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Wednesday, September 22 • 4:40pm - 5:20pm
Artificial Intelligence: The transition to edge computing and beyond

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AI applications and systems are proliferating rapidly, automating and making more efficient a broad range of processes and tasks across every facet of our lives. AI has traditionally been deployed in the cloud because AI solutions require high-performance computing access and remote data centers, which means they are extremely data bandwidth and power-hungry. AI at the edge which allows localized decision making, whereby applications and devices can collect and analyze data on their own, offers a solution to significantly reduce the data transfer and energy impact. 
Edge AI is also gaining momentum because it offers meaningful innovation for consumer products, building management, predictive maintenance, self-driving for vehicles, and much more. There is growing interest in this type of technology because it can change how we interact with applications while better protecting personal data, reducing latency, and allowing decision autonomy at the point of use. But to realize this promise Edge AI has several challenges, in terms of constraints related to the amount of computing, memory, and power budget that these edge devices can sustain. In this Keynote, we look at the various facets of solution innovation to meet these Edge AI challenges including the new paradigm of System-Technology Co-Optimization to design the next generation of Edge AI products

avatar for Nitin Chawla

Nitin Chawla

ST Fellow Strategy & Innovation, ST Microelectronics

Wednesday September 22, 2021 4:40pm - 5:20pm IST