Recently, Italian researchers have created the first working quantum neural network by operating a distinctive algorithm on a real quantum computer.

At the beginning of this month, Francesco Tacchino et al. from the University of Pavia in Italy, pre-published their paper titled “An Artificial Neuron Implemented on an Actual Quantum Processor” in ArXiv.

Mainly, they created a single-layer artificial neural network (ANN) that can operate on a quantum computer. This basic type of ANN is known as a perceptron, and it can create more robust neural network.

Earlier works related to developing a perceptron on a quantum system have taken separate qubits as neurons in a network. But this method is clumsy and very complicated which has not been able to produce productive results.

Tacchino and the team thought of trying a different method:
“Here we introduce an alternative design that closely mimics a Rosenblatt perceptron on a quantum computer …We experimentally show the effectiveness of such an approach by practically implementing a 2 qubits version of the algorithm on the IBM quantum processor available for cloud quantum computing.”

A five-qubit quantum system with cloud access, Q Experience computer of IBM, has been taken as a way to communicate with quantum computing for people who don’t have lots to spend on labs and access to top-notch engineers and physicists. But, normally, it is taken as an educational device.

One of the main issues with quantum computers is that there are not any programs, codes of software for them. It is tough to develop codes for a machine that challenges the laws of physics. However, it can happen. The Italian group has proved it by successfully operating the perceptron model on the IBM Q computer and utilizing the subsequent artificial neural network (ANN) to perform image recognition tasks. For now, it can recognize three fundamental patterns in the target image. This may not sound very impressive, but it has value because of the quantum advantage.

The researchers claim:

“Our algorithm presents an exponential advantage over classical perceptron models, as we have explicitly shown by representing and classifying 4 bits strings using 2 qubits, and 16 bits strings using only 4 qubits.”

This implies that artificial neural network (ANN) operating on quantum computers could possibly be exponentially tougher when compared with classical computers. The effects of this combination of quantum computing and Artificial Intelligence are way beyond dreams.

What happens when the machines with the ability to act as translators among the humankind and the basic raw language of the universe are created? Philosophers can best answer it. However, in physics’ world, it is possible that new type of machine learning comes and it replaces the old traditional deep learning networks. The engineers are creating more innovate quantum computers and the researchers are studying more about artificial neural networks (ANNs).

Intelligent machines in the future will be both quantum and AI-powered.