Seth Lloyd: Quantum Machine Learning
Δημοσιεύθηκε στις 9 Απρ 2014
Seth Lloyd visited the Quantum AI
Lab at Google LA to give a tech talk on "Quantum Machine Learning." This
talk took place on January 29, 2014.
Speaker Info:
Seth
Lloyd is one of pioneers in the quantum information science with several
seminal contributions to quantum computing, quantum communication, and
quantum control. He developed the first quantum algorithms for efficient
simulation of many-body systems at the quantum scale. He has also
introduced the first realizable model for quantum computation and is
working with a variety of groups to construct and operate quantum
computers and quantum communication systems. Dr. Lloyd is the author of
over a hundred and fifty scientific papers, and of `Programming the
Universe,' (Knopf, 2004). He is currently professor of
quantum-mechanical engineering at MIT.
Abstract:
Machine
learning algorithms find patterns in big data sets. This talk presents
quantum machine learning algorithms that give exponential speed-ups over
their best existing classical counterparts. The algorithms work by
mapping the data set into a quantum state (big quantum data) that
contains the data in quantum superposition. Quantum coherence is then
used to reveal patterns in the data. The quantum algorithms scale as the
logarithm of the size of the database.
Lab at Google LA to give a tech talk on "Quantum Machine Learning." This
talk took place on January 29, 2014.
Speaker Info:
Seth
Lloyd is one of pioneers in the quantum information science with several
seminal contributions to quantum computing, quantum communication, and
quantum control. He developed the first quantum algorithms for efficient
simulation of many-body systems at the quantum scale. He has also
introduced the first realizable model for quantum computation and is
working with a variety of groups to construct and operate quantum
computers and quantum communication systems. Dr. Lloyd is the author of
over a hundred and fifty scientific papers, and of `Programming the
Universe,' (Knopf, 2004). He is currently professor of
quantum-mechanical engineering at MIT.
Abstract:
Machine
learning algorithms find patterns in big data sets. This talk presents
quantum machine learning algorithms that give exponential speed-ups over
their best existing classical counterparts. The algorithms work by
mapping the data set into a quantum state (big quantum data) that
contains the data in quantum superposition. Quantum coherence is then
used to reveal patterns in the data. The quantum algorithms scale as the
logarithm of the size of the database.
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Τυπική άδεια YouTubeANAΡΤΗΣΗ ΑΠΟ ΤΟ YOUTUBE 28/4/2014
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