The AI chip unicorn that’s about to revolutionize everything has computational Graph at its Core

The AI chip unicorn that’s about to revolutionize everything has computational Graph at its Core

AI is the most disruptive technology of our lifetimes, and AI chips are the most disruptive infrastructure for AI. By that measure, the impact of what Graphcore is about to massively unleash in the world is beyond description. Here is how pushing the boundaries of Moore’s Law with IPUs works, and how it compares to today’s state of the art on the hardware and software level. Should incumbent Nvidia worry, and users rejoice?
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If luck is another word for being at the right place at the right time, you could say we got lucky. Graphcore , the hottest name in AI chips , has been on our radar for a while now, and a discussion with Graphcore’s founders was planned well before news about it broke out this week.
Graphcore, as you may have heard by now, just secured another $200 million of funding from BMW, Microsoft, and leading financial investors to deliver the world’s most advanced AI chip at scale. Names include the likes of Atomico, Merian Chrysalis, Investment Company Limited, Sofina, and Sequoia. As Graphcore CEO and Founder Nigel Toon shared , Graphcore had to turn down investors for this round, including, originally, the iconic Sequoia fund.

Graphcore is now officially a unicorn, with a valuation of $1.7 billion. Graphcore’s partners such as Dell, the world’s largest server producer, Bosch, the world’s largest supplier of electronics for the automotive industry, and Samsung, the world’s largest consumer electronics company, have access to its chips already. So, here’s your chance to prepare for, and understand, the revolution you’re about to see unfolding in the not-so-distant future.

Learning how the brain works is one thing, modeling chips after it is another

Graphcore is based in Bristol, UK, and was founded by semiconductor industry veterans Nigel Toon, CEO, and Simon Knowles, CTO. Toon and Knowles were previously involved in companies such as Altera, Element14, and Icera that exited for combined value in the billions. Toon is positive they can, and will, disrupt the semiconductor industry more than ever before this time around, breaking what he sees as the near monopoly of

Nvidia.
Nvidia is the dominant player in AI workloads, with its GPU chips, and it keeps evolving. There are more players in the domain, but Toon believes it’s only Nvidia that has a clear, coherent strategy and an effective product in the marketplace. There are also players such as Google, with its TPU investing in AI chips, but Toon claims Graphcore has the leading edge and a fantastic opportunity to build an empire with its IPU (Intelligent Processor Unit) chip. He cites the success of ARM mobile processors versus incumbents of the time as an example.

In order to understand his confidence, and that of investors and partners, we need to understand what exactly Graphcore does and how that is different from the competition. Machine learning and AI are the most rapidly developing and disruptive technologies. Machine learning, which is at the core of what is called AI these days , is effectively very efficient pattern matching, based on a combination of appropriate algorithms (models) and data (training sets).

Some people go to the extreme of calling AI, essentially, matrix multiplication . While such reductionism is questionable, the fact remains that much of machine learning is about efficient data operations at scale. This is why GPUs are so good at machine learning workloads. Their architecture, originally developed for graphics rendering, has proven very efficient for data operations as well.

Graphcore revolutionizes hardware and software, using Graphs
What Graphcore has done, however, is to invest in a new architecture altogether.