IoT device development has traditionally relied on a monolithic approach, with all firmware developed by a single vendor using a rigid waterfall model, typically in C, and infrequently updated. This paradigm is insufficient. For AI-enabled IoT devices to reach their […]
Join us to learn all about NXP’s just-launched i.MX 93 applications processor family. The i.MX 93 is built with NXP’s innovative Energy Flex architecture, which delivers high performance, low power consumption and incredible versatility at an affordable price. We’ll introduce […]
When you think about building a vision-enabled product, you probably think about things like: Which processor am I going to use? What neural network will it run? Where will I get the training data? These are important questions that need […]
Join us to hear about the new Hailo-15 AI vision processor family, specifically designed to empower smart cameras with unprecedented AI capabilities. In this talk, we’ll explain how the Hailo-15 family of processors—with performance ranging from 7 to 20 tera […]
The AIoT industry is expected to reach $1T by 2030—but that will happen only if edge devices rapidly become more intelligent. In this presentation, we’ll show how BrainChip’s Akida IP solution enables improved edge ML accuracy and on-device learning with […]
The phrase “garbage in, garbage out” is applicable to machine and human vision. If we can improve the quality of image data at the source by removing noise, this will have far-reaching impacts, such as improved accuracy later in the […]
The Qualcomm AI Stack revolutionizes how we think about AI software and provides the ultimate tool and user interface to enable our ecosystem partners to create faster and smarter AI applications for all embedded form factors. Focusing on real user […]
Being first to market can mean the difference between success and failure of a new product. But rapid product development brings challenges. With the growing use of AI in embedded vision applications, designers need more flexibility to change and refine […]
ImmersiView is a deep learning–based augmented reality solution for automotive safety. It uses a head-up display to draw a driver’s attention to important objects. The development of such solutions often resembles research more than development, with long development cycles and […]
Until recently, the majority of sensor-based AI processing used vision and speech inputs. Recently, we have begun to see radar, LiDAR, event-based image sensors and other types of sensors used in new AI applications. And, increasingly, system developers are incorporating […]
