AI on the Edge: Scaling Machine Learning Solutions

Date: Archived version now available
Duration: 1 Hour

This webinar is part of our TechXchange webinar series and the AI on the Edge TechXchange, where you can find additional articles and resources. 

Description

Artificial-intelligence (AI) solutions have taken the embedded community by storm, including high-performance solutions in the cloud. On the edge, inclusion of machine learning (ML) becomes more challenging because of size, weight, and power (SWaP) constraints, but this doesn’t force AI/ML solutions to be tied to the cloud. There are many options for AI/ML on the edge. However, it can be a challenge to know what’s available and how powerful a solution can fit within the desired design constraints.

We have gathered a group of experts who will discuss embedded AI/ML from microcontrollers to dedicated, high-performance solutions that can address everything from smart motor control to robotics and self-driving cars.

Host:

William Wong
Editor/Electronic Design
Senior Content Director/Endeavor Business Media

Panelists:

 

Ali Osman Örs
AI ML Strategy and Technologies Lead/NXP

Ali currently leads the AI/ML and related enablement strategy and technology activities for NXP’s Edge processing portfolio. He previously held leadership roles in AI strategy,  strategic partnerships, and platform designs for ADAS and Autonomous products in the automotive business line and has served as a director on the board  for several industry consortia related to autonomous driving. Prior to joining NXP, Ali was VP of Engineering for CogniVue Corp and led the R&D teams developing vision SoC solutions and Cognition Processor IP cores. Ali holds an engineering degree from Carleton University in Ottawa, Canada.

Amit Goel
Director, Product Management/NVIDIA

Amit Goel is Director of Product Management for Autonomous Machines at NVIDIA, where he leads the product development of NVIDIA Jetson, the most advanced platform for AI computing at the edge.

Amit has more than 15 years of experience in the technology industry working in both software and hardware design roles. Prior to joining NVIDIA in 2011, he worked as a senior software engineer at Synopsys, where he developed algorithms for statistical performance modeling of digital designs.

Amit holds a Bachelor of Engineering in electronics and communication from Delhi College of Engineering, a Master of Science in electrical engineering from Arizona State University, and an MBA from the University of California at Berkeley.

Deepak Boppana
Senior Director of Segment and Solutions Marketing/
Lattice Semiconductor

Deepak Boppana is the Senior Director of Segment and Solutions Marketing at Lattice Semiconductor. Since joining Lattice in 2012, Deepak has been driving secure, flexible, and low-power FPGA solutions for transformative technologies impacting multiple end markets, such as IoT, 5G wireless, embedded vision, and artificial intelligence/machine learning. He has more than 18 years of semiconductor product management and business development experience, including prior strategic marketing roles at Intel (Altera). Deepak holds a Master of Science in Electrical Engineering from Villanova University, and has been quoted extensively in various technical articles, analyst interviews, and press/trade publications.

 

Original post: https://www.electronicdesign.com/technologies/embedded-revolution/article/21179014/electronic-design-ai-on-the-edge-scaling-machine-learning-solutions

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