35
$\begingroup$

What aspects of quantum computers, if any, can help to further develop Artificial Intelligence?

$\endgroup$
22
$\begingroup$

Quantum computers are super awesome at matrix multiplication, with some limitations. Quantum superposition allows each bit to be in a lot more states than just zero or one, and quantum gates can fiddle those bits in many different ways. Because of that, a quantum computer can process a lot of information at once for certain applications.

One of those applications is the Fourier transform, which is useful in a lot of problems, like signal analysis and array processing. There's also Grover's quantum search algorithm, which finds the single value for which a given function returns something different. If an AI problem can be expressed in a mathematical form amenable to quantum computing, it can receive great speedups. Sufficient speedups could transform an AI idea from "theoretically interesting but insanely slow" to "quite practical once we get a good handle on quantum computing."

$\endgroup$
  • 1
    $\begingroup$ Adding to this answer, matrix multiplication is the backbone of most Machine Learning applications today. Anything that uses a GPU today could tomorrow use a quantum computer bringing us that much closer to AI. $\endgroup$ – Harsh Aug 3 '16 at 1:03
  • 2
    $\begingroup$ ML is subset if AI. Deep ML is subset if ML. Hence we are not building any AI by multiplying matrices. We simply cut the best pieces out of a corpse like piranhas. For publications scores degrees grants tenures and money. I really doubt an actual AI is going to have anything to do with speed of multiplying matrices. Human brain produces intelligence effortlessly using infinitely slower apparatus compared to a quantum computer. $\endgroup$ – Boppity Bop May 28 '17 at 22:00
8
$\begingroup$

Until we can make a quantum computer with a lot more qubits, the potential to further develop AI will remain just that.

D-Wave (which has just made a 2,000+ qubit system around 2015) is an adiabatic quantum computer, not a general-purpose quantum computer. It is restricted to certain optimization problems (at which its effectiveness has reportedly been doubted by one of the originators of the theory on which it is based).

Suppose that we could build a 32 qubit general-purpose quantum computer (twice as big as current models, as far as I'm aware). This would still mean that only 232 possibilities exist in superposition. This is a space small enough to be explored exhaustively for many problems. Hence, there are perhaps not so many problems for which any of the known quantum algorithms (e.g. Shor, Grover) would be useful for that number of bits.

$\endgroup$
  • $\begingroup$ "D-Wave (which has just made a 2,000+ qubit system around 2015)" This statement is misleading at best. Be aware that D-Wave has claimed to create a computer using adiabetic quantum annealing. This computation model is significantly different than other quantum computing models. For example, I'm not aware whether Shor and Grover work on this model! So, talking about "2,000+ qubits" is a bit misleading: computers in the model where we care about the qubit count have something around 50 qubits as the current frontier. $\endgroup$ – Discrete lizard Mar 21 '18 at 13:28
  • $\begingroup$ Also note that there are experts that do not believe adiabetic quantum annealing can give significant improvements on the classical computing technique of simulated annealing. $\endgroup$ – Discrete lizard Mar 21 '18 at 13:29
4
$\begingroup$

Quantum computers can help further develop A.I. algorithms and solve the problems to the extent of our creativity and ability to define the problem. For example breaking cryptography can take seconds, where it can takes thousands of years for standard computers. The same with artificial intelligence, it can predict all the combinations for the given problem defined by algorithm. This is due to superposition of multiple states of quantum bits.

Currently, quantum computers are still in the early stages of development and can perform complex calculation. There are already technologies like D-Wave systems which are used by Google and NASA for complex data analysis, using Multi-Qubit type quantum computers for solving NSE fluid dynamics problems of interest or global surveillance for military purposes, and many more which we're not aware.

Currently there are only a few quantum computers available to the public, like IBM Quantum Experience (the world’s first quantum computing platform delivered via the IBM Cloud), but it's programming on quantum logic gates levels, so we're many years behind creating artificial intelligence available to public. There are some quantum computing languages such as QCL, Q or Quipper, but I'm not aware any libraries which can provide artificial intelligence frameworks. It doesn't mean it's not there, and I'm sure huge companies and governments organisations are using it for their agenda to outcome the competition (like financial market analysis, etc.).

$\endgroup$
0
$\begingroup$

Together with quantum computers,quantum mechanics and Quantum mathematics will change the future of Artificial Intelligence.

In current computation cost and limitation the super invention complex number usage is limited,many statistical problems and algorithms are in queue waiting to process and make it in production,Quantum computers are not able to solve it as the current computation error is high,Quantum mathematics won't die and special computation logic will come to tackle this ,More info available

$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.