Learning how a physical system behaves usually means repeating measurements and using statistics to uncover patterns. That ...

Quantum computing appears on track to help companies in three main areas: optimization, simulation and machine learning. The appeal of quantum machine learning lies in its potential to tackle problems ...

At a time when data are doubling every two years, the U.S. is projected to create over 40 billion gigabytes of data by 2025. To prepare for the influx, Kennesaw State University associate professor ...

One of the current hot research topics is the combination of two of the most recent technological breakthroughs: machine learning and quantum computing. An experimental study shows that already ...

Your phone finishes your sentences, your camera detects faces and your streaming app suggests songs you never thought you would want, thanks to classical AI systems. These are powerful logic engines: ...

Quantum can learn from the AI hype cycle, finding ways to manage expectations of what could be a very transformative technology. In the near- and mid-term, we need to not overplay things and be ...

Overview: Quantum computing promises exponential speedups for complex healthcare problems like molecular simulation, genomics, and precision medicine, but real- ...

Quantum physics has a reputation for needing exotic hardware, from liquid-helium-cooled qubits to sprawling AI clusters, just to crunch through basic simulations. Now a new “physics shortcut” is ...

There is more than one way to describe a water molecule, especially when communicating with a machine learning (ML) model, says chemist Robert DiStasio. You can feed the algorithm the molecule's ...