Edge AI and Vision Insights: January 25, 2023 Edition

On Thursday, March 2, 2023 at 9 am PT, the Yole Group will deliver the free webinar “Short-wave Infrared: The Dawn of a New Imaging Age?” in partnership with the Edge AI and Vision Alliance. The term short wave refers to a portion of the infrared spectrum between 1 µm and 3 µm in wavelength. Short-wave infrared (SWIR) imagers based on InGaAs technology have found use in defense markets, for example, where they implement laser target designation and enhanced vision in harsh conditions, as well as in industrial applications such as semiconductor defect detection, package content inspection and inventory sorting.

Historically, SWIR imaging has been a niche market, with cost a key factor limiting broader adoption. InGaAs image sensors typically range in cost from a few thousand to more than ten thousand dollars. However, SWIR is now at a turning point, driven by the emergence of more cost-effective implementations based on quantum dots, germanium and various organic and other materials. The promise of lower-price image sensors has attracted interest in SWIR from consumer electronics and other high-volume applications. For this market growth potential to become a reality, however, the technology will also require further refinement in sensitivity, dark current, response time and other metrics.

In this webinar, Axel Clouet, Ph.D., technology and market analyst at the Yole Group, will discuss the history, current status and future technology and market trends for SWIR imaging, including comparisons with alternative imaging approaches, as well as the evolving and maturing ecosystem that supports SWIR imaging. A question-and-answer session will follow the presentation. For more information and to register, please see the event page.

Registration is now open for the 2023 Embedded Vision Summit, coming up May 22-25 in Santa Clara, California! The Summit is the premier conference and tradeshow for innovators incorporating computer vision and visual or perceptual AI in products. The program is designed to cover the most important technical and business aspects of practical computer vision, deep learning and perceptual AI. Register now and you can save 25%: don’t delay!

Brian Dipert
Editor-In-Chief, Edge AI and Vision Alliance

A Highly Scalable, Heterogeneous and Secure Processor for High-performance AI/ML in Smart Edge Devices
AI capabilities have become an integral part of many products across a wide range of markets and applications. Increasingly, system developers prefer to implement AI workloads at the edge. This leads to a key challenge: meeting the growing computational demands of AI algorithms with hardware suitable for the edge, where power consumption is constrained. In this presentation, Yair Siegel, Senior Director of Business Development at CEVA, introduces the NeuPro-M, CEVA’s latest AI processor architecture, and shows how it addresses today’s main AI processing challenges, such as adapting to the latest DNN topologies and reducing risk and design time via a full-featured software development kit. By examining some of the NeuPro-M’s heterogeneous processing features, he shows how it achieves its exceptional ML performance, high TOPS-per-watt ratio and scalability—which enable it to meet requirements of a diverse set of use-cases for a wide range of end markets including automotive, mobile, consumer, robotics, industrial, telecommunication, defense and IoT.

A Novel Packet-based Accelerator for Resource-Constrained Edge Devices
As AI applications move from cloud platforms into edge devices, processor designers are increasingly incorporating hardware accelerators for real-time AI processing. These accelerators must meet tight cost, bandwidth and power consumption constraints, while still delivering the high performance needed by consumer, automotive and industrial system developers. In this talk, Sharad Chole, Chief Scientist and Co-founder of Expedera, introduces Expedera’s revolutionary packet-based AI accelerator architecture. He illustrates how this novel architecture eliminates bandwidth bottlenecks that limit conventional architectures, leading to significantly better performance and efficiency.

Building Embedded Vision Products: Management Lessons From The School of Hard Knocks
It’s hard to build embedded AI and vision products, and the challenges aren’t just technical. In this talk, Phil Lapsley, Vice President of the Edge AI and Vision Alliance, shares management pitfalls frequently encountered when planning and building embedded vision systems. He focuses on the importance of understanding exactly what problem you’re solving with vision—and why you’re solving it—and the customer and business benefits enabled by this clarity. Lapsley highlights the importance of collaboration between engineering and product marketing. For those who are new to embedded vision development, he acquaints you with some of the common difficulties encountered in such work, and concludes with suggested management best practices for embedded vision/AI product development.

Deploying Visual AI on Edge Devices: Lessons From the Real World
Developing an AI-based edge device is complex, involving hardware, algorithms and software. It requires making many technology-selection decisions and balancing numerous trade-offs. In this talk, Luc Chouinard, AI Specialist and Design Architect at Teledyne Imaging, explores several of the most important decisions and challenges typically encountered in creating an edge visual AI solution. On the hardware side, he explores choosing a processor, including evaluating performance, cost and power, and understanding the capabilities of on-chip processing engines such as CPUs, AI accelerators and ISPs. Chouinard also examines the process of selecting, training and evaluating deep neural network topologies, and he illustrates how Astrocyte, Teledyne’s deep learning tool, helps simplify this process. Next, he discusses key considerations for creating an optimized, efficient hardware/software pipeline implementing the trained DNNs on the edge device. Finally, Chouinard uses an AI camera solution developed for traffic tolling to show how these concepts play out in real applications.

Implementing Advanced AI-based Analytics for Video Management Systems – Hailo Webinar: February 7, 2023, 9:00 am PT

Short-wave Infrared: The Dawn of a New Imaging Age? – Yole Group Webinar: March 2, 2023, 9:00 am PT

Embedded Vision Summit: May 22-25, 2023, Santa Clara, California

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Sequitur Labs EmSPARK Security Suite 3.0 (Best Edge AI Software or Algorithm)
Sequitur Labs’ EmSPARK Security Suite 3.0 is the 2022 Edge AI and Vision Product of the Year Award winner in the Edge AI Software and Algorithms category. The EmSPARK Security Suite is a software solution that makes it easy for IoT and edge device vendors to develop, manufacture, and maintain secure and trustworthy products. By implementing the EmSPARK Security suite, enabled by industry-leading processors, device OEMs can: isolate and protect security credentials to prevent device compromise, protect critical IP, including device-resident software, prevent supply chain compromises with secure software provisioning and updates and accelerate time-to-market while reducing implementation cost and overall security risk. The EmSPARK Security Suite is the industry’s first solution to provide a suite of tools for protecting AI models at the Edge. With the release of EmSPARK 3.0, developers can safely deploy AI models on IoT devices, opening the door for a new era of edge computing.

Please see here for more information on Sequitur Labs’ EmSPARK Security Suite 3.0. The Edge AI and Vision Product of the Year Awards celebrate the innovation of the industry’s leading companies that are developing and enabling the next generation of edge AI and computer vision products. Winning a Product of the Year award recognizes a company’s leadership in edge AI and computer vision as evaluated by independent industry experts.