Unlike the number-crunching alternatives, British startup Graphcore, founded in 2016, has developed a brain for computers that excels at guesswork that they are calling IPUs, or intelligence processing units. Whereas human brains use intuition to simplify problems such as identifying an approaching friend, a computer might try to analyze every pixel of that person’s face, comparing it to a database of billions of images before attempting to say hello. That precision, which made sense when computers were primarily calculators, is massively inefficient for AI, burning huge quantities of energy to process all the relevant data.
Put another way, Graphcore is developing a brain for computers that, if its co-founders are right, will be able to process information more like a human instead of faking it through massive feats of number crunching. “For decades, we’ve been telling machines what to do, step by step, but we’re not doing that anymore,” Graphcore CEO Nigel Toon said to Bloomberg, describing how Graphcore’s chips instead teach machines how to learn. “This is like going back to the 1970s—we need to break out our wide lapels—when microprocessors were first coming out. We’re reinventing Intel.”
Graphcore has raised $328 million from investors, including BMW, Microsoft, and Samsung, and was last valued in December at $1.7 billion. It declined to comment on specific applications for its chips, citing nondisclosure agreements, but given its investors, some seem obvious: self-driving cars, Siri-like voice assistants, and cloud server farms. But Graphcore CTO Simon Knowles is most excited about humanity-altering applications, such as the impact IPUs could have on the complex analysis that scientists need for research in climate change and medicine.