Latest news with #Penadés
Yahoo
16-03-2025
- Health
- Yahoo
Scientists spent 10 years cracking superbug problem. It took Google's 'co-scientist' a lot less.
When you buy through links on our articles, Future and its syndication partners may earn a commission. Google's new artificial intelligence (AI) tool has cracked a problem that took scientists a decade to solve in just two days. José Penadés and his colleagues at Imperial College London spent 10 years figuring out how some superbugs gain resistance to antibiotics — a growing threat that claims millions of lives each year. 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with researchers — this question in a short prompt, the AI's response produced the same answer as their then-unpublished findings in just two days.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responded that it didn't. The researchers published their findings Feb. 19 on the preprint server bioRxiv, so they have not been peer reviewed yet. "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." Antimicrobial resistance (AMR) occurs when infectious microbes — such as bacteria, viruses, fungi and parasites — gain resistance to antibiotics, rendering essential drugs ineffective. Dubbed a "silent pandemic," AMR represents one of the biggest health threats facing humanity as the overuse and misuse of antibiotics in both medicine and agriculture accelerate its prevalence. According to a 2019 report by the Centers for Disease Control and Prevention (CDC), drug-resistant bacteria killed at least 1.27 million people globally that year. About 35,000 of those deaths were in the U.S. alone, meaning that U.S. fatalities from the issue had spiked by 52% since the CDC's last AMR report, in 2013. To investigate the problem, Penadés and his team began searching for ways one type of superbug — a family of bacteria-infecting viruses known as capsid-forming phage-inducible chromosomal islands (cf-PICIs) — acquire their ability to infect diverse species of bacteria. Related: Dangerous 'superbugs' are a growing threat, and antibiotics can't stop their rise. What can? The scientists hypothesized that these viruses did this by taking tails, which are used to inject the viral genome into the host bacterial cell, from different bacteria-infecting viruses. Experiments proved their hunch to be correct, revealing a breakthrough mechanism in horizontal gene transfer that the scientific community was previously unaware of. RELATED STORIES —Scientists create 'toxic AI' that is rewarded for thinking up the worst possible questions we could imagine —Want to ask ChatGPT about your kid's symptoms? Think again — it's right only 17% of the time —Just 2 hours is all it takes for AI agents to replicate your personality with 85% accuracy Before anyone on the team shared their findings publicly, the researchers posed this same question to Google's AI co-scientist tool. 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. To minimize these problems and maximize the benefits AI could bring to research, scientists are proposing tools to detect AI misconduct and establishing ethical frameworks to assess the accuracy of findings.
Arab Times
22-02-2025
- Science
- Arab Times
AI solves decade-long superbug mystery in just two days
LONDON, Feb 22: A breakthrough in microbiology, which took researchers a decade to solve, has been resolved in just two days with the help of a new artificial intelligence (AI) tool. Professor José R. Penadés and his team at Imperial College London had spent years studying why certain superbugs are immune to antibiotics. The research process was long, involving both detailed investigation and proof of the mechanism behind the resistance. However, after providing a short prompt to "co-scientist," a tool developed by Google, Professor Penadés was astounded when the AI arrived at the same conclusion within just 48 hours. Despite the fact that the research had not been published and therefore could not have been accessed by the AI system, Professor Penadés was initially stunned by the speed of the result. He shared his surprise during an interview on BBC Radio Four's Today programme, recalling how he had to step away for a while to process the unexpected findings. 'I was shopping with somebody, and I said, 'please leave me alone for an hour, I need to digest this thing,'" he said. The professor even emailed Google, asking if it had access to his computer, but the tech giant confirmed it had not. The decade-long research process, including years spent verifying the team's findings, might have been significantly shortened had the AI tool been available from the start. Professor Penadés expressed that if they had known the hypothesis at the beginning of the project, much of the work could have been avoided. What impressed the team even further was that the AI provided more than just the correct hypothesis—it also suggested several other plausible ideas. "It's not just that the top hypothesis they provide was the right one,' Penadés explained. '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 team had been investigating how certain superbugs, germs resistant to antibiotics, are formed. Their working hypothesis involved the idea that these superbugs could form a "tail" from different viruses, which enabled them to spread between different species. Professor Penadés likened the process to the superbugs having 'keys' that allowed them to move between various hosts. This hypothesis was unique to the research team and had not been published, nor shared outside the team. With this in mind, Professor Penadés used it to test the AI tool, and just two days later, the AI returned hypotheses, with its top suggestion closely matching the research team's theory. The role of AI in scientific advancement has sparked ongoing debate. While some advocate for AI's potential to accelerate scientific progress, others are concerned about its impact on jobs. Professor Penadés acknowledged the concerns about job losses but emphasized that AI should be seen as a powerful tool for research and discovery. 'It's more that you have an extremely powerful tool,' he said. '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.'
