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Driving AI at the edge with neuromorphic computing

January 26, 2021

RESEARCH REPORT

In brief

Powering sophisticated smart products

See neuromorphic computing in action

AI powered by brain-like computing architectures

We’ve seen a lot of progress in scaling and industrialization of neuromorphic architectures. Still, building and deploying complete neuromorphic solutions will require overcoming some additional challenges.

Energy efficiency

Neuromorphic systems are several orders of magnitude more energy efficient than general purpose computing architectures.

Low latency

Neuromorphic systems excel at processing continuous streams of data and deploying neuromorphic processors at the edge reduces the delay to analysis.

Adaptive processing

Neuromorphic system architectures let devices adapt to changes in context.

Rapid learning

Recent advances in training neuromorphic systems have enabled rapid learning from little data—capabilities beyond most conventional AI systems.

Looking forward

Alex Kass

LEAD – DIGITAL EXPERIENCES R&D, ACCENTURE LABS

Alex Kass is a Fellow and Principal Director, Future Technologies R&D, Accenture Labs. He is an expert in AI and human-machine interaction.​


Tim Shea

RESEARCH LEAD – NEUROMORPHIC COMPUTING, ACCENTURE LABS

Tim applies emerging technology to empower people. His work focuses on Neuromorphic Computing R&D.