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Germany and Europe lead digital innovation and AI with collaborative health data use at continental level

Collaborative use of population-level health data and artificial intelligence is essential for achieving precision health through a learning health system. Two groundbreaking initiatives—the European Health Data Space (EHDS), covering 449 million EU citizens, and Germany’s forthcoming Health Data Lab, providing access to data from 75 million insured individuals (90% of the country’s population)—offer unprecedented opportunities to advance digital health innovation and research with global impact.

Triple equivalence for the emergence of biological intelligence

Characterizing the intelligence of biological organisms is challenging yet crucial. This paper demonstrates the capacity of canonical neural networks to autonomously generate diverse intelligent algorithms by leveraging an equivalence between concepts from three areas of cognitive computation: neural network-based dynamical systems, statistical inference, and Turing machines.

Integrating physical units into high-performance AI-driven scientific computing

Existing numerical computing libraries lack native support for physical units, limiting their application in rigorous scientific computing. Here, the authors developed SAIUnit, which integrates physical units, and unit-aware mathematical functions and transformations into numerical computing libraries for artificial intelligence-driven scientific computing.

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