Quantum computers represent the future when it comes to the development of machine learning or artificial intelligence (AI). A new study called “Supervised learning with quantum enhanced feature spaces,” conducted by IBM and recently published in Nature, shows that a quantum computer can become more powerful and can help artificial intelligence to develop by learning algorithms faster and better. As the computers’ Quantum Volume will increase, they will be performing feature mapping with ease.
Artificial intelligence operates better when data can be classified according to specific characteristics or features. According to IBM researchers Kristian Temme and Jay Gambetta, “feature mapping is a way of disassembling data to get access to finer-grain aspects of that data.”
For example, data features and aspects can be isolated one from the other with the help of feature mapping created by a quantum computer, something that a classical machine learning algorithm is not able to do. This way, artificial intelligence will be able to spot data patterns that traditional systems are unable to see.
IBM researchers unveiled their breakthrough in developing algorithms for a quantum computer with machine learning
Quantum computers can generate more precise and sophisticated data maps so that researchers can promote more effective machine learning. To operate calculation, the qubits of a quantum computer have to stay in a quantum state as long as possible. The “noise” was thought to be an issue, but it turned out that the IBM researchers were able to classify data with precision.
Even if there is still a long way for quantum computers to outrun classical computers and their ability to perform artificial intelligence algorithms, the IBM researchers said that “there are high hopes that quantum computing’s tremendous processing power will someday unleash exponential advances in artificial intelligence.”
The researcher’s algorithms will be available for industry experts and other researchers on an open-source library of quantum algorithms, Qiskit Aqua, and they can access them through programming languages like Python.
Erin VanDyke lives on her family farm and has more than 35 years of hands-on experience with the use of livestock guard dogs for predator control. On their farm, Jan and her family use corgis as herding dogs and have raised Shetland sheep, Fainting goats, Morgan and Trakehner horses, and historic breeds of chickens and turkeys. Erin is also an active beekeeper.