Graphcore

Imagine the effect of accelerating the pace of innovation: Autonomous driving a decade earlier could equate to millions of lives saved; new AI-powered forms of cancer detection or drug discovery 5–10 years earlier could reduce mortality, pain and suffering for tens of millions; machine intelligence based models for global climate could allow us to finally settle the debate surrounding the impact of man, and get on with doing something proportionate to the challenge.

At Atomico we set out to find a solution to what was an all but obvious problem, and encouragingly found a great deal of work going on in the area. However, one company’s approach stood apart both in ambition, elegance and generality of their solution and in early performance. And perhaps, even more crucially, had a world class team of founders that could deliver.

Founded in Bristol in 2016 by serial entrepreneurs Nigel Toon and Simon Knowles, Graphcore has developed a new machine learning co-processor they call an Intelligent Processing Unit (IPU) .

Unlike traditional von Neumann architectures, where memory is a major bottleneck, this is a completely different design of processor built for graph algorithms (of which neural networks are perhaps the most significant current example). Full models are loaded into a combined memory-compute architecture, and then trained very rapidly on large datasets. This results in strikingly lower power consumption and hugely improved performance. Better still, given that most modern machine learning frameworks internally represent their models as graphs, it’s a relatively straightforward task to take advantage of this new hardware. A developer using Tensorflow, or other standard framework supported at launch, should just need to recompile their code to get the basic speedup, with advanced changes only needed for power users.

We’ve been extremely impressed by Nigel and Simon, both seasoned founders with an impressive track record — at Icera, Element14 and Picochip — developing complex chips and successfully bringing them to market. What they’re doing requires a skill set few teams in the world possess, and it was critical to our investment decision to get to know and appreciate the confidence-inspiring group of people they have brought together.