Edge AI and Vision Insights: July 22, 2020 Edition

LETTER FROM THE EDITOR

Dear Colleague,

For less than $300, you can enjoy a first-rate training created by a Google Developer Expert on how to use TensorFlow and Keras for deep learning on computer vision projects. Originally an in-person class offered at the Embedded Vision Summit, we’ve moved the training to an on-line, on-demand format — but with the same great content, Jupyter Notebook labs, and instructor office hours! Are you an engineer who wants to design intelligent computer vision systems that learn from complex or large-scale datasets? Get the hands-on knowledge you need to develop deep learning computer vision applications—both on embedded systems and in the cloud—with TensorFlow, today’s most popular framework for deep learning. See here for more information and to register; use discount code SUMMER20NL until next Friday, July 31 for an additional 20% discount!

Speaking of the Embedded Vision Summit…if you’re a product developer, engineer or business leader looking for real-world, commercial technologies that will help you add visual intelligence and AI to your new products, then you won’t want to miss the new sessions just added to our Enabling Technologies track at the Embedded Vision Summit. You’ll learn about the latest computer vision and AI tools, processors and techniques that you can use to quickly develop innovative products today! Check out the already announced talks in the Enabling Technologies track and other tracks for yourself. (We’re adding new talks daily, and it won’t be long before we’ll have nearly 100 talks across four tracks.) And then be sure to register today with promo code EARLYBIRDNL20-V to receive your Early Bird Discount!

The Embedded Vision and Visual AI Industry Map, recently updated with search support and other enhancements, is a free-to-use tool that provides an efficient way to understand how hundreds of companies fit into the vision industry ecosystem. It is an interactive, visual database that displays companies within different layers of the vision value chain, and in specific end-application markets. It covers the entire embedded vision and visual AI value chain, from sub-components to complete systems. From our immersion in the embedded vision and visual AI industry over the past nine-plus years, we know that the right company-to-company partnerships are essential. We’re excited to provide this Industry Map to help people efficiently find the companies they want to partner with—and to help companies make themselves more visible. Check it out online; we welcome your feedback!

Tomorrow, Thursday, July 23 at 9 am PT, Platform.ai will deliver the free webinar “AI Training Data Image Labeling and Few-Shot Learning: Under the Hood with Platform.ai” in partnership with the Edge AI and Vision Alliance. The time it takes to accurately and comprehensively label training images remains one of the biggest problems in AI. Outsourcing the labeling effort is particularly ineffective in cases where subject matter expertise is necessary to label the images or the images are confidential. Label accuracy in cases involving small training sets also remains a challenge. In this online presentation, Platform.ai will discuss how the company employs a diversity of AI techniques to visualize image sets, facilitating mass expert labeling, as well as how it applies new few-shot learning approaches to solve for low-data cases. For more information and to register, please see the event page.

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

INDUSTRY TRENDS AND TRENDSETTING PRODUCTS

2020 Vision Product of the Year Awards Ceremony
The Vision Product of the Year Awards recognize the innovation and achievement of the industry’s leading technology, service and end-product companies that are enabling the next generation of practical applications for computer vision. The awards are open to Member companies of the Edge AI and Vision Alliance. At a ceremony held online last month, the Embedded Vision Alliance announced this year’s award winners:

NVIDIA (Best AI Processor)
iniVation (Best Camera or Sensor)
Morpho (Best AI Software or Algorithm)
Intel (Best Developer Tool)
Horizon Robotics (Best Automotive Solution)

memorialized in a video recording of the event.

Free Webinar Explores Key Trends in the Deployment of Edge AI and Computer Vision
On August 20, 2020, Jeff Bier, founder of the Edge AI and Vision Alliance, will present two sessions of a free one-hour webinar, “Key Trends in the Deployment of Edge AI and Computer Vision”. The first session will take place at 9 am PT (noon ET), timed for attendees in Europe and the Americas. The second session, at 6 pm PT (9 am CST on August 21), is timed for attendees in Asia. With so much happening in edge AI and computer vision applications and technology, and happening so fast, it can be difficult to see the big picture. This webinar from the Alliance will examine the four most important trends that are fueling the proliferation of edge AI and vision applications and influencing the future of the industry:

Deep learning – the Alliance’s multi-year survey of vision developers shows that deep learning is re-shaping how visual perception is implemented.
Democratization – thanks to cloud computing and higher levels of abstraction in both hardware and software, it is now much easier than ever before for developers to implement edge AI and vision capabilities.
Fast, cheap, energy-efficient processors – massive investment in specialized processors is paying off, delivering 1000x improvements in performance and efficiency, enabling AI and vision to be deployed even in very cost- and energy-constrained applications at the edge.
Enhanced perception – the introduction of new 3D optical, thermal, neuromorphic and other advanced sensor technologies into high-volume applications like mobile phones and automobiles has catalyzed a dramatic acceleration in innovation, collapsing the cost and complexity of implementing visual perception.

Bier will explain what’s fueling each of these key trends, and will highlight key implications for technology suppliers, solution developers and end-users. He will also provide technology and application examples illustrating each of these trends, including spotlighting the winners of the Alliance’s yearly Vision Product of the Year Awards. A question-and-answer session will follow the presentation. See here for more information, including online registration.

COMPUTER VISION FOR AUTONOMOUS DEVICES

Certifying Neural Networks for Autonomous Flight
Deep neural networks have demonstrated impressive performance on visual recognition tasks relevant to the operation of airborne vehicles such as autonomous drones and personal electric air-taxis. For this reason, their application to visual problems, including object detection and image segmentation, is promising (and even necessary) for autonomous flight. The downside of this increased model performance is higher complexity, which poses challenges related to interpretability, explainability and (eventually) the certification of safety-critical aviation applications. In this presentation, David Haber, Head of Deep Learning at Daedalean AI, examines the opportunities and challenges when building AI for safety-critical applications.

AI Computing for Automotive: The Battle for Autonomy
In this summary of the recently published “Artificial Intelligence Computing for Automotive 2020 Report,” the market analyst team at Yole Développement assesses competitors in the race for automobile autonomy, with likely winners determined by success in merging AI and computing. Yole forecasts that the 2025 market for automotive AI, including ADAS and robotic vehicles, is estimated at $2.75B, of which $2.5B will be ADAS-only.