Intel Corporation

Daniel Korat

Moshe Wasserblat

Oren Pereg

Ze'ev Rivlin

Vasudev Lal

Phillip Howard

Erik Norden

Gadi Singer

Nagib Hakim

Arden Ma

Ana Paula Quirino Simoes

Methods and apparatus for a knowledge-based deep learning refactoring model with tightly integrated functional nonparametric memory are disclosed. An example non-transitory computer readable medium comprises instructions that, when executed, cause a machine to at least estimate a first information extraction cost corresponding to retrieval of information from a local knowledge base, estimate a second information extraction cost corresponding retrieval of information from a remote knowledge base, select an information source based on the first and second estimated information extraction costs, query the selected information source, in response to determining that the selected information source was an external information source, store the queried information in the local knowledge base, organize the stored information in the local knowledge base, and return the queried information.

Methods and apparatus for a knowledge-based deep learning refactoring model with tightly integrated functional nonparametric memory

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Tel Aviv, Israel

Daniel Korat