Obtaining suitable training data remains a core challenge in the development of custom computer vision solutions for industrial applications such as those in supply chain and logistics. Industrial data differs fundamentally from common datasets—it is often domain-specific, making it expensive […]

Software-defined vehicles and in-vehicle AI are reshaping automotive compute from dozens of distributed ECUs to centralized and zonal architectures—fundamentally changing how data movement, power delivery, safety and cost are engineered. This talk compares decentralized, centralized and zonal compute approaches and […]

Industrial visual inspection operates at the intersection of perception, decision-making and physical consequences. Despite advances in automated vision and large foundation models, industrial inspection remains fundamentally unsolved: the assets being inspected are domain-specific and evolving, labeled data is scarce, environments […]

Successful deployment of AI on edge platforms requires system-level strategies that account for critical considerations such as latency bounds, memory behavior and orchestration of heterogeneous hardware cores. In this talk, we present techniques for running deep learning pipelines on edge […]

Reliable localization and mapping are foundational for autonomous vehicles and robots, yet camera-centric systems often degrade in fog, rain, snow, glare or low light—exactly when robust perception is most critical. This talk explores radar-based simultaneous localization and mapping (SLAM) as […]

BNSF is one of four Class I railways in the United States. We maintain 30,000 miles of rail and process 5M+ intermodal shipping containers annually. Maintaining accurate inventory at this scale is a challenge. We’ve developed and deployed an embedded […]