Edge AI and Vision Insights: September 28, 2021 Edition

Today, September 28 at 9 am PT, Sequitur Labs will deliver the free webinar “Securing Smart Devices: Protecting AI Models at the Edge” in partnership with the Edge AI and Vision Alliance. Billions of new IoT devices are expected to come online in just the next few years. Securing these devices is an area of significant concern–to date, about half of IoT vendors have experienced at least one security breach. IoT vendors need to ensure that their products are designed, manufactured and deployed without risk of being compromised. And the problem is becoming even more serious with the deployment of AI models at the network edge. Implementing IoT security, is, however, a big challenge. It requires understanding a variety of new features and functions, a steep learning curve in learning how to implement these features using the silicon of choice, and an investment in mastering a diverse, fragmented microprocessor market, since each microprocessor vendor implements security differently. This webinar will cover best practices for securing smart devices at the edge, including a number of methods for protecting AI models, as well as real-life case studies and demonstrations of the concepts discussed. For more information and to register, please see the event page.

And next Tuesday, October 5 at 9 am PT, Eta Compute will deliver the free webinar “How Battery-powered Intelligent Vision is Bringing AI to the IoT” in partnership with the Edge AI and Vision Alliance. In today’s landscape for the enterprise Internet of Things (IoT), the promise of artificial intelligence (AI) is as yet unfulfilled. Existing solutions are complex and expensive to deploy and do not address the numerous cases where low power consumption is critical. In this webinar, you’ll learn about various applications for AI at the edge, as well as how battery-operated and AI-based computer vision can solve real-world problems and create business value. A case study example will highlight Eta Compute’s space monitoring sensor, Tally. By providing high-accuracy, reliable local insights in an easy-to-deploy form factor, Tally helps enterprises in building, hospitality, and retail make better decisions and optimize occupants’ space and well-being. For more information and to register, please see the event page.

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

From Inference to Action: AI Beyond Pattern Recognition
Pattern recognition—such as that used in image recognition, speech recognition and machine translation—has been the primary focus of the last decade’s progress in artificial intelligence. But intelligence fundamentally requires more than mere pattern recognition: It also requires the ability to achieve goal-oriented behaviors. Two new methods, deep reinforcement learning and deep imitation learning, provide paradigms for learning goal-oriented behaviors and have shown great promise in recent research. These approaches have demonstrated remarkable success in learning to play video games, learning to control simulated and real robots, mastering the classical game of Go and automation of character animation. In this 2021 Embedded Vision Summit keynote presentation, Professor Pieter Abbeel, Director of the Berkeley Robot Learning Lab and Co-Director of the Berkeley Artificial Intelligence (BAIR) Lab describes the ideas underlying these advances, and their current capabilities and limitations, with a focus on practical applications. He explores the characteristics that have unlocked important new use cases (e.g., AI robotic automation in warehouses) while others (e.g., self-driving cars) remain AI-bottlenecked. He also highlights important areas where significant breakthroughs are still needed.

Also see Abbeel’s Q&A session with Jeff Bier, the founder of the Edge AI and Vision Alliance, also at the Summit.

5G and AI: Transforming the Next Generation of Robotics
Bringing together the transformative power of 5G and AI technologies is essential to driving the next generation of high-compute, low-power robots and drones for consumer, enterprise and industrial sectors. In this presentation, Kishore Chakravadhanula, Staff Product Manager at Qualcomm, discusses how scaling 5G and AI will help solve a diverse set of robotics challenges—from enabling high-accuracy AI inferencing and superior power efficiency to enhanced security and connectivity. Chakravadhanula explains why these advances are key to enabling the robotics ecosystem and accelerating growth in segments from automated guided vehicles, autonomous mobile robots, delivery robots and drones to inventory, industrial, and collaborative robots. Additionally, he highlights recent use cases including how our AI and computer vision technologies are enabling autonomous flight on Mars and enabling your home vacuum robot to map rooms and avoid obstacles.

Embedded Vision in ADAS and Autonomous Vehicles: Navigating the New Reality
In this presentation, Mark Fitzgerald, Director of Autonomous Vehicle Service at Strategy Analytics, presents market forecasts for vision technologies in automotive advanced driver assist systems (ADAS), and explores the applications and industry forces that are driving camera fitment in vehicles. He also examines the unprecedented changes unfolding in the automotive industry – with long-standing vehicle architectures and business models under threat – and assesses the impact of COVID-19 on the industry. Fitzgerald explains the influence of government mandates on the ADAS market, including the three generations of driver monitoring systems. Finally, he highlights what is most important and what is at stake as the automotive industry transitions to higher levels of ADAS and autonomous systems.

Winds of Change in the Automotive Semiconductor Industry
The automotive industry faces new business and technological challenges, while undergoing dramatic changes in its value chain, notes Yole Développement in a recently published market research report. Yole’s analysts forecast that the aggregate of connectivity, ADAS, sharing and electrification (C.A.S.E.) applications in vehicles will be a $318B market in 2035, and that the chip-level semiconductor value in cars will reach $78.5B in 2026 with a 14.75% compound annual growth rate from 2020 to 2026.

Securing Smart Devices: Protecting AI Models at the Edge – Sequitur Labs Webinar: September 28, 2021, 9:00 am PT

How Battery-powered Intelligent Vision is Bringing AI to the IoT – Eta Compute Webinar: October 5, 2021, 9:00 am PT

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Hailo Hailo-8 AI Processor (Best Edge AI Processor)
Hailo’s Hailo-8 AI Processor is the 2021 Edge AI and Vision Product of the Year Award Winner in the Edge AI Processors category. Hailo’s AI chip is transforming visual intelligence for multiple industries, enabling smart devices to run neural network-based applications such as detection and segmentation more effectively at the edge. The Hailo-8 processes high-resolution data streams in real time, enabling cameras to detect objects from greater distances. The chip is also capable of processing multiple camera streams on a single device, making it more cost-effective. And computing at the edge reduces the need to transport data to the cloud, enhancing data privacy.

Please see here for more information on Hailo’s Hailo-8 Processor. 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.