Summit

“Recent Advances in Post-training Quantization,” a Presentation from Intel

Alexander Kozlov, Deep Learning R&D Engineer at Intel, presents the “Recent Advances in Post-training Quantization” tutorial at the September 2020 Embedded Vision Summit. The use of low-precision arithmetic (8-bit and smaller data types) is key for the deployment of deep neural network inference with high performance, low cost and low power consumption. Shifting to low-precision […]

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“The Opportunities and Challenges in Realizing the Potential for AI at the Edge: An Update from the Front Lines,” An Embedded Vision Summit Expert Panel Discussion

Samir Kumar, Managing Director at Microsoft M12, moderates the “Opportunities and Challenges in Realizing the Potential for AI at the Edge: An Update from the Front Lines” Expert Panel at the September 2020 Embedded Vision Summit. Other panelists include Pete Warden, Staff Research Engineer at Google; Stevie Bathiche, Technical Fellow at Microsoft; Steve Teig, CEO

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“The Future of Image Sensors,” An Embedded Vision Summit Expert Panel Discussion

Shung Chieh, Co-founder and Vice President of Engineering at Solidspac3, moderates the “Future of Image Sensors” Expert Panel at the September 2020 Embedded Vision Summit. Other panelists include Sandor Barna, Vice President of Hardware at Aurora; Boyd Fowler, Chief Technology Officer at OmniVision; Sundar Ramamurthy, Group Vice President and General Manager at Applied Materials; and

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“Streamline, Simplify, and Solve for the Edge of the Future,” a General Session Presentation from Intel

Bill Pearson, Vice President of the Internet of Things Group and General Manager of Developer Enabling at Intel, presents the “Streamline, Simplify, and Solve for the Edge of the Future” tutorial at the September 2020 Embedded Vision Summit. Today, edge AI is changing our world — whether it’s smart lab instruments enabling faster blood tests,

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“A New Golden Age for Computer Architecture: Processor Innovation to Enable Ubiquitous AI,” a Keynote Presentation from David Patterson

David Patterson, UC Berkeley professor of the graduate school, a Google distinguished engineer and the RISC-V Foundation Vice-Chair, presents the “A New Golden Age for Computer Architecture: Processor Innovation to Enable Ubiquitous AI” tutorial at the September 2020 Embedded Vision Summit. Paradoxically, processors today are both a key enabler of and a painful obstacle to

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“Perspective On the Past, Present, and Future of Processor Design,” an Alliance Interview with David Patterson

David Patterson, UC Berkeley professor of the graduate school, a Google distinguished engineer and the RISC-V Foundation Vice-Chair, talks with Jeff Bier, Founder of the Edge AI and Vision Alliance, for the “Perspective On the Past, Present, and Future of Processor Design” interview at the September 2020 Embedded Vision Summit. See here for Patterson’s keynote

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“Driver Monitoring Systems: Present and Future,” a Presentation from XPERI

Petronel Bigioi, CTO for Imaging at XPERI, presents the “Driver Monitoring Systems: Present and Future” tutorial at the September 2020 Embedded Vision Summit. Monitoring drivers and passengers inside of vehicles is an increasingly critical capability. For example, driver monitoring is required in order for cars to obtain a top safety rating from NCAP. This presentation

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“High-Bandwidth Multicamera Systems with PCIe Backbone: Snapshot and Outlook on Technologies and Applications,” a Presentation from XIMEA

Kevin Toerne, Sales Engineer at XIMEA, presents the “High-Bandwidth Multicamera Systems with PCIe Backbone: Snapshot and Outlook on Technologies and Applications” tutorial at the September 2020 Embedded Vision Summit. In this presentation, Toerne explores high-bandwidth cameras and their application to multi-camera and embedded systems. He presents solutions for machine vision applications, focused on the use

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“Vitis and Vitis AI: Application Acceleration from Cloud to Edge,” a Presentation from Xilinx

Vinod Kathail, Fellow and Chief Architect at Xilinx, presents the “Vitis and Vitis AI: Application Acceleration from Cloud to Edge” tutorial at the September 2020 Embedded Vision Summit. Xilinx SoCs and FPGAs provide significant advantages in throughput, latency, and energy efficiency for production deployments of compute-intensive applications when compared to CPUs and GPUs. Over the

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“Making Edge AI Inference Programming Easier and Flexible,” a Presentation from Texas Instruments

Manisha Agrawal, Product Marketing Engineer at Texas Instruments, presents the “Making Edge AI Inference Programming Easier and Flexible” tutorial at the September 2020 Embedded Vision Summit. Deploying an AI model at the edge doesn’t have to be challenging—but it often is. Embedded processing vendors have unique sets of software tools for deploying models. It takes

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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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