Software is becoming the critical differentiator in AI edge app development and adoption. This presentation will examine a new approach for enterprises challenged to take AI edge products from idea to production fast, but lacking the right talent, tools and […]
Detecting defects in parts and products is a common need in manufacturing. We will show how to use Laon People’s AI machine vision tools to develop solutions for product defect inspection applications. Manufacturers find these easy-to-use tools highly accurate, robust […]
Come join Raymond Lo and Soren Knudsen from the Intel OpenVINO toolkit team to hear what they have learned about what developers need from AI tools. How does the OpenVINO team get feedback from developers? (Do they even want it?) […]
80% of AI projects never reach broad deployment. In this roundtable discussion, we’ll have a lively debate and dialogue to re-think the promise of AI and uncover why successfully taking AI solutions to production—to actually doing something wonderful in the […]
Edge AI provides benefits for cost, latency, privacy, and connectivity. Developing and deploying optimized, accurate and effect AI on edge-based systems is a time-consuming, challenging and complex process. In this session, you will learn how NVIDIA makes it easier for […]
In this talk, we’ll explain why we targeted autonomous valet parking (AVP) with our newest APACHE6 SoC, and how we tailored the chip design for this application. Our sister company, VADAS, will share insights from their development of camera-based AVP […]
Xilinx Kria System-on-Modules (SOMs) provide a secure, production-ready multi-core Arm and FPGA platform, including memories, power management, and Yocto or Ubuntu Linux to build accelerated AI-enabled applications at the edge. Kria SOMs enable smart vision applications across cities, factories, and […]
When developing a new edge AI solution, you want to focus on your system’s unique functionality. In this session, we will share the different foundational developer kits available from Intel’s partners to help speed your edge AI solution development. These […]
The ability to perform neural network inference in resource-constrained devices is fueling the growth of machine learning at the edge. But application solutions require more than just inference—they also incorporate aggregation and pre-processing of input data, and post-processing of inference […]
Computer-vision-enabled cameras have demonstrated the potential to bring compelling functionality to numerous applications. But to realize the full potential and assist with the growth of AI-enabled cameras, we must drastically simplify the work of developing, deploying and maintaining these cameras. […]
