SoftBank Group has acquired British semiconductor startup Graphcore, as the Japanese firm seeks to strengthen its investments in chips and artificial intelligence (AI). The companies announced the deal on Friday without disclosing financial terms. Bristol-based Graphcore will operate as a SoftBank subsidiary and keep its management team, Nigel Toon, Graphcore's chief executive officer, told reporters in a briefing. It's the second U.K. semiconductor company that SoftBank's snapped up, and follows its 2016 takeover of Cambridge-based Arm Holdings, the chip designer whose technology is found in almost all of the world's smartphones. Graphcore was frequently held up as a champion of the U.K. tech industry -- it participated in the country's inaugural AI safety summit last year.

"We're probably still at the stage of Pac Man, we haven't yet gotten to three-dimensional games," as far as AI's evolution, says Graphcore CEO Nigel Toon. "The misconception here is that this is as much, if not more, a software problem to solve than it is a hardware problem," said Nigel Toon, chief executive officer of AI computer startup Graphcore. Graphcore is known for making a computer system that has hundreds of thousands of processor cores inside every "intelligence processing unit," or IPU, chip, to crunch artificial intelligence problems. Its latest machines have an IPU chip, "Bow," that consists of two semiconductor die stacked one on top of the other. And yet, Toon, who was in town last week from Graphcore's headquarters in Bristol, England, told ZDNet that software is at the heart of the very large challenge of increasingly large AI problems, whereas the hardware, though by no means trivial, is, in a sense, secondary.

Graphcore, the UK maker of chips designed for use in artificial intelligence, has raised $222m (£164m) from investors, valuing the company at $2.8bn. The Bristol-based company's latest round of funding was led by the Ontario Teachers' Pension Plan as well as investors including Fidelity International and Schroders. Existing Graphcore investors, including Baillie Gifford and Draper Esprit, also joined the round. The $2.8bn valuation propels Graphcore further up the ranks of the UK's most valuable private tech companies as it seeks to confirm its position in the fast-growing artificial intelligence industry. The company has $440m in cash as it seeks to expand, with voice recognition and driverless cars among the potential target markets for its technology.

THE FUNDAMENTAL assumption of the computing industry is that number-crunching gets cheaper all the time. Moore's law, the industry's master metronome, predicts that the number of components that can be squeezed onto a microchip of a given size--and thus, loosely, the amount of computational power available at a given cost--doubles every two years. For many comparatively simple AI applications, that means that the cost of training a computer is falling, says Christopher Manning, an associate director of the Institute for Human-Centered AI at the University of Stanford. But that is not true everywhere. A combination of ballooning complexity and competition means costs at the cutting edge are rising sharply.

As tensions and tech rivalry between the U.S. and China intensify, artificial intelligence is taking center stage. During the recent Tortoise Global AI Summit, panelists discussed the increasingly fraught relationship between these global superpowers, whose rivalry had shown signs of bitterness even before President Trump launched a trade war. While this competition extends across a wide range of technologies, the panelists agreed AI has increasingly become a focal point, thanks to the essential role many predict it will play in the coming decades. And not only is the race for AI supremacy pitting China against the U.S., it is forcing every other country to reassess their place in this technological duel. "We're seeing a technology competition in the context of a worsening relationship between the world's two great powers," said John Sawers, former head of the U.K.'s MI6 spy agency.

Graphcore Ltd., the British semiconductor firm whose chips are used to run artificial intelligence programs, has raised $150 million, bringing its valuation to $1.95 billion. The company now has $300 million in cash, which it will use to invest in research and development and global expansion, Bristol, England-based Graphcore said in a statement on Tuesday. After it raised $200 million in 2018, Graphcore was approached by additional investors who wanted to put money into the company, Chief Executive Officer Nigel Toon said in an interview. While the company has no immediate plans for an initial public offering, several of its investors, such as Baillie Gifford, have experience investing in publicly traded technology companies and are the types of shareholders the company would try to target if it were to go public at some point in the future, Toon said. "Having this additional capital on hand allows us to accelerate our investment and allows us to be in a position to support the really large customers who we're building business with," Toon said.

A Bristol start-up building the next generation of microchips for artificial intelligence technology has raised $150m (£116m) from investors including Edinburgh's Baillie Gifford. Graphcore, founded in 2016 by Icera co-founder Nigel Toon, is now valued at almost $2bn having raised $450m from investors. Its new investors include Baillie Gifford, which has more than £200bn of assets under management, Mayfair Equity Partners and M&G Investments. Previous backers include Microsoft, BMW and Silicon Valley venture capital fund Sequoia. Graphcore has developed an intelligence processing unit, a microchip designed for artificial intelligence software.

Artificial Intelligence (AI) is already pervasive in many applications. Deep learning has happened since 2012 and it's only growing. This is Nigel Toon's perspective, which he shared at Berlin's TechCrunch Disrupt conference on Wednesday. Toon is Graphcore's CEO, a company that specializes in AI chips. For Toon, AI can allow many different kinds of innovation. Deep learning, probabilistic machine learning, to exploit to make new breakthroughs.

"What we heard universally was that current hardware was holding developers back," says Nigel Toon, co-founder of Graphcore, the Bristol-based startup behind a new chip to help speed up the process-hogging, resource-intensive deployment of AI. By using cloud computing and vast datasets, some neural networks function sufficiently well. The more powerful AI systems in development, however, struggle to process complex rapid-fire calculations at speed if using computer processing units (CPUs) which work sequentially. Latency, in other words, has slowed. "For 70 years we have programmed computers to work on instructions step-by-step," says Toon, 54.

For most organisations, the process of cognification is the single biggest challenge of the next five years. Everything will get smarter – in theory. The limitations of existing computer chips, however, is slowing down the process. Put simply, today's technology simply isn't up to the job. "What we heard universally was that current hardware was holding developers back," says Nigel Toon, co-founder of Graphcore, the Bristol-based startup behind a new chip to help speed up the process-hogging, resource-intensive deployment of AI.