Google has taught a quantum computer to recognize images
Researchers at Google said they managed to get a quantum computer to recognize the cars in the photos. This is reported on the official blog of the company.
The work was done in collaboration with the Canadian company D-wave, which provided the Chimera chip for operation. At present, however, far from all physicists agree that this chip is indeed a quantum computer in the sense that theorists understand this term.
In the framework of this work, researchers used the so-called adiabatic algorithm. The essence of this algorithm is as follows. Consider a system whose states are the solution of a certain known problem. Then, rather slowly and adiabatically (that is, without exchanging heat with the external environment), we “deform” the system to another, which corresponds to the problem under study. It is argued that the “deformed” states of the new system will represent the desired solutions.
Using a similar algorithm, scientists tried to “teach” the system to recognize cars in the picture. For this, the algorithm was fed 20 thousand photos, half of which were cars. Each of the vehicles was manually placed in a special frame. After that, the system was given to work with raw photos. As a result, the chip coped, according to scientists, faster than any of Google’s systems. Scientists emphasize that the practical application of the new technology is still far away.
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More recently, scientists have managed to create the first programmable quantum (in the "correct" sense of the word) computer. The scientists' machine works with two qubits, which can simultaneously be in two states. In the new installation, these objects are realized as beryllium ions in a miniature (about 200 nanometers) magnetic trap.
additions from ALEX_A :
As far as I understand, a quantum computer here is used to train a neural network. The quantum adiabatic algorithm (Quantum Adiabatic Algorithm) is used for optimization. If all is true, then this is a very serious breakthrough in the design of neural networks, and therefore the development of various AI systems, since it will now be much easier to achieve learning a complex neural network and it is even possible to find a global minimum of error (I am not sure) without wandering endlessly over local minima.
Here are links to the news and explanations to it:
Google demonstrates quantum computer image search
Machine Learning with Quantum Algorithms
Quantum Adiabatic Algorithms, Small Gaps, and Different Paths
The work was done in collaboration with the Canadian company D-wave, which provided the Chimera chip for operation. At present, however, far from all physicists agree that this chip is indeed a quantum computer in the sense that theorists understand this term.
In the framework of this work, researchers used the so-called adiabatic algorithm. The essence of this algorithm is as follows. Consider a system whose states are the solution of a certain known problem. Then, rather slowly and adiabatically (that is, without exchanging heat with the external environment), we “deform” the system to another, which corresponds to the problem under study. It is argued that the “deformed” states of the new system will represent the desired solutions.
Using a similar algorithm, scientists tried to “teach” the system to recognize cars in the picture. For this, the algorithm was fed 20 thousand photos, half of which were cars. Each of the vehicles was manually placed in a special frame. After that, the system was given to work with raw photos. As a result, the chip coped, according to scientists, faster than any of Google’s systems. Scientists emphasize that the practical application of the new technology is still far away.
')
More recently, scientists have managed to create the first programmable quantum (in the "correct" sense of the word) computer. The scientists' machine works with two qubits, which can simultaneously be in two states. In the new installation, these objects are realized as beryllium ions in a miniature (about 200 nanometers) magnetic trap.
additions from ALEX_A :
As far as I understand, a quantum computer here is used to train a neural network. The quantum adiabatic algorithm (Quantum Adiabatic Algorithm) is used for optimization. If all is true, then this is a very serious breakthrough in the design of neural networks, and therefore the development of various AI systems, since it will now be much easier to achieve learning a complex neural network and it is even possible to find a global minimum of error (I am not sure) without wandering endlessly over local minima.
Here are links to the news and explanations to it:
Google demonstrates quantum computer image search
Machine Learning with Quantum Algorithms
Quantum Adiabatic Algorithms, Small Gaps, and Different Paths
Source: https://habr.com/ru/post/78228/
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