titled "Amazon’s Most Ambitious Research Project Is a Convenience Store" that talks about the challenges of fresh items in this environment and the reasons they abandoned that type of merchandise. The second and larger issue is the costs associated with cameras, compute, and bandwidth. In the Go model, there are about 300-400 cameras covering the 1,000 sq. ft. store, which implies 1 camera per 3 sqft. A large format grocery store is typically 50,000–100,000 sq. ft. This suggests the system would require 15,000 – 30,000 cameras! Each camera produces 30 frames per second of RGB-depth data. With aggressive assumptions on the reduction in compute, camera and scale hardware costs over time, implementing this type of system will likely not prove a positive ROI in large format grocery until 2040 compared to the baseline method of operating the front end with cashiers. Here is a link we published on how we came to that conclusion.
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