Google's AI 'Co-Scientist' Solves Decade-Long Superbug Mystery in 48 Hours

AI stuns scientists : Superbug mystery solved in 48 hours after decade long research

A new artificial intelligence tool, Google's "Co-Scientist," has shocked researchers by solving a decade-long superbug mystery in just 48 hours. Professor José R. Penadés and his team at Imperial College London had been investigating how certain bacteria become resistant to antibiotics. When they tested the AI, it not only confirmed their unpublished hypothesis but also suggested four additional valid theories, one of which the team had never considered.A groundbreaking artificial intelligence (AI) tool developed by Google has left scientists astounded by solving a decade-old mystery about superbugs in just 48 hours. Researchers at Imperial College London had been investigating why certain bacteria are resistant to antibiotics, a problem that took them years to understand and prove. However, when they tested Google's AI tool 'Co-Scientist,' it reached the same conclusion in just two days, confirming their hypothesis and even presenting additional possibilities. Professor José R. Penadés and his team had theorized that superbugs develop resistance by forming a tail composed of multiple viruses, allowing them to move between species. This hypothesis was unique to their research and had not been published or shared anywhere. To their surprise, Co-Scientist not only confirmed their findings but also suggested four additional hypotheses, all of which were valid. "It's not just that the top hypothesis they provided was the right one," Penadés told the BBC. "It's that they provided another four, and all of them made sense. And for one of them, we never thought about it, and we're now working on that." The speed and accuracy of the AI tool left Penadés in disbelief. He initially suspected that Google might have accessed his unpublished research without permission. "I was shopping with somebody, and I said, 'Please leave me alone for an hour, I need to digest this thing,'" he recounted. Concerned about potential data breaches, he even contacted Google to ask if they had access to his computer, but the tech giant assured him they did not. Co-Scientist, built on Google's Gemini 2.0 AI system, is designed as a "virtual scientific collaborator" that can generate new hypotheses and research proposals. According to Google, the tool aims to accelerate biomedical and scientific discoveries by assisting researchers in formulating new ideas. Institutions interested in using the tool can apply through a trusted tester program. The breakthrough has reignited discussions about the role of AI in scientific research. While some experts fear that AI could replace human scientists, others see it as an invaluable tool for speeding up discoveries. Despite concerns about AI's impact on jobs, Penadés is convinced of its benefits. "I understand the fear, but having an extremely powerful tool like this outweighs the negatives," he said. He described the experience as being part of a historic moment in science. "I feel this will change science, definitely. I'm in front of something that is spectacular, and I'm very happy to be part of that. It's like you have the opportunity to be playing a big match - I feel like I'm finally playing a Champions League match with this thing."

AI accelerates superbug solution, completing in two days what took scientists years

Serving tech enthusiasts for over 25 years. TechSpot means tech analysis and advice you can trust. What just happened? Researchers at Imperial College London say an artificial intelligence-based science tool created by Google needed just 48 hours to solve a problem that took them roughly a decade to answer and verify on their own. The tool in question is called "co-scientist" and the problem they presented it with was straightforward enough: why are some superbugs resistant to antibiotics? Professor José R Penadés told the BBC that Google's tool reached the same hypothesis that his team had - that superbugs can create a tail that allows them to move between species. In simpler terms, one can think of it as a master key that enables the bug to move from home to home. Penadés asserts that his team's research was unique and that the results hadn't been published anywhere online for the AI to find. What's more, he even reached out to Google to ask if they had access to his computer. Google assured him they did not. Arguably even more remarkable is the fact that the AI provided four additional hypotheses. According to Penadés, all of them made sense. The team had not even considered one of the solutions, and is now investigating it further. Co-scientist is a multi-agent AI system built using Gemini 2.0. According to Google, it serves as a "virtual scientific collaborator" that can help generate novel hypotheses and research proposals, and speed up biomedical and scientific discoveries. Research organizations interested in co-scientist can apply to participate in a trusted tester program. AI has been a topic of debate for years. Among other concerns, critics warn that it could impact jobs and put scientists like Penadés out of work. The lead researcher told the BBC that he understands the fear, but believes that having an extremely powerful tool outweighs the negatives. Penadés is now sold on artificial intelligence. "This will change science, definitely, he said, adding that he believes he is witnessing something spectacular. "It's like you have the opportunity to be playing a big match - I feel like I'm finally playing a Champions League match with this thing."

