Google's AI 'Co-Scientist' Solved a 10-Year Superbug Problem in Two Days

Google collaborated with Imperial College London and its 'Fleming Initiative' partnership with Imperial NHS, giving their scientists 'access to a powerful new AI designed' built with Gemini 2.0 'to make research faster and more efficient,' according to an announcement from the school. And the results were surprising...

'José Penadés and his colleagues at Imperial College London spent 10 years figuring out how some superbugs gain resistance to antibiotics,' writes LiveScience. 'But when the team gave Google's 'co-scientist'' — an AI tool designed to collaborate with researchers — this question in a short prompt, the AI's response produced the same answer as their then-unpublished findings in just two days.'

Astonished, Penadés emailed Google to check if they had access to his research. The company responded that it didn't. The researchers published their findings [about working with Google's AI] Feb. 19 on the preprint server bioRxiv...

'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,' co-author Tiago Dias da Costa, a lecturer in bacterial pathogenesis at Imperial College London, said in a statement. '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....'

After two days, the AI returned suggestions, one being what they knew to be the correct answer. '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,' Penadés, a professor of microbiology at Imperial College London, said in the statement. The researchers noted that using the AI from the start wouldn't have removed the need to conduct experiments but that it would have helped them come up with the hypothesis much sooner, thus saving them years of work.
Despite these promising findings and others, the use of AI in science remains controversial. A growing body of AI-assisted research, for example, has been shown to be irreproducible or even outright fraudulent.


Google has also published the first test results of its AI 'co-scientist' system, according to Imperial's announcement, which adds that academics from a handful of top-universities 'asked a question to help them make progress in their field of biomedical research... Google's AI co-scientist system does not aim to completely automate the scientific process with AI. Instead, it is purpose-built for collaboration to help experts who can converse with the tool in simple natural language, and provide feedback in a variety of ways, including directly supplying their own hypotheses to be tested experimentally by the scientists.'
Google describes their system as 'intended to uncover new, original knowledge and to formulate demonstrably novel research hypotheses and proposals, building upon prior evidence and tailored to specific research objectives...
'We look forward to responsible exploration of the potential of the AI co-scientist as an assistive tool for scientists,' Google adds, saying the project 'illustrates how collaborative and human-centred AI systems might be able to augment human ingenuity and accelerate scientific discovery.

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