What Can Quantum Computers Do?
Δημοσιεύτηκε στις 19 Νοε 2013
Want to Learn More about Quantum Computers? Check out: http://muonray.blogspot.ie/2014/11/qu...
Lockheed
Martin, NASA and Google all have one thing in common: they all own
quantum computers. These quantum computers are superconducting chips
which were designed by D-wave systems and were fabricated at the NASA
Jet Propulsion Laboratories.
NASA and Google share a quantum
computer for use at the Quantum Artificial Intelligence Lab using a 512
qubit D-Wave Two that would be used for research into machine learning
to assist in using artificial neural networks to search through large
astronomical data sets for extrasolar planets and to increase the
efficiency of internet searchs by using A.I. metaheuristics on
heuristical search engines.
Such A.I. metaheuristics may resemble
global optimization problems similar to classical problems such as the
travelling salesman, ant colony or swarm optimization, which can
navigate through maze-like databases. Using entangled particles as
qubits, these algorithms can be navigated far faster than conventional
computers and with much more variables.
By using a decentralized,
quantum swarm AI, it may be possible to simulate emergent behavior
aswell, such as Langton's ant, which could see the rise of quantum-based
simulated intelligence which could go so far as to create realistic
cellular automatons on a computer.
The use of sophisticated
metaheuristics on lower heuristical functions may see computer
simulations which can select specific sub routines on computers by
themselves to solve problems in a truly intelligent way. In this way the
machines would be far more adaptable to changes in sensory data and
would be able to function with far more automation than would be
possible with normal computers.
Moreover, it may be possible to
use metaheuristics to perform error correction on software using neural
networks by comparing the optimized problem solving in a quantum
computer with the regular programming software of a regular computer.
Since regular computers are not quantum mechanical, they must be
programmed classically. However, by using quantum metaheuristics it may
be possible to perform optimization problems using Artificial
intelligence on a quantum computer and then compare to the command line
architecture in a piece of conventional software on a classical
computer, which may be too complex to modify or to check for errors
using human software engineers.
It may become routine that to
design large software, rather than use a team of engineers to design a
single piece of large software and to do multiple tests, revisions and
redistribution, quantum optimization problems will be run though a
machine instructed to do a particular task and the software will be
designed around such optimizations. Computer chips could even be
designed to be superconducting and quantum compatible in a factory or
laboratory and classically operating in conventional computer equipment.
In this way, optimization and programming could be done on the chips in
a factory or lab to search for any possible errors that could arise in
designing software. After which the chips would be used in conventional
computers for their particular tasks. Quantum computers may well find
their place in industry more than anywhere else, designing AI optimized
software around computer chips.
Lockheed
Martin, NASA and Google all have one thing in common: they all own
quantum computers. These quantum computers are superconducting chips
which were designed by D-wave systems and were fabricated at the NASA
Jet Propulsion Laboratories.
NASA and Google share a quantum
computer for use at the Quantum Artificial Intelligence Lab using a 512
qubit D-Wave Two that would be used for research into machine learning
to assist in using artificial neural networks to search through large
astronomical data sets for extrasolar planets and to increase the
efficiency of internet searchs by using A.I. metaheuristics on
heuristical search engines.
Such A.I. metaheuristics may resemble
global optimization problems similar to classical problems such as the
travelling salesman, ant colony or swarm optimization, which can
navigate through maze-like databases. Using entangled particles as
qubits, these algorithms can be navigated far faster than conventional
computers and with much more variables.
By using a decentralized,
quantum swarm AI, it may be possible to simulate emergent behavior
aswell, such as Langton's ant, which could see the rise of quantum-based
simulated intelligence which could go so far as to create realistic
cellular automatons on a computer.
The use of sophisticated
metaheuristics on lower heuristical functions may see computer
simulations which can select specific sub routines on computers by
themselves to solve problems in a truly intelligent way. In this way the
machines would be far more adaptable to changes in sensory data and
would be able to function with far more automation than would be
possible with normal computers.
Moreover, it may be possible to
use metaheuristics to perform error correction on software using neural
networks by comparing the optimized problem solving in a quantum
computer with the regular programming software of a regular computer.
Since regular computers are not quantum mechanical, they must be
programmed classically. However, by using quantum metaheuristics it may
be possible to perform optimization problems using Artificial
intelligence on a quantum computer and then compare to the command line
architecture in a piece of conventional software on a classical
computer, which may be too complex to modify or to check for errors
using human software engineers.
It may become routine that to
design large software, rather than use a team of engineers to design a
single piece of large software and to do multiple tests, revisions and
redistribution, quantum optimization problems will be run though a
machine instructed to do a particular task and the software will be
designed around such optimizations. Computer chips could even be
designed to be superconducting and quantum compatible in a factory or
laboratory and classically operating in conventional computer equipment.
In this way, optimization and programming could be done on the chips in
a factory or lab to search for any possible errors that could arise in
designing software. After which the chips would be used in conventional
computers for their particular tasks. Quantum computers may well find
their place in industry more than anywhere else, designing AI optimized
software around computer chips.
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