Quantum Artificial Intelligence
Quantum computing and artificial intelligence are both transformational technologies and artificial intelligence needs quantum computing to achieve significant progress. Although artificial intelligence produces functional applications with classical computers, it is limited by the computational capabilities of classical computers. Quantum computing can provide a computation boost to artificial intelligence, enabling it to tackle more complex problems in many fields in business and science.
One of the areas where quantum computing is more lucrative and promising is artificial intelligence (AI), which relies on processing huge amounts of complex datasets. As AI operates on the analysis of large datasets, the margin of error and inaccuracy in the process of learning has significant room for improvement — and quantum computing may well allow us to improve the algorithm's ability to learn and interpret.
What is so special about quantum computers?
Quantum computers take advantage of the laws of quantum physics to provide new computational capabilities. While quantum mechanics has been foundational to the theories of physics for about a hundred years the picture of reality it paints remains enigmatic. This is largely because at the scale of our every day experience quantum effects are vanishingly small and can usually not be observed directly. Consequently, quantum computers astonish us with their abilities. Let’s take unstructured search as an example. Assume I hide a ball in a cabinet with a million drawers. How many drawers do you have to open to find the ball? Sometimes you may get lucky and find the ball in the first few drawers but at other times you have to inspect almost all of them. So on average it will take you 500,000 peeks to find the ball. Now a quantum computer can perform such a search looking only into 1000 drawers. This mind boggling feat is known as Grover’s algorithm.
Keeping in mind that the term “quantum AI” means the use of quantum computing for computation of machine learning algorithms, which takes advantage of computational superiority of quantum computing, to achieve results that are not possible to achieve with classical computers. That will be critical if we are going to be able to process the monumental amount of data we generate and solve very complex problems. Artificial intelligence, and in particular machine learning, can benefit from advances in quantum computing technology, and will continue to do so, even before a full quantum computing solution is available. Quantum computing algorithms allow us to enhance what’s already possible with machine learning.
How Can AI And Quantum Computers Work Together?
One of the areas where quantum computing is more lucrative and promising is artificial intelligence (AI), which relies on processing huge amounts of complex datasets. As AI operates on the analysis of large datasets, the margin of error and inaccuracy in the process of learning has significant room for improvement — and quantum computing may well allow us to improve the algorithm's ability to learn and interpret.
Today’s computer intelligences are limited by the amount of data they have access to, and how quickly they can analyze it. Many of the problems affecting AI today, including things like accidentally programming inherent bias into their systems, could be caused by the limitations of the datasets they are using. Employing quantum computers to give an AI quick access to trillions more data points could supercharge its accuracy and usefulness.
