30 July 2013 – Algorithms developed so far for quantum computers have typically focused on problems such as breaking encryption keys or searching a list — tasks that normally require speed but not a lot of intelligence. But in a series of papers posted online this month on Arxiv (which is an open e-print archive with over 100,000 articles in physics, 10000 in mathematics, and 1000 in computer science) Seth Lloyd of the Massachusetts Institute of Technology in Cambridge and his collaborators have put a quantum twist on AI.
The team developed a quantum version of “machine learning”, a type of AI in which programs can learn from previous experience to become progressively better at finding patterns in data. Machine learning is popular in applications ranging from e-mail spam filters to online-shopping suggestions. The team’s invention would take advantage of quantum computations to speed up machine-learning tasks exponentially.
You can read more in an article that posted in Nature magazine by clicking here.