A new AI tool developed by Google has taken just two days to solve a problem that took human scientists a decade to figure out.
The breakthrough was made by researchers at Imperial College London, who were testing out Google’s latest “co-scientist” artificial intelligence model on a subject that had puzzled them for years.
After inputting a short prompt about how some superbugs gain resistance to antibiotics, the scientists received several suggestions from the AI – including one answer that they knew to be correct.
"This effectively meant that the algorithm was able to look at the available evidence, analyse the possibilities, ask questions, design experiments and propose the very same hypothesis that we arrived at through years of painstaking scientific research, but in a fraction of the time,” said Professor José Penadés, from Imperial’s Department of Infectious Disease .
“This type of AI ‘co-scientist’ platform is still at an early stage, but we can already see how it has the potential to supercharge science.”
Dr Tiago Dias da Costa, who co-led the research, said the AI tool will allow scientists to identify “experimental dead ends” that consume valuable time and resources.
“What our findings show is that AI has the potential to synthesise all the available evidence and direct us to the most important questions and experimental designs,” he said.
“If the system works as well as we hope it could, this could be game-changing; ruling out ‘dead ends’ and effectively enabling us to progress at an extraordinary pace.”
The new AI tool does not negate the need for experiments, but the researchers believe it will help accelerate scientific discoveries by coming up with the most probably hypotheses.
Early discoveries will likely involve antimicrobial resistance (AMR), which is currently one of the biggest global healthcare challenges due to the increasing rates of infections and deaths from so-called superbugs.
“The world is facing multiple complex challenges – from pandemics to environmental sustainability and food security,” said Professor Mary Ryan from Imperial College London.
“To address these urgent needs means accelerating traditional R&D processes and artificial intelligence will increasingly support scientific discovery and pioneering developments.
“Our scientists are among the most talented in the world, with the curiosity and lateral thinking needed to exploit AI technologies for societal good. Starting with new avenues for biomedical research and sowing the seeds for greater scientific efficiency – the prospects could be game-changing.”
The findings, which are yet to be peer-reviewed, are detailed in a study, titled ‘AI mirrors experimental science to uncover a novel mechanism of gene transfer crucial to bacterial evolution’, which is available in the preprint server bioRxiv.
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