Google, NASA, and Universities Space Research Association (USRA) run a joint research lab called the Quantum Artificial Intelligence Laboratory (QuAIL). That partnership has used a 512-qubit D-Wave Two quantum annealer, upgraded to the 1,152-qubit D-Wave 2x, and is now upgrading again to the company's latest D-Wave 2000Q system (2048 qubits):
Google, NASA, and the USRA are now buying the latest generation D-Wave quantum computer, as well, to further explore its potential. The new D-Wave 2000Q is not just up to 1,000 times faster than the previous generation, but it also has better controls, allowing QuAIL to tweak it for its algorithms. QuAIL is now looking at developing machine learning algorithms that can take advantage of D-Wave's latest quantum annealing computer.
[...] D-Wave also announced that it will help the Virginia Polytechnic Institute and State University (Virginia Tech) establish a quantum computing research center for defense and intelligence purposes. D-Wave's role will be to aid the Virginia Tech staff in developing applications and software tools for its quantum annealing computers. [...] Because D-Wave is not a universal quantum computer, like what Google and IBM plan to build over the next few years, it is not expected to be useful in cracking encryption. Virginia Tech plans to also focus on developing machine learning algorithms for the D-Wave computers.
Previously: Trees Are the New Cats: D-Wave Used for Machine Vision
(Score: 1) by charon on Wednesday March 15 2017, @01:38AM (4 children)
(Score: 0) by Anonymous Coward on Wednesday March 15 2017, @01:52AM (1 child)
From what I've read, it's often easier to check the answer than find the solution.
Suppose each hidden neuron in a neural network were a qubit. Then, train the network via quantum principals. What you get out is a thoroughly trained neural network -- immediately.
How do you know it's the right network? Test it. It's not the execution or knowing whether the output is correct that's hard, it's the training that is hard. If it gets 99 out of 100, you've got the right answer.
(Score: 0) by Anonymous Coward on Wednesday March 15 2017, @05:15AM
Suppose each hidden neuron in a neural network were a qubit. Then, train the network via quantum principals.
We call this "going to school" :D
(Score: 0) by Anonymous Coward on Wednesday March 15 2017, @03:45AM
(Score: 2) by Geezer on Wednesday March 15 2017, @07:14AM
Simple. 42.