Many companies are trying to build increased intelligence into their products. A recent survey by XMOS found that 82% of engineers believed that AI would increase the competitive advantage of the products they design. To support this drive for increased functionality there is a major expansion in the number of companies offering Embedded AI Chips and the … Continue reading Running AI at the Edge
Lessons in practical AI ethics: Taking the UK’s AI ecosystem from ‘what’ to ‘how’
The widespread development and deployment of artificial intelligence (AI) technologies is deeply impacting individual lives, society, and the environment. Now more than ever, at a time when our reliance on digital technologies is increasing due to the COVID-19 pandemic, it is crucial to ensure that AI systems are designed, developed, and deployed in ways that … Continue reading Lessons in practical AI ethics: Taking the UK’s AI ecosystem from ‘what’ to ‘how’
AI in the UK
The following report may be of interest to some of you. AI in UK : Artificial Intelligence Industry landscape overview Q3 / 2018 Big Innovation Centre and Deep Knowledge Analytics in dialogue with the All-Party Parliamentary Group on AI have produced a first-of-its-kind, 2200-page report on the state of the Artificial Intelligence Industry in the … Continue reading AI in the UK
Event: Embedded AI Part 1 – Smart Silicon
Last chance to register to attend this event…
If you want to see more information on Embedded AI solutions – join LinkedIn Group bit.ly/EmbeddedAI
AI, Neural Networks or Machine Learning technologies are being adopted in many circumstances to make products and systems more intelligent. Data usually has to be sent to a server for processing.
In order to develop smarter product this processing has to be done on the embedded system itself. But, the problem is that traditional embedded solutions cannot handle the processing power required. The solution is not just faster silicon – but new system architectures and implementations.
At this event, we will bring together “Embedded AI” technology suppliers & technology users to enable an understanding of the opportunities. The event is designed for people involved in the management and implementation of products – from developers to CTOs.
Registration link is: https://embedded-ai-part1-smart-silicon.eventbrite.co.uk
Programme (Thursday 23 November 2017)
09:00 Registration and coffee
10:00 Welcome: Nigel Rix (Head of Enabling Technologies, KTN)
10:05 Impact of AI on traditional systems
Prof David Brown (Professor of Industrial Systems, Portsmouth)10:20 Architecture for Future Intelligent Technologies
Matt Horsnell (Principal Research Engineer, ARM Research)10:50 Embedded AI: The story so far and the upcoming applications
Ajit Jaokar (Director, AI Labs for Future Cities – Madrid)11:15 Coffee Break
11:45 PlasticARMPit – a printed electronics Neural Network
Emre Ozer (Principal Research Engineer, ARM)12:00 AI technologies for the Internet of Things
Ben Cope (Segment Marketing Manager, Intel)12:30 nVidia Platforms
Eddie Seymour (European Technical Director, nVidia)13:00 Lunch
14:00 Impact of AI on Robotics
Rich Walker (CEO, Shadow Robot)14:25 Spatial AI algorithms – The commercial opportunities and the technical challenges
Owen Nicholson (CEO, SLAMCore)14:50 Mars Rovers to embedded industrial inspection solutions using GPUs for machine intelligence
Mark Woods (CTO, SciSys)15:15 Machine learning at the edge – applications and future use cases
Tom Parsons (Director, Spotlight Data)15:40 Discussion
Phil Williams (KTN)16:00 Networking
17:00 Close
Event Title: Embedded AI: Part 1 Smart Silicon
Event Date: Thursday 23rd November 2017
Location: London
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…
View original post 57 more words