Ever wonder what will happen when exabyte data stores are the norm, and even the parallelism of Hadoop can no longer provide the necessary processing power to address the data deluge? Quantum computing may hold the answer. Seth Lloyd from MIT visited the Google Quantum AI Lab in Los Angeles to give a tech talk on “Quantum Machine Learning.” 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.
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.
You can read up on quantum algorithms for supervised and unsupervised machine learning with this recent research paper by Dr. Lloyd.
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