Simple data gets the most out of quantum machine learning

New theoretical research proves that machine learning on quantum computers requires far simpler data than previously believed. The finding paves a path to maximizing the usability of today's noisy, intermediate-scale quantum computers for simulating quantum systems and other tasks better than classical digital computers, while also offering promise for optimizing quantum sensors.

computers data digital intermediate machine machine learning machine learning & ai path quantum quantum computers research scale systems usability