Oct 2026· Zenodo (CERN European Organization for Nuclear Research)
Abstract
The ground segment is often the most accessible and operationally exposed part of a satellite system,yet its automation remains largely rule-based. As satellite constellations multiply, ground infrastructure isfragmenting into many small, remote and often contested sites, yet each still depends on either a link backto centralised cloud services or a human at the console. Both are genuine single points of failure. Over thelast two years, three trends have converged: low-power AI accelerators on single-board computers, compactlanguage models distilled from larger ones, and mature compression and fine-tuning techniques. Together theymake it plausible, for the first time, to run language-model reasoning down to a credit-card-sized computerdrawing under 15 W: hardware that is low in size, weight, power and cost (low-SWaP-C). This paper sets outwhy autonomous reasoning should now move into the ground station and what still has to be proven next tosupport it.
Supporting data, adapters, predictions and code for the article *Low-Cost LoRA Fine-Tuning of Small Language Models for Multi-Step Arithmetic Reasoning* by Jake O'Grady, Asena Isik Gürhan, Chee Fong Ting and Effirul Ramlan (University of Galway). We generated 20,000 GSM8K-derived arithmetic problems with step-by-step s...
O'Grady, Jake, Gürhan, Asena Isik, Chee, Fong Ting et al.· Zenodo (CERN European Organi...· 465 citations
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