The use of quantum algorithms in AI will increase Machine learning abilities. This will in turn helps to increase productivity in the industries. However, this is a field that is still in a young phase, and we will have to wait a bit more for the technology to roll out.
To extract unmanageable large data sets and to apply machine learning algorithms to them requires large processing power. Researchers have been looking for a way to apply a quantum computing algorithm to AI and this method is known as Quantum Machine Learning (QML). According to Samuel Lorenzo, a Quantum Algorithm researcher “Quantum machine learning can be more efficient than classic machine learning, at least for certain models that are intrinsically hard to learn using conventional computers. We still have to find out to what extent do these models appear in practical applications. in this area, based on the different QML proposals that have already been set forth, it is likely that we’ll start seeing acceleration – which, in some cases, could be exponential – in some of the most popular algorithms in the field, such as ‘support vector machines’ and certain types of neural networks”
Machine learning and AI are the two mainstream where quantum computing comes to play. One of the main features of quantum computing is that it allows us to represent several states simultaneously. This can be an advantage while using Artificial intelligence techniques. Quantum computing increases the speed by doing more calculations and therefore provides faster answers than a human would.
Intel has now a whole dedicated wing of researchers for the quantum algorithm. The ability to handle multiple sets of data at so many states makes it an extremely powerful tool. The very first project of the intel is in the field f material science where quantum computing is used to model extremely small molecules.
Quantum computing due to its increased computational skills will surely influence the modern era. It is said that the time taken to complete complex data problems is minimal which at present takes months maybe years to complete. It has applications in the banking sector, defense sector, education, etc.
