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AI Chip Startup Aims to Take on Industry Giants

In the middle of the historic city of Bristol in England, about 150 engineers are currently designing the most sophisticated computer AI chip in the world.

The “Colossus” has 1216 processors fitted on a chip characterized by the size of a postage stamp.

Designed specifically for artificial intelligence (AI) applications, the AI chip draws its name from the computer that was used by cryptographers at Bletchley Park during World War II.

“[Colossus] was all top-secret for decades after the war, so the Americans thought they invented everything first. Now it is clear to the world that they didn’t,” claimed Simon Knowles, the inventor of the novel AI chip.

Aged 57, Knowles is the co-founder of Graphcore, a two-year-old UK-based AI chip startup that is currently striving to create the next breed of silicon AI chips in a bid to power artificial intelligence (AI) programs, specifically from voice recognition to autonomous driving vehicles.

His company hopes that each high-tech industry, in the coming decade, from automotive to manufacturing, security, and health, will have to embed machine learning into all their systems, enabling computers to not only identify patterns but also make some discoveries from massive data sets.

SEE MORE: Startup Graphcore Raises £30m to Take on AI Chips Giants in a Different Direction

Once they do, they will require new hardware for running such power-hungry applications, primarily within their existing computing infrastructure.

“This is a multibillion-dollar opportunity, I don’t see it any other way. We have a lot of conviction that the [machine learning] workload has a bunch of very specific requirements that are unique from what current AI chips are designed to do,” claimed Eric Vishria, an investor at California-based Benchmark Capital, which has invested in Cerebras, one of Graphcore’s rival companies.

Graphcore's AI chip Alexnet deep neural network
Graphcore’s Alexnet deep neural network

“So just like we saw with Intel, Nvidia, Arm and Qualcomm, there should be a new large independent company created here. It’s like talking about the smartphone just before the iPhone in 2007, we don’t know how big it can be.”

In the startup space, Graphcore’s co-founders CEO Nigel Toon and Knowles are outliers.

They are both above 50 years, have established and sold two semiconductor entities for a combined amount of over $1 billion and are currently making long-term plans.

They sold their last company dubbed Icera to Nvidia for 367 million dollars in 2011, before taking a few months to consider their subsequent move.

SEE MORE: New Frontier for AI Chip Startups

The concept behind the new company, one that would focus on AI chips, was fostered by another British chipmaker known as Hermann Hauser, who is the co-founder of Arm, a mobile chip company as well as an early Graphcore investor.

“This is only the third time in the history of computing that there is a need for new microprocessors,” he said. “The first was when we founded Arm, where low-power chips became powerful in mobile phones, the second time was GPUs, which were needed for high-intensity video processing and the third time is now. It’s very unusual.”

When the two Graphcore co-founders proposed their idea to California-based venture capitalists back in 2016, many doubted whether the plan could work.

“The VC world was focused on software and consumer internet and closed to hardware,” claimed Matt Miller, a partner at Sequoia as well as a member of Graphcore’s board.

“To be honest, the VC community is generally pretty skeptical about semiconductors, because you have to invest tens of millions before you know if you have something that works. You have no idea until you put it into silicon and get it back from manufacturing, which is a pretty scary prospect.”

SEE MORE: Secretive Chip Startup Groq Will Reveal Artificial Intelligence Chip Next Year

However, when Google revealed in 2016 that it was creating its own AI chips designed for internal applications, investors suddenly began to develop an interest in the field.

“In one sweep, they said everything that we had spent the last several years trying to tell people. This is big enough to justify investing in AI chips, which are very expensive, and the chips that exist are not the right chips,” said Mr Knowles. The day when Google made its announcement, he drafted an email and sent it to Jeff Dean, who is the head of Google’s AI division, saying: “Thanks, mate.”

Since this period, nearly 50 startups have claimed that they are developing AI chips, including well-financed entities such as California-based Cerebras and China-based Horizon Robotics.

Aside from Google, these companies are also competing with other entities like Apple and Amazon, which are both involved in creating AI chips.

Dell-Graphcore AI chip IPU platform
Dell-Graphcore IPU platform

According to research company CB Insights, venture capitalists invested over $1.5 billion in chip startups back in 2017, an amount that is estimated to be double the investments made in 2015.

UBS has forecasted that global artificial intelligence AI chip revenue will increase to $35 billion in 2021, approximately six times the value in 2016.

Graphcore is convinced that its advantage over other companies is that the data required for training algorithms can be found on its chips instead of externally.

This feature combined with the chip’s communication network and its wide variety of chips ascertain the fact that Graphcore systems are about 10-100 times much faster compared to the existing chips designed for applications like video analysis, voice processing, and image recognition.

“This new microprocessor allows us to build a company that rivals an Intel or some of the other big semiconductor companies because we are right at the start of this new wave of computing,” said Mr Toon.

Back in December, Graphcore fundraised $200 million in a new financing exercise, specifically from investors such as BMW and Microsoft as well as other existing investors like Amadeus Capital and Sequoia Capital, which caused the company’s valuation to hit $1.5 billion.

Toon is convinced that Graphcore will make over $50 million of revenue in 2019, and then, at its current growth rate, it will reach a $1 billion run rate in five years.

Graphcore has a total of 200 engineers and is now expanding its operations into other parts of the world like the United States, Taiwan, and Norway.

An investor who funds a different chip company claimed they are convinced beyond doubt that Graphcore’s chips were developed to fit into the existing computing systems as opposed to making a step alteration in chip design. “It remains to be seen if it is an appetizer or an entrée,” the person said.

According to some sources, Samsung, Dell, and Microsoft are all Graphcore investors and the company’s AI chip is being tested by DeepMind (Google’s AI division) and Uber’s autonomous driving car unit.

Both Demis Hassabis (DeepMind’s CEO) and Zoubin Ghahramani (Uber’s chief scientist) are personal investors in Graphcore.

Google, DeepMind’s parent company, has created its own artificial intelligence-based chips, which help power various services like Street View and search.

“DeepMind is particularly keen to try out new algorithms, and our processor is totally general purpose so new algorithms which maybe haven’t been honed down yet can run on our architecture just as well as any of the older algorithms. Others’ chips may not be as friendly to new algorithms,” claimed Mr Hauser.

“Google has told us they are very happy to have their internal [chip] programme but also work with us, they don’t feel they need an exclusive programme.”

DeepMind denied the claims that it was involved in the testing of Graphcore’s chips.

Microsoft boasts AI across its products like Azure cloud services, LinkedIn, Skype for real-time language translation, and Office 365 for email.

Sources familiar with the partnership said that Graphcore chips would undergo testing internally across several of these products.

For the co-founders of Graphcore, the aim is to become a general-purpose provider of AI chip to companies like Nvidia or Intel, as well as take the startup public in the coming five years.

“It’s very exciting that unexpectedly a European company seems to have the lead in what must be one of the hottest semiconductor events this decade. It’s a big prize, and we do have the chance of creating a company worth tens of billions of dollars.”

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KC Cheung
KC Cheung
KC Cheung has over 18 years experience in the technology industry including media, payments, and software and has a keen interest in artificial intelligence, machine learning, deep learning, neural networks and its applications in business. Over the years he has worked with some of the leading technology companies, building and growing dynamic teams in a fast moving international environment.
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