Abstract:  In all machine learning problems, there is an explicit trade off between cost and benefit. In real world vision problems, this optimization becomes increasingly difficult since those trade offs directly impact technology and product development as well as business strategy. For any successful business case, it is critical that the cost/benefit trade offs in the technical area correctly correlate to the needs of the customer. Furthermore, deep learning does not present accessible answers to “why” a recommendation was made, and this presents challenges for customers unfamiliar with deep learning answers. Here we’ll present how some of these critical challenges at RoadBotics were overcome as we’ve successfully moved from academia, to early adopter customers, and onto market leaders. At each stage we have had to carefully consider these trade offs to successfully commercial our product vision which directly impacted our technology choices.

Bio:  Ben is the President and Co-Founder of RoadBotics and has been the leader of product development at the company since its inception. With a Ph.D. in engineering, Ben has extensive experience in bringing machine learning technologies out of the research lab and successfully into the market. Ben brings a data driven management culture to the teams he leads in order to rapidly grow companies in a fast paced start-up environment by harnessing and executing on a cohesive strategic vision. As a successful serial entrepreneur, Ben is always focused on transitioning companies from product innovators to market leaders.

Homepage:  https://www.roadbotics.com,https://www.linkedin.com/in/schmidtbt/