The UK is to use artificial intelligence (AI) to tackle the rising numbers of infections that have become resistant to treatment. The project - a collaboration between the Fleming Initiative and the pharmaceutical company GSK - is a battle between superbugs and supercomputers. It aims to speed up the discovery of fresh antibiotics and deliver new ways of killing other threats, including deadly fungal infections. Overusing antibiotics drives bacteria to evolve resistance to infections, which means new drugs are a priority. Drug-resistant infections are a growing problem - one known as the silent pandemic.

The most sophisticated AI models in existence today have scored poorly on a new benchmark designed to measure their progress towards artificial general intelligence (AGI) – and brute-force computing power won't be enough to improve, as evaluators are now taking into account the cost of running the model. There are many competing definitions of AGI, but it is generally taken to refer to an AI that can perform any cognitive task that humans can do. To measure this, the ARC Prize Foundation previously launched a test of reasoning abilities called ARC-AGI-1. Last December, OpenAI announced that its o3 model had scored highly on the test, leading some to ask if the company was close to achieving AGI. But now a new test, ARC-AGI-2, has raised the bar.

Imperial College London's major new initiative I-X will use artificial intelligence and data science to tackle global challenges. I-X harnesses the College's long-standing excellence in artificial intelligence (AI), machine learning, data sciences, and the many fields in science, engineering, medicine and business where they are applied. Its projects include developing new computational tools for improving image-based detection and diagnosis of disease, using AI to direct the design and implementation of new biological systems, and intelligent systems and networks for monitoring, control, and security of critical infrastructure. Other fields of research include human-AI cooperation, robotics and automation, and machine learning systems that understand the real world, such as self-driving vehicles. The initiative is housed over two floors at the Translation & Innovation Hub (I-HUB) at Imperial's White City Campus.

Summary: Combining new wearable technology and artificial intelligence, researchers are better able to track motion and monitor the progression of movement disorders. A multi-disciplinary team of researchers has developed a way to monitor the progression of movement disorders using motion capture technology and AI. In two ground-breaking studies, published in Nature Medicine, a cross-disciplinary team of AI and clinical researchers have shown that by combining human movement data gathered from wearable tech with a powerful new medical AI technology they are able to identify clear movement patterns, predict future disease progression and significantly increase the efficiency of clinical trials in two very different rare disorders, Duchenne muscular dystrophy (DMD) and Friedreich's ataxia (FA). DMD and FA are rare, degenerative, genetic diseases that affect movement and eventually lead to paralysis. There are currently no cures for either disease, but researchers hope that these results will significantly speed up the search for new treatments.

Applications are invited for a research associate position in the Department of Mathematics at Imperial College London to work in the area of statistical machine learning with applications in population health. The overall theme of the research is to develop methods in statistical machine learning to study worldwide phenotypes and transitions in multiple health outcomes. The position is funded through an UKRI Medical Research Council grant which involves collaborative research among statisticians and health researchers at Imperial College as well as with a network of scientists from most of the world's countries, which will give the work significant scientific and policy impact and visibility. The post-holder will be based in the vibrant Statistics section of the Department of Mathematics, which is consistently ranked as one of the top in the country for research and has world-class expertise in statistical machine learning, and will collaborate with the Environment and Global Health Research Group (www.globalenvhealth.org) at Imperial School of Public Health. The project will involve the development of Bayesian hierarchical models to identify multimorbidity clusters and investigate the variation in both magnitude and characteristics of these clusters across and within regions of the world.

Pianists equipped with a third robotic thumb were able to adapt to using the extra digit after just one hour of practice, Imperial research has found. Researchers from Imperial College London have been working to understand how well the human brain can cope with using extra limbs made possible through robotic technology. To assess the effects of such devices on the brain, the research team, led by Professor Aldo Faisal of Imperial's Department of Bioengineering, attached robotic extra thumbs to a group of piano players next to their little finger that could be controlled by the pianists using their feet. The inspiration for the study came from humanity's long-standing fascination with characters who have extra limbs, such as those found in Indian mythology and modern superhero comic books. Professor Faisal said: "We wanted to see whether we can enhance people using extra limbs; specifically, an extra thumb that sits opposite--contralaterally, technically speaking--the thumb of your right hand. "The basic question was: can we use 11 fingers in a task that requires actual skills?

FICO, the leading provider of analytics and decision management technology, together with Google and academics at UC Berkeley, Oxford, Imperial, UC Irvine and MIT, have announced the winners of the first xML Challenge at the 2018 NeurIPS workshop on Challenges and Opportunities for AI in Financial Services. Participants were challenged to create machine learning models with both high accuracy and explainability using a real-world dataset provided by FICO. Sanjeeb Dash, Oktay Gu nlu k and Dennis Wei, representing IBM Research, were this year's challenge winners. The winning team received the highest score in an empirical evaluation method that considered how useful explanations are for a data scientist with the domain knowledge in the absence of model prediction, as well as how long it takes for such a data scientist to go through the explanations. For their achievements, the IBM team earned a $5,000 prize.

Maths PhD student, Alex Terenin, recently presented his group's work at the 2021 International Conference of Artificial Intelligence and Statistics. AISTATS is a prestigious event that brings together researchers from the machine learning and statistics communities. One of the group's papers, Matérn Gaussian Processes on Graphs, won the Best Student Paper award at the event – congratulations! We caught up with Alex to find out more about his experience at the conference and as a PhD student at Imperial, why he's fascinated with research into uncertainty, and to get his thoughts on why the visual aspect of machine learning is vital. My research focuses on artificial intelligence, particularly on learning-based decision-making systems.

We have a research associate (postdoc) position to work on spatial audio processing and spatial hearing using methods from machine learning. The aim of the project is to design a method for interactively fitting individualised filters for spatial audio (HRTFs) to users in real-time based on their interactions with a VR/AR environment. We will use meta-learning algorithms to minimise the time required to individualise the filters, using simulated and real interactions with large databases of synthetic and measured filters. The project has potential to become a very widely used tool in academia and industry, as existing methods for recording individualised filters are often expensive, slow, and not widely available for consumers. The role is initially available for up to 18 months, ideally starting on or soon after 1st January 2022 (although there is flexibility).

Insights into how bacterial proteins work as a network to take control of our cells could help predict infection outcomes and develop new treatments. Much like a hacker seizes control of a company's software to cause chaos, disease-causing bacteria, such as E. coli and Salmonella, use miniature molecular syringes to inject their own chaos-inducing agents (called effectors) into the cells that keep our guts healthy. These effectors take control of our cells, overwhelming their defences and blocking key immune responses, allowing the infection to take hold. Previously, studies have investigated single effectors. Now a team led by scientists at Imperial College London and The Institute of Cancer Research, London, and including researchers from the UK, Spain and Israel, has studied whole sets of effectors in different combinations.