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Standard $\Lambda$CDM cosmology faces a $>2\sigma$ challenge from model-independent Lagrange reconstructions of DESI and supernova data, which indicate an earlier cosmic transition and weaker present-day acceleration than predicted.
Delays in cloud-side inference can be effectively compensated, retaining over 80% performance in imitation-learning tasks even under significant latency.
Near-field lighting? No problem: 8DNA pre-bakes complex light transport into neural representations, outperforming prior methods with faster inference and lower training costs.
