Accelerating Automotive AI
IMG SERIES4 MULTI-CORE NNA
Hosted by Andrew Grant
12 November, 2020
Join this webinar to learn about the latest IMG Series4 NNA (neural network accelerator) range of multi-core IP for Artificial Intelligence (AI).
IMG Series4 is a range of multi-cores with a new architecture and advanced features that are ideal for Automotive needs for autonomous vehicles and ADAS.
It is designed to conform to ISO 26262 processes they enable the safe inference of neural networks without performance degradation. Featuring ultra-low latency, low bandwidth thanks to Imagination Tensor Tiling; and with sophisticated workload management, these designs meet the needs of R&D teams as well as SoC designers. The Series4 NNA range can be used for multiple use cases from embedded on-vehicle to cloud and hits the sweet spot for self-driving due to its energy-efficiency, low silicon area, and offline/online mature software tools.
For more information on IMG Series4 NNA, please visit our product page.
About the speaker
Andrew Grant, Senior Director of AI, Imagination Technologies
Andrew Grant joined Imagination in 2018 as Senior Director of Business Development, responsible for strategic business development in AI and building the wider ecosystem of AI partnerships. Mr. Grant advises customers on the impact of new and emerging technologies and how best to utilise neural networks in edge devices.
Prior to working with Imagination Technologies, Mr. Grant was involved with spin-outs from UCL and CERN, chairing Satalia, an AI company based in London, for several years. He has also worked with UCL School of Management, WPP and has completed innovation projects on the Future of Automotive, Aviation, Retail and the IoT. At British Telecom he was a CIO and Marketing leader and he has also worked with Intel and HP.
Mr Grant has a particular interest in autonomous vehicles and ADAS and how AI can be used to create smarter IoT devices for vision, home and robotics use cases and is a frequent visitor to China and the ASEAN region