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Filmed on Tuesday August 9, 02016
Seth Lloyd is a professor of mechanical engineering and physics at MIT researching quantum information and quantum computing. He is the author of Programming the Universe: A Quantum Computer Scientist Takes on the Cosmos.
Quantum computing is widely considered to be:
A reliable reporter who is familiar with all of the rich variety of quantum research going on and the reality of the remarkable progress in the field (along with its still-expanding potential) is quantum pioneer Seth Lloyd, professor of mechanical engineering and physics at MIT.
Lloyd describes himself as a mechanic of quantum computing, quantum communication, and quantum biology. He is director of MIT’s Center for Extreme Quantum Information Theory, which is working on breakthroughs in general-purpose optimization, vastly enhanced communication, and ultra-precise measurement. In his book Programming the Universe (2006) he proposes that the universe is a vast quantum computer that can eventually be completely understood through local-scale quantum computation.
The 15th-century Renaissance was triggered, Lloyd began, by a flood of new information which changed how people thought about everything, and the same thing is happening now. All of us have had to shift, just in the last couple decades, from hungry hunters and gatherers of information to overwhelmed information filter-feeders.
Information is physical. A bit can be represented by an electron here to signify 0, and there to signify 1. Information processing is moving electrons from here to there. But for a “qubit" in a quantum computer, an electron is both here and there at the same time, thanks to "wave-particle duality.” Thus with “quantum parallelism” you can do massively more computation than in classical computers. It’s like the difference between the simple notes of plainsong and all that a symphony can do—a huge multitude of instruments interacting simultaneously, playing arrays of sharps and flats and complex chords.
Quantum computers can solve important problems like enormous equations and factoring--cracking formerly uncrackable public-key cryptography, the basis of all online commerce. With their ability to do “oodles of things at once," quantum computers can also simulate the behavior of larger quantum systems, opening new frontiers of science, as Richard Feynman pointed out in the 1980s.
Simple quantum computers have been built since 1995, by Lloyd and ever more others. Mechanisms tried so far include: electrons within electric fields; nuclear spin (clockwise and counter); atoms in ground state and excited state simultaneously; photons polarized both horizontally and vertically; and super-conducting loops going clockwise and counter-clockwise at the same time; and many more. To get the qubits to perform operations—to compute—you can use an optical lattice or atoms in whole molecules or integrated circuits, and more to come.
The more qubits, the more interesting the computation. Starting with 2 qubits back in 1996, some systems are now up to several dozen qubits. Over the next 5-10 years we should go from 50 qubits to 5,000 qubits, first in special-purpose systems but eventually in general-purpose computers. Lloyd added, “And there’s also the fascinating field of using funky quantum effects such as coherence and entanglement to make much more accurate sensors, imagers, and detectors.” Like, a hundred thousand to a million times more accurate. GPS could locate things to the nearest micron instead of the nearest meter.
Even with small quantum computers we will be able to expand the capability of machine learning by sifting vast collections of data to detect patterns and move on from supervised-learning (“That squiggle is a 7”) toward unsupervised-learning—systems that learn to learn.
The universe is a quantum computer, Lloyd concluded. Biological life is all about extracting meaningful information from a sea of bits. For instance, photosynthesis uses quantum mechanics in a very sophisticated way to increase its efficiency. Human life is expanding on what life has always been—an exercise in machine learning.--Stewart Brand
Condensed ideas about long-term thinking summarized by Stewart Brand
(with Kevin Kelly, Alexander Rose and Paul Saffo) and a foreword by Brian Eno.
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