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NASA announced that the Nancy Grace Roman Space Telescope will launch in September 2026, eight months ahead of schedule, promising to deliver roughly 20,000 terabytes of data over its mission. Combined with the daily 57 GB from the James Webb Space Telescope and the Vera C. Rubin Observatory’s nightly 20 TB, astronomers are turning to GPU‑accelerated AI to keep up.NASA’s Roman Telescope Launch Accelerates Data DelugeThe Roman telescope, slated for a September 2026 orbit insertion, is designed to conduct wide‑field infrared surveys that will generate an unprecedented volume of raw observations. Its data pipeline is expected to feed 20,000 terabytes to researchers over the mission’s lifespan, dwarfing the output of legacy assets.Data Volumes Surge: From Hubble to Rubin’s Nightly 20 TBHubble: 1–2 GB per dayJames Webb: 57 GB per dayRoman Telescope: 20,000 TB totalRubin Observatory: 20 TB per nightThis exponential growth forces a shift from manual analysis to high‑throughput computing.GPU Shortage Threatens Astronomical Research PaceBrant Robertson, a UC Santa Cruz astrophysicist, describes a “global GPU crunch” as more teams adopt deep‑learning pipelines. His NSF‑funded GPU cluster is already aging, and a proposed 50% cut to the National Science Foundation budget by the Trump administration threatens further capacity.Transformers and Generative AI: The Next Frontier for Space DataRobertson and graduate student Ryan Hausen are evolving their Morpheus model from convolutional networks to transformer architectures, aiming to scan several times more sky area per run. Parallel efforts on generative AI seek to de‑blur ground‑based images, compensating for atmospheric distortion and extending the scientific return of the Rubin Observatory.