AI cracks superbug problem in two days that took scientists years

A complex problem that took microbiologists a decade to get to the bottom of has been solved in just two days by a new artificial intelligence (AI) tool. Professor José R Penadés and his team at Imperial College London had spent years working out and proving why some superbugs are immune to antibiotics. He gave "co-scientist" - a tool made by Google - a short prompt asking it about the core problem he had been investigating and it reached the same conclusion in 48 hours. He told the BBC of his shock when he found what it had done, given his research was not published so could not have been found by the AI system in the public domain. "I was shopping with somebody, I said, 'please leave me alone for an hour, I need to digest this thing,'" he told the Today programme, on BBC Radio Four. "I wrote an email to Google to say, 'you have access to my computer, is that right?'", he added. The tech giant confirmed it had not. The full decade spent by the scientists also includes the time it took to prove the research, which itself was multiple years. But they say, had they had the hypothesis at the start of the project, it would have saved years of work.

AI solves superbug mystery in 48 hours - after it took scientists 10 years to crack

"This was the top one, it was the first hypothesis it suggested. It was, as you can imagine, quite shocking," said Prof Penadés. Dr Tiago Dias da Costa, a bacterial pathogenesis expert at Imperial and co-author of the study, added: "It's about 10 years of research which was condensed in two days by co-scientist." While the AI was able to spit out the correct hypothesis within 48 hours of being asked, it was unable to do the experiments to prove it, which themselves took years of work. However, the experts say if they had been given the hypothesis at the start of their project, before they drew up the theory themselves, it would have saved years of work. 'Imagine how much time and money we could save' "The system gives you an answer and that needs to be experimentally validated," added Dr da Costa. "You cannot take the answer as a universal truth, so the scientific process would still have to happen. "But 90 per cent of our experiments in the lab are failed experiments, and imagine if we have an AI collaborator that could guide us in reducing the failed experiments. "Imagine how much time, grant money and, ultimately, taxpayer money we could save." The Google AI co-scientist system is still in its infancy and will continue to be refined with further work. But it is quick, easy to use, and simple, the Imperial researchers said. The Imperial scientists were given a host of other ideas by the technology as to what may be driving AMR, some of which are now the focus of real-world research to see if they are also correct. This includes a suggested explanation for a 70-year biological mystery, which preliminary experimental data suggest holds promise. When the scientists, who have spent their entire careers trying to understand and unpick the mysteries of the microbial world, saw the results of the Google AI, they were astonished. 'It was amazing - and very scary' Prof Penadés was shopping on a weekend when the email came through from Google with the suggested hypotheses from co-scientist. "I said to the person I was with to leave me alone for one hour in order to digest this," he told The Telegraph. "Half of me was thinking that this cannot be true and it is amazing, and the other half found it very scary. I have this feeling that we are involved in something that will change the way we do science. This is my personal feeling." Dr Alan Karthikesalingam, a spokesman for Google, told The Telegraph: "AI co-scientist is intended to be a helpful collaborative tool for biomedical researchers and accelerate their scientific discoveries. "We hope that eventually health systems such as the NHS might benefit from the downstream impacts of AI tools, should they help lead to new insights into health and disease, or help accelerate the development of new treatments." AI is already widely used in science. It includes the Nobel Prize-winning AlphaFold technology, developed at Google DeepMind, which uses AI to correctly predict the shapes, structures and behaviours of proteins. Scientists can now see, just from DNA code, how a protein looks and how it will interact with the body, drugs and other entities. A tester version of co-scientist is now to be made freely available to researchers, and an application programming interface (API)I to allow websites to use the base technology is also to be published. The co-scientist was also tested with researchers at Stanford University and Houston Methodist in the US to see if it could identify new targets to treat disease, and if any pre-existing drugs could treat other diseases. The AI found a new target to try to treat liver fibrosis, and suggested that the drug Vorionostat, which is used to treat cancer of immune cells, could help treat the condition. Government investing in AI The Government is currently in the process of trying to ramp up the UK's own AI infrastructure, with a focus on turning world-leading academic research into new uses for AI and commercial applications. Last week, the Department for Science, Innovation and Technology approved a new project to use AI in science conducted in the UK. This includes world-first trials that will integrate AI into the peer-review process to try to free up researchers from some of the more time-consuming tasks which distract from doing actual research. A total of £4.8 million of taxpayers' money has been shared among 23 research projects dedicated to using AI in science, including at Bath and Sheffield, to see if AI can improve peer-review. Lord Vallance, the science minister, told The Telegraph last week: "AI presents new opportunities in a range of sectors, and if researchers can demonstrate its potential to increase transparency, robustness and trust in science, then this could pave the way to freeing them up from mundane paperwork tasks while driving growth."