Yahoo
20-02-2025
- Science
- Yahoo
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. What is AI and how does it work? Prof Penadés' said the tool had in fact done more than successfully replicating his research. "It's not just that the top hypothesis they provide was the right one," he said. "It's that they provide 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 researchers have been trying trying to find out how some superbugs - dangerous germs that are resistant to antibiotics - get created. Their hypothesis is that the superbugs can form a tail from different viruses which allows them to spread between species. Prof Penadés likened it to the superbugs having "keys" which enabled them to move from home to home, or host species to host species. Critically, this hypothesis was unique to the research team and had not been published anywhere else. Nobody in the team had shared their findings. So Mr Penadés was happy to use this to test Google's new AI tool. Just two days later, the AI returned a few hypotheses - and its first thought, the top answer provided, suggested superbugs may take tails in exactly the way his research described. The impact of AI is hotly contested. Its advocates say it will enable scientific advances - while others worry it will eliminate jobs. Prof Penadés said he understood why fears about the impact on jobs such as his was the "first reaction" people had but added "when you think about it it's more that you have an extremely powerful tool." He said the researchers on the project were convinced that it would prove very useful in the future. "I feel this will change science, definitely," Mr Penadés said. "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."
BBC News
20-02-2025
- Science
- BBC News
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) José R Penadés and his team at Imperial College London had spent years working out and proving why some superbugs are immune to 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 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 tech giant confirmed it had full decade spent by the scientists also includes the time it took to prove the research, which itself was multiple they say, had they had the hypothesis at the start of the project, it would have saved years of work. Prof Penadés' said the tool had in fact done more than successfully replicating his research."It's not just that the top hypothesis they provide was the right one," he said."It's that they provide 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." Bugged by superbugs The researchers have been trying trying to find out how some superbugs - dangerous germs that are resistant to antibiotics - get hypothesis is that the superbugs can form a tail from different viruses which allows them to spread between Penadés likened it to the superbugs having "keys" which enabled them to move from home to home, or host species to host this hypothesis was unique to the research team and had not been published anywhere else. Nobody in the team had shared their Mr Penadés was happy to use this to test Google's new AI two days later, the AI returned a few hypotheses - and its first thought, the top answer provided, suggested superbugs may take tails in exactly the way his research described. 'This will change science' The impact of AI is hotly advocates say it will enable scientific advances - while others worry it will eliminate Penadés said he understood why fears about the impact on jobs such as his was the "first reaction" people had but added "when you think about it it's more that you have an extremely powerful tool."He said the researchers on the project were convinced that it would prove very useful in the future."I feel this will change science, definitely," Mr Penadés said."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."
Yahoo
19-02-2025
- Science
- Yahoo
AI solves superbug mystery in two days after scientists took 10 years
A scientific mystery that took 10 years to solve was cracked in two days by Google's artificial intelligence. The tech giant's latest AI development is dubbed 'co-scientist' and is designed to act as a colleague for researchers, with its own ideas, theories and analysis. Scientists at Imperial College London had spent a decade solving a mystery in the field of antimicrobial resistance (AMR), which creates superbugs that are immune to antibiotics and are expected to kill millions of people a year by 2050. Using traditional research methods, the team had theorised and then proved how different bacteria are able to accrue new DNA which can make them more dangerous, and its study is now in the process of being published by Cell, the peer-reviewed journal. After the work was finished, the scientists at Imperial partnered with Google to help test out the AI co-scientist feature. The researchers asked the co-scientist – which uses many of Google's Gemini AI models to pit various existing data and novel theories against each other – for ideas on how bacteria become immune to antibiotics. Prof José Penadés, who co-led the experimental work at Imperial, told The Telegraph: 'We worked for many years to understand this thing and we found the mechanism. 'Capsids (the protein shell of a virus) are produced with DNA inside and no tails. They have the ability to take a tail from different viruses and affect different species.' While the team knew about this tail-gathering process, nobody else in the world did. Imperial's revelations were private, there was nothing publicly available, and nothing was written online about it. The scientists then asked the co-scientist AI, using a couple of written sentences, if it had any ideas as to how the bacteria operated. Two days later, the AI made its own suggestions, which included what the Imperial scientists knew to be the right answer. '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. '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. 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.' 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. 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.' Broaden your horizons with award-winning British journalism. Try The Telegraph free for 1 month with unlimited access to our award-winning website, exclusive app, money-saving offers and more.
