AI cancer treatments slowed by chip shortage, says UK’s biggest tech boss

The head of a major technology company headquartered in the UK has said that artificial intelligence will find a cure for cancer that humans will not be able to find in our lifetime.

Rene Haas, chief executive of Cambridge chip designer Arm Holdings, said that while modeling how a DNA marker affects cancer is currently a “too difficult” problem, computers are “going to solve it” in the future.

Haas also told the BBC that artificial intelligence will lead to the widespread adoption of humanoid robots in the next five years, but its current rapid growth is being held back by a shortage of chips needed to build data centers.

However, he was skeptical about the idea that chips could be made in the UK in the future.

Arm designs the brains, or microchip processors, that are already used in hundreds of billions of phones, cars, smartwatches and gadgets around the world.

Earlier this summer, the company’s peak share price amid the artificial intelligence boom made it the most valuable British company in history in monetary terms.

Haas, who resigned from the board of British pharmaceutical giant AstraZeneca in April, told the BBC’s Big Boss Interview podcast: “AI is going to… find the cure for cancer that you and I have in other people today.” [could] not in our lifetime. I believe that in our lifetime, AI will help cure cancer.

“Modeling a cell, simulating a person, simulating how cancer affects a DNA marker is too complex a problem, not only for today’s people, but also for computers running AI.

“Going forward, however, as we load more and more models into these computers, and the computers become more complex to run models, they will solve this problem,” said Haas, who also plays a key role in Arm’s majority owner, Japan’s Softbank, which has a number of technology investments, including OpenAI.

Professor Chris Bakal from the Institute of Cancer Research London and CEO of Sentinal4D said the real question is no longer whether we use AI, but what we feed it.

He said that in labs like his, they train AI on self-reported data from patient samples.

“It is not taken from the Internet. It doesn’t require a giant data center to operate. The future of medical AI will not belong to whoever builds the biggest computer. It will belong to the one who takes the correct measurements.

“Such a prediction could shorten the years needed to develop new treatments. This is where AI brings real benefits to patients.”