Academic papers, research breakthroughs, and scientific advances in machine learning and AI.
319 articles
Researchers used a machine learning model to screen roughly 500,000 possible perovskite materials for solar cell applications. The approach narrowed the pool down to just 38 promising candidates for further study. Source: azom.com
Researchers Youle Wang and Lei Zhang showed that physics-informed kernels can bypass long-standing query complexity limits in quantum learning tasks. The approach promises more efficient methods for learning quantum systems. Source: quantumzeitgeist.com
A new machine learning approach aims to identify disease-related genetic signatures in prenatal tissue by analyzing data from postnatal blood samples. The method could enhance accuracy in classifying uncertain genetic variants before birth. Source: progress.org.uk
A new study shows machine learning models can help forecast whether chronic lung infections in cystic fibrosis patients will resist commonly used antibiotics. This could support more targeted treatment decisions in the future. Source: cysticfibrosisnewstoday.com
Researchers developed a stereodivergent protein engineering platform powered by machine learning that evolved a single alcohol dehydrogenase enzyme into eight variants. Each variant can produce a different stereoisomer of chiral alcohols, expanding options for precise chemical synthesis. Source: nature.com
Researchers from UPV/EHU, Harvard, and TECNALIA have applied quantum computing to classify particle events recorded by neutrino telescopes. The findings were published in a quantum science journal. Source: quantumzeitgeist.com
Archaeologists have tested a new training method for deep learning models in cases where real examples of a given site type are rare. Instead of relying on large sets of known sites, the model was trained using simulated data to detect unknown features in lidar imagery. Source: archaeologymag.com
Legal tech company Harvey has unveiled Harvey Tenet, a post-trained version of the Kimi K3 base model built with Fireworks for handling long, complex legal agent tasks. The company detailed its deployment approach, training methodology, and benchmark results. Source: marktechpost.com
A machine learning model has shown strong accuracy in telling peanut allergy apart from mere peanut sensitisation. Researchers say this could improve clinical diagnosis and reduce unnecessary testing. Source: emjreviews.com
Georgia Southern University has introduced an advanced humanoid robot within its Allen E. Paulson College of Engineering and Computing. The robot is meant to support both teaching and research activities for students. Source: griceconnect.com
A new study explores machine learning survival models for predicting colorectal cancer outcomes, showing random survival forests offer advantages over standard classification approaches. Colorectal cancer remains one of the leading causes of cancer death worldwide, driving demand for better prognostic tools. Source: nature.com
A new Google paper presents a novel component that dynamically controls how complex operating environments interact with AI agents. The approach extends the Harness framework, previously used mainly for agents, to environments themselves. Source: eu.36kr.com
Researchers have decoded the sequence of the 'initiator,' a key DNA element that triggers gene activation. Using machine learning analysis, the team identified patterns in this sequence that help explain how genes get switched on. Source: today.ucsd.edu
Scientists used machine learning to decode the sequence structure of the 'initiator,' a key DNA element that triggers gene activation. The analysis offers new insight into how genes are switched on at the molecular level. Source: google.com
As language models grow larger, their data requirements increase, but many valuable data sources, such as low-resource languages, remain scarce. A new study examines scaling laws for mixing different data sources under such constraints. Source: google.com
CoreWeave signed a multi-year, multi-billion-dollar contract with quantitative trading firm Hudson River Trading to supply large-scale AI computing power. The deal centers on NVIDIA's upcoming Vera Rubin research platform. Source: pulse2.com
Researchers used AI to sift through data buried in hundreds of scientific papers to identify new lead-free dielectric materials that stay stable under heat. The approach dramatically speeds up a process that traditionally relies on slow, manual literature review. Source: phys.org
The U.S. Department of Energy has selected a Fermilab-led initiative for funding under its Genesis Mission program, aiming to use AI to improve particle accelerator performance. The project brings together Fermi National Accelerator Laboratory and partners from other national labs. Source: news.fnal.gov
A study published August 18, 2026 in Quantum Science used Fourier analysis to map out the properties of quantum machine learning ansatzes. The research aims to better understand how these quantum algorithms behave and perform. Source: quantumzeitgeist.com
Traditional drug discovery used to take years, starting with identifying a biological target and then screening thousands of compounds. New approaches are now shortening that painstaking process significantly. Source: today.ucsd.edu