Mathematicians put AI to work on Fermat's last theorem At an event in London, mathematicians have made unexpectedly fast progress on formalising Fermat's last theorem using AI In the lobby of a central London hotel, tourists are bracing themselves for a day of sightseeing in a heatwave. Meanwhile, staff are resetting the dining room after breakfast. And in a windowless meeting room, assembled academics are contemplating whether humans have a role to play in the future of mathematics, now that AI can prove theorems by itself. The general mood in the room is one of bewilderment at the recent jump in computer intelligence and excitement about the potential it unlocks - and perhaps a slight unease about what the future holds for them personally. Twenty-five researchers from diverse fields and countries are here to spend a week working on formalising Fermat's last theorem with cutting-edge AI models.

Combining math concepts with sports can help boost your fractions game. More information Adding us as a Preferred Source in Google by using this link indicates that you would like to see more of our content in Google News results. Students also saw improvement in other math areas after participating in the workshop. Breakthroughs, discoveries, and DIY tips sent six days a week. By signing up, you confirm you are 16+, will receive newsletters and promotional content and agree to our Terms of Use and acknowledge the data practices in our Privacy Policy .

Meet the UK's very own LeBron James... but not as you know it Look out LeBron James and Michael Jordan, there's a new basketball champ around. But it was made in Lisburn rather than Los Angeles or Chicago. The name 25416 may not appear on many replica vests, but it can shoot hoops like no-one else. And the basketball-playing robot won a school in Lisburn first prize at the UK-wide First Tech Challenge robotics competition. The team of sixth-formers from Friends' School came top of 48 schools from across the UK at the competition held in London's Copper Box Arena. Going down and working on it with my friends is honestly one of the highlights of my last year in school, he said.

The 10th International Workshop on Health Intelligence (W3PHIAI-26) celebrated a decade of bringing AI and health research together, building on a lineage that began with the AAAI-W3PHI workshops focused on population health (2014-2016), the AAAI-HIAI workshops focused on personalized health (2013-2016), and the subsequent joint W3PHIAI workshops held annually from 2017 through 2025. Over this decade, the series has produced hundreds of talks and high-impact publications that have collectively received thousands of citations, shaping the research agenda in both population health intelligence and personalized healthcare AI. This year's special theme, "Foundation Models and AI Agents," reflected the field's rapidly evolving frontier: the emergence of autonomous and semi-autonomous AI systems reshaping clinical workflows, patient management, health system operations, and public health surveillance. Day 1 of the workshop focused on medical imaging and the translation of AI for clinical ...

I knew my writing students were using AI. It's what's lost when we surrender the struggle to translate thought into words I have been teaching fiction writing at MIT since 2017. Mark what works and what doesn't - underline great sentences, flag clunky syntax, gaps in logic and unrealistic dialogue. Ask yourself: does the story work? Answer in a signed letter to the author, attached to their story.

How did you arrive at this research area?

However,thisisrarelythecase in real LR images, in contrast to synthetically generated SR datasets. When the assumed downscaling kernel deviates from the true one, the performance of SR methods significantly deteriorates. This gaverise toBlind-SR-namely, SR when the downscaling kernel ("SR-kernel") is unknown.

We consider the problem of automatic posterior inference. A scientist or expert creates a model p(z,x) for latent variablesz and observed variablesx.