Google and UK researchers are launching a £5m trial using AI to predict where aircraft contrails form and redirect planes to avoid them, focusing on the Shanwick airspace which accounts for 5% of global contrail warming. The 30-month Operation Blue Skies project will test altitude changes of roughly 2,000 feet during winter 2026-27 and 2027-28, affecting around 10,000 flights. If successful, the approach could reduce aviation's climate impact without significantly increasing fuel consumption, with previous trials showing 60-70% reductions in contrail formation.
A new AI workspace platform has been developed to help researchers conduct reproducible scientific research. The platform integrates AI tools to streamline workflows and improve documentation standards. This enables scientists to more easily share, verify, and build upon each other's work.
A specialized semismooth Newton method is proposed to solve kernel-based optimal transport problems more efficiently than the short-step interior-point method used by existing estimators. Each SSN iteration is made significantly cheaper in practice, and the method is shown to converge globally at O(1/√k). This reduces computation time enough to deliver substantial speedups on synthetic and real datasets, making the kernel-based OT estimators more scalable to larger sample sizes.
Researchers developed MVICAD2, a machine learning method for analyzing multi-view data that addresses challenges in integrating heterogeneous data across different views or subjects. The method applies independent component analysis with time delays and dilations to better align feature spaces across views, tested on magnetoencephalography brain imaging data where sources should be consistent across subjects. This enables more accurate source estimation in neuroscience studies by accounting for temporal shifts and scaling differences between subjects' measurements.
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