Exploring the World of Quantum Computing: Applications and Limitations
While quantum computers can process data exponentially more efficiently than traditional computers using a qubit which mimics the state of a subatomic particle, they’re not for every application. In fact, their speed and accuracy are limited to problems that can’t be solved by classical computers.
Machine learning and optimization – AI algorithms that rely on large amounts of data to learn and improve can choke standard computers. In these cases, a quantum computer would be able to store more data more quickly and use that data to make predictions faster.
Fraud detection – Healthcare fraud costs billions of dollars a year, and traditional computers can’t keep up. A quantum computer could incorporate more data and improve pattern detection to flag potential fraud, helping insurers to cut that cost.
Weather prediction – While traditional computers can model weather patterns and traffic models, they’re not always accurate. This is because there are too many variables that change too rapidly for them to keep up.
A quantum computer’s advantage is its ability to be in multiple states simultaneously, a concept called superposition. This can allow it to solve a problem faster by trying different solutions and seeing which one works best, without being hampered by the constraints of its single-state state.
While these applications might seem far-fetched, they do represent a promising direction for quantum computing research to take. But only a broad-based commitment to quantum research can determine whether they will become reality or not.
