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PPPL: Distinguished Oxford physicist named head of world-class PPPL Theory Department

PPPL: Distinguished Oxford physicist named head of world-class PPPL Theory Department
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PPPL: New insights into behavior of ultra-dense star core

Scattered throughout the universe are unimaginably dense remnants of stellar death, cold cores of large stars that have burned through their fuel, collapsed, and blown off their outer layers in supernova(link is external) explosions. Known as neutron

How can I prepare for something I do not yet know?

How can I prepare for something I do not yet know? How can I prepare myself for something I do not yet know? Scientists from the Technical University of Munich (TUM) and from the Fritz Haber Institute Of Berlin have addressed this almost philosophical question in the context of machine learning. Learning is no more than drawing new decisions on prior experience. In order to deal with a new situation in this way, one needs to have dealt with roughly similar situations before. In machine learning, this correspondingly means that a learning algorithm needs to have been exposed to roughly similar data.

Towards new solar cells with active machine learning

Fewer requirements let artificial intelligence discover new materialsTowards new solar cells with active machine learning A research team from the Technical University of Munich (TUM) and the Fritz Haber Institute in Berlin uses active machine learning in the search for suitable molecular materials for new organic semiconductors, the basis for organic field effect transistors (OFETs), light-emitting diodes (OLEDs) and organic solar cells (OPVs). To efficiently deal with the myriad of possibilities for candidate molecules, the machine decides for itself which data it needs. How can I prepare myself for something I do not yet know? Scientists from the Technical University of Munich and from the Fritz Haber Institute in Berlin have addressed this almost philosophical question in the context of machine learning. 

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