Arm's chief executive warned that a shortage of semiconductor capacity is impeding efforts to use artificial intelligence to model complex biological problems, including how a DNA marker is affected by cancer. He said such modelling "cannot be done now" because of current limits on computing resources, but added that computers are "going to solve it".
Background and context
Arm, the UK-based designer of processors used widely in mobile devices and servers, sits at the centre of efforts to scale AI applications that require large amounts of compute. The executive’s comments underline the dependence of some medical and scientific research on access to advanced chips and processing power.
Implications for research
Researchers and companies developing AI-driven approaches to disease modelling rely on high-performance hardware to train and run complex models. Shortages or constrained supply of processors can slow progress by limiting the scale and speed at which models can be developed and tested, according to the executive’s account.
Outlook
Despite the immediate constraints, the Arm head expressed optimism about the longer-term role of computing in health sciences, saying that while certain problems cannot be addressed now, advances in hardware and software will ultimately enable machines to tackle them. The remarks highlight both the promise of AI for medical breakthroughs and the practical infrastructure challenges that need to be resolved for that promise to be realised.