AI cancer cures slowed by chip shortage, says UK's biggest tech boss

The boss of the biggest UK-headquartered tech firm has said that artifical intelligence will find a cure for cancer that humans cannot in our lifetimes.

Rene Haas, chief executive of Cambridge-based chip designer Arm Holdings, said while modelling how a DNA marker is impacted by cancer was currently "too complex" a problem, computers are "going to solve it" in the future.

Haas also told the BBC that AI would lead to widespread humanoid robots in the next five years, but that its current rapid growth was being held up by a shortage of chips needed to build data centres.

However, he was sceptical about the idea chips could be manufactured in the UK in the future.

Arm designs the brains or CPUs of microchips already used in hundreds of billions of phones, cars, smartwatches and gadgets across the globe.

Earlier this summer, the company's peak share price amid the AI boom made it, in cash terms, the most valuable UK-based company in history.

Haas, who stepped down from the board of British pharmaceutical giant AstraZeneca in April, told the BBC's Big Boss Interview podcast: "AI is going to... find a cure for cancer that today you and I, other humans [could] not in our lifetimes. I believe in our lifetime, AI will help cure cancer.

"Modelling a cell, modelling a human, modelling how a DNA marker is impacted by cancer - it's too complex a problem, not only for humans today, but the computers that run AI.

"However, going forward, as we feed more and more of the models into these computers, and the computers get more sophisticated to run the models, they're going to solve it," said Haas, who also holds a key role in Arm's main owner, the Japan-based Softbank, which has a range of investments in tech including in OpenAI.

Prof Chris Bakal, from the Institute of Cancer Research, London, and CEO of Sentinal4D, said the real question was no longer whether we use AI, it's what we feed it.

He said in labs like his, they are training AI on data generated themselves from patient samples.

"It is not scraped from the internet. It does not need a giant data centre to run. The future of medical AI will not belong to whoever builds the biggest computer. It will belong to whoever has the right measurements.

"That kind of prediction could cut years from the time it takes to develop new treatments. This is where AI delivers real benefit to patients."