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An automatic planner developed by the SkAI institute has decided on its own where to point the Blanco telescope during two campaigns, in the spring and summer of 2026.
Based on DeepMind’s AlphaEarth Foundations model, the product transforms the static annual dataset into on-demand representations, by area and by period.
A team led from Princeton has reduced 80 million light curves to 2.5 million using machine learning, cutting the analysis time from three and a half years to just a few weeks.
The Dublin-based company, validated on more than ten missions, applies its embedded AI to maritime surveillance and dynamically pilots optical, radar and RF satellites.
A literature review takes stock of the use of machine learning for the atmospheric detection and characterization of exoplanets with the JWST and the future Ariel mission.
The NASA and IBM open model, trained on thirteen years of Landsat and Sentinel-2 images, was carried on the Australian Kanyini satellite and on a payload installed on board the ISS.
The neural network of two ESA researchers has isolated nearly 1,400 atypical objects in the Hubble archive, more than 800 of which had never been described.