Researchers introduce a multimodal, multiresolution foundation model trained from scratch for lunar remote sensing. It was pretrained on SomBench, a geographically partitioned dataset of roughly two million co-registered tile bundles covering 11 sensor modalities at two spatial resolutions of 1 m/pixel. The work targets general-purpose representation learning for planetary surface analysis.
Astronaut Christina Koch had a conversation with James Manyika, Google's Senior Vice President of Research, Labs, Technology & Society. The discussion covered space, technology, and discovery.
WHY IT MATTERS ↘Google's research leadership publicly aligning with crewed spaceflight signals that space is being treated as a demanding testbed for autonomy, robotics, and decision-making under communication latency — capabilities with direct commercial spillover into terrestrial AI systems. It also positions Google to shape norms for AI in safety-critical, government-adjacent domains where NASA procurement and export rules, not consumer markets, will set the terms.
A German report describes the Fermi Explorer mission, which aims to launch a spacecraft toward Alpha Centauri by the end of 2029. An AI system was used to work out the trajectory for the proposed interstellar journey. Details on the method and mission design are limited in the source.
A new arXiv paper introduces a multi-task surrogate model that combines physical constraints with machine learning to simulate the Martian nightside thermosphere. The problem is difficult because direct measurements are sparse and transport, magnetic, and seasonal effects interact strongly, so purely data-driven approaches can produce unphysical outputs such as reversed density trends. Embedding physics into the training process aims to keep the model's predictions consistent with known atmospheric behavior.
A new arXiv preprint describes a deep-learning pipeline that boosts detection of dim moving objects in optical space situational awareness imagery. The method combines automated star removal with background reconstruction to help recover objects at low signal-to-noise ratios. The authors frame the work as a step toward more reliable tracking of faint orbital targets.
Besxar, a startup founded by former OpenAI staff member Ashley Pilipiszyn, aims to manufacture materials used in advanced chipmaking in orbit. The company intends to leverage the vacuum of space and launch its hardware aboard SpaceX rockets.