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  "documentTitle": "2022 Air Street Capital The State of AI Report 2022",
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      "text": "DeepMind researchers used their framework in a collaboration with mathematics professors from the University of Sydney and the University of Oxford to (i) propose an algorithm that could solve a 40 years-long standing conjecture in representation theory and (ii) prove a new theorem in the study of knots.",
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      "text": "DeepMind researchers used their framework in a collaboration with mathematics professors from the University of Sydney and the University of Oxford to (i) propose an algorithm that could solve a 40 years-long standing conjecture in representation theory and (ii) prove a new theorem in the study of knots.",
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      "text": "DeepMind made an important contribution in materials science as well. It showed that the exact functional in Density Functional Theory, an essential tool to compute electronic energies, can be efficiently approximated using a neural network. Notably, instead of constraining the neural network to verify mathematical constraints of the DFT functional, researchers simply incorporate them into the training data to which they fit the NN.",
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