Advertisement Cambridge China Centre
Barr Ellison Solicitors – commercial property
Advertisement: RSM
Advertisement: Wild Knight Vodka
Advertisement EY mid banner
ARM Innovation Hub
Advertisement: Bradfield Centre mid
Advertisement: Mogrify
Advertisement: Cambridge Network
RealVNC mid banner careers
RealVNC mid-banner general
Advertisement: TTP
Mid banner advertisement: BDO
1 August, 2017 - 01:53 By Tony Quested

Cambridge investors back $30m machine intelligence raise

business awards, business weekly, cambridge

Cambridge investors have piled into a $30 million funding round for UK machine intelligence company Graphcore. Hermann Hauser’s Amadeus Capital in Cambridge has injected follow-on cash. 

AI pioneers Zoubin Ghahramani of the University of Cambridge and chief scientist at Uber, and Cambridge alumnus Demis Hassabis (Google DeepMind) are new angel investors in the business.

The Series B has been led by Atomico, the international technology investment firm. 

The investment comes as Graphcore prepares to ship its first Intelligence Processing Unit hardware customers later this year. Scale-up production for enterprise data centres and cloud environments is slated for 2018.

Bristol-based Graphcore is building a community of developers around its Poplar™ graph framework software, which provides a seamless interface to multiple machine networks.

Graphcore IPU products are destined to cut the cost of accelerating AI applications and increase the performance of both training and inference by between 10X and 100X compared to the fastest systems around at the moment. 
The company says delivery of this vision will enable recent successes in deep learning to evolve rapidly towards useful, general artificial intelligence.

Demis Hassabis commented: “Building systems capable of general artificial intelligence means developing algorithms that can learn from raw data and generalise this learning across a wide range of tasks.

“This requires a lot of processing power and the innovative architecture under-pinning Graphcore’s processors holds a huge amount of promise.”
Zoubin Ghahramani added: “Deep neural networks have allowed us to make massive progress over the last few years but there are also many other machine learning approaches that could help us achieve radical leaps forward in machine intelligence.

“Current hardware is holding us back from exploring these different approaches. A new type of hardware that can support and combine alternative techniques, together with deep neural networks, will have a massive impact.”

• PHOTOGRAPH SHOWS: Dr Hermann Hauser

Newsletter Subscription

Stay informed of the latest news and features