Quantum Machine Learning (QML) May Furnish Processing Power Needed by Financial Sector
(BBVA) A new discipline that’s been dubbed Quantum Machine Learning (QML) may furnish the processing power required to extract value from the unmanageable swaths of data currently being collected. Researchers have been trying to figure out a way to expedite these processes applying quantum computing algorithms to artificial intelligence technique.
“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,” says Samuel Fernández Lorenzo, a quantum algorithm researcher who collaborates with BBVA’s New Digital Businesses area. “We still have to find out to what extent do these models appear in practical applications.”
In the financial sector, the combination of AI with quantum computing may help improve and combat fraud detection. On the one hand, models trained using a quantum computer could be capable of detecting patterns that are hard to spot using conventional equipment. At the same time, the acceleration of algorithms would yield great advantages in terms of the volume of information that the machines would be able to handle for this purpose.
