Jeff Bier, Founder of the Edge AI and Vision Alliance, welcomes attendees to the May 2021 Embedded Vision Summit on May 28, 2021. Bier provides an overview of the edge AI and vision market opportunities, challenges, solutions and trends. He also introduces the Edge AI and Vision Alliance and the resources it offers for both […]
May 2021 Embedded Vision Summit Opening Remarks (May 28) Read More +
Jeff Bier, Founder of the Edge AI and Vision Alliance, welcomes attendees to the May 2021 Embedded Vision Summit on May 27, 2021. Bier provides an overview of the edge AI and vision market opportunities, challenges, solutions and trends. He also introduces the Edge AI and Vision Alliance and the resources it offers for both
May 2021 Embedded Vision Summit Opening Remarks (May 27) Read More +
Jeff Bier, Founder of the Edge AI and Vision Alliance, welcomes attendees to the May 2021 Embedded Vision Summit on May 26, 2021. Bier provides an overview of the edge AI and vision market opportunities, challenges, solutions and trends. He also introduces the Edge AI and Vision Alliance and the resources it offers for both
May 2021 Embedded Vision Summit Opening Remarks (May 26) Read More +
Jeff Bier, Founder of the Edge AI and Vision Alliance, welcomes attendees to the May 2021 Embedded Vision Summit on May 25, 2021. Bier provides an overview of the edge AI and vision market opportunities, challenges, solutions and trends. He also introduces the Edge AI and Vision Alliance and the resources it offers for both
May 2021 Embedded Vision Summit Opening Remarks (May 25) Read More +
Professor Pieter Abbeel, Director of the Berkeley Robot Learning Lab and Co-Director of the Berkeley Artificial Intelligence (BAIR) Lab, talks with Jeff Bier, Founder of the Edge AI and Vision Alliance, for the “Perspectives on AI Beyond Pattern Recognition” interview at the May 2021 Embedded Vision Summit. See here for Abbeel’s keynote at the Summit,
Professor Pieter Abbeel, Director of the Berkeley Robot Learning Lab and Co-Director of the Berkeley Artificial Intelligence (BAIR) Lab, presents the “From Inference to Action: AI Beyond Pattern Recognition” tutorial at the May 2021 Embedded Vision Summit. Pattern recognition—such as that used in image recognition, speech recognition and machine translation—has been the primary focus of
APPLICATION CASE STUDIES Combining CNNs and Conventional Algorithms for Low-Compute Vision: A Case Study in the Garage Chamberlain Group (CGI) is a global leader in access control solutions with its Chamberlain and LiftMaster garage door opener brands and myQ connected technology. In this presentation from Nathan Kopp, the company’s Principal Software Architect for Video Systems,
Edge AI and Vision Insights: August 31, 2021 Edition Read More +
Neil Trevett, Vice President of Developer Ecosystems at NVIDIA and President of the Khronos Group, presents the “Khronos Group Standards: Powering the Future of Embedded Vision” tutorial at the May 2021 Embedded Vision Summit. Open standards play an important role in enabling interoperability for faster, easier deployment of vision-based systems. With advances in machine learning,
LETTER FROM THE EDITOR Dear Colleague, On Thursday, September 16 at 9 am PT, Edge Impulse will deliver the free webinar “Introducing the EON Tuner: Edge Impulse’s New AutoML Tool for Embedded Machine Learning” in partnership with the Edge AI and Vision Alliance. Finding the best machine learning (ML) model for analyzing sensor data isn’t
Edge AI and Vision Insights: August 17, 2021 Edition Read More +
LETTER FROM THE EDITOR Dear Colleague, On Tuesday, 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.
Edge AI and Vision Insights: August 3, 2021 Edition Read More +
Here you’ll find a wealth of practical technical insights and expert advice to help you bring AI and visual intelligence into your products without flying blind.
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