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Jointly training on simulation and experimental data unlocks balanced prediction in physical systems, outperforming sequential transfer and preserving crucial simulation-only knowledge.
Trusting autonomous AI systems without human-like accountability can lead to catastrophic failures, necessitating a shift towards engineered heterogeneity for reliable governance.
