The development of artificial intelligence capable of discovering cancer cures beyond human lifetimes is being hampered by a global shortage of specialized chips, according to Rene Haas, chief executive of Arm Holdings, the UK's largest tech firm.
Haas stated that while modeling DNA markers and their impact by cancer is currently too complex for both humans and existing AI, he believes computers will eventually solve these challenges. "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," Haas told the BBC.
He also predicted the widespread adoption of humanoid robots within the next five years. However, the rapid advancement of AI is currently constrained by the limited availability of chips required for building data centers. Haas expressed skepticism about the feasibility of manufacturing these advanced chips in the UK in the future.
Arm Holdings, headquartered in Cambridge, designs the central processing units (CPUs) for microchips used in a vast array of devices, including hundreds of billions of phones, cars, smartwatches, and other gadgets worldwide. The company's peak share price earlier this summer, driven by the AI boom, made it the most valuable UK-based company in history in terms of cash.
Haas, who previously served on the board of pharmaceutical giant AstraZeneca, elaborated on the complexity of biological modeling. "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," he said. "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."
Professor Chris Bakal, from the Institute of Cancer Research, London, and CEO of Sentinal4D, suggested that the focus for medical AI should shift from computing power to data quality. "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," Bakal explained. He noted that AI trained on specific patient data generated in labs could accelerate the development of new treatments, potentially saving years of research time and delivering tangible benefits to patients.