Thanks to recent advances in artificial intelligence (AI), civil engineers can inspect large-scale infrastructure more efficiently and cost-effectively, while also monitoring the progression of damage severity over time. A team…
A new EPFL paper has found that students are cautious towards AI feedback, highlighting the complexity of integrating it into educational feedback systems.
Researchers have found that AI large language models, like GPT-4, are better at predicting what comes next than what came before in a sentence. This “Arrow of Time” effect could…
An AI-powered tool developed at EPFL can distinguish dark matter’s elusive effects from other cosmic phenomena, which could bring us closer to unlocking the secrets of dark matter.
Researchers at EPFL unlock a detailed understanding of brain and spinal cord interactions. The tool paves the way for future research breakthroughs and innovative therapeutic approaches.
Scientist Mackenzie W. Mathis, a professor at EPFL and winner of the Swiss Science Prize Latsis 2024, has developed pioneering artificial intelligence algorithms in behavioural neuroscience.
Vinitra Swamy and Paola Mejia-Domenzain are the first two graduating PhDs of EPFL’s Machine Learning for Education Laboratory (ML4ED). They are aiming to bring AI-powered upskilling to adult learners.
Scientists at EPFL have developed an AI tool that creates detailed models of cellular metabolism, making it easier to understand how cells function.
Medical imaging technology – such as MRI, ultrasound and X-ray – is gaining in power and precision, especially in the wake of recent breakthroughs in artificial intelligence. Several EPFL research…
Researchers from EPFL have developed a next-generation miniaturized brain-machine interface capable of direct brain-to-text communication on tiny silicon chips.
Sabine Süsstrunk, an expert in scientific photography, has seen first-hand the amazing progress in imaging technology over the past 40 years. And now her field is being upended by artificial…
EPFL scientists have developed an AI-based technique to improve chemical analysis of nanomaterials, overcoming challenges of noisy data and mixed signals.
EPFL researchers have developed a novel AI-driven model designed to predict protein sequences from backbone scaffolds, incorporating complex molecular environments. It promises significant advancements in protein engineering and applications across…