AI, Neural Networks or Machine Learning technologies are being adopted in many circumstances, but usually all the data has to be sent to a server for processing before being acted upon.
There would be many advantages of being able to do this analysis on the embedded system itself - faster decision making and the ability to implement AI in situations where the data link is not possible. But the problem is that traditional embedded compute platforms cannot handle the processing power required. The solution is not just faster silicon - but new architectures and ways to implement systems.
The Knowledge Transfer Network (www.ktn-uk.org) is organising a workshop “Embedded AI Part 1- Smart Silicon” on the 23rd November in London that will bring together technology suppliers and technology users to discuss the opportunities and barriers to the deployment of next generation systems.
At the event experts (industry and academic) will give presentations covering this topic to promote discussion and share learning.
Registration site: https://embedded-ai-part1-smart-silicon.eventbrite.co.uk
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