The chief executive of the UK’s largest tech firm has asserted that artificial intelligence will discover a cure for cancer that humans cannot find within our lifetimes.
Rene Haas, CEO of Cambridge‑based chip designer Arm Holdings, said that while modelling how a DNA marker is affected by cancer remains “too complex” for current computers, AI systems will eventually solve the problem. Speaking on the BBC’s Big Boss Interview podcast, Haas added that AI would also drive the rapid emergence of humanoid robots over the next five years, though progress is currently hampered by a shortage of chips for data centres.
He expressed skepticism about the feasibility of manufacturing chips in the UK in the future. Arm designs the CPUs that power billions of devices worldwide, from smartphones to cars and wearables. Earlier this summer, the company’s share price surged during the AI boom, making it, in cash terms, the most valuable UK‑based company ever.
Haas, who stepped down from the board of AstraZeneca in April, said: “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 for 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,” he explained.
Prof Chris Bakal, from the Institute of Cancer Research, London, and CEO of Sentinal4D, noted that the key question is no longer whether to use AI, but what data we feed it. In his laboratory, AI models are being trained on data generated directly from patient samples rather than 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. This kind of prediction could cut years from the time it takes to develop new treatments, delivering real benefit to patients,” he added.