Google DeepMind CEO Demis Hassabis, one of the only people in the world with a Nobel Prize for work on artificial intelligence, shares what’s next for the world of AI.
🎓 Team BrainGraphers, Deep Learning👥 Team members: Mohamamd Mohammadi, Mohammadhosein Shakiba, Rana Rokni💡Mentor: Nima Dehghani 🔗 https://impact-scholars…
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.
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.
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.
“Completely automating labor could generate vast abundance, much higher standards of living, and new goods and services that we can’t even imagine today.”