What Can Quantum Machine Learning Do?

What can quantum computers do? In this post, we explore the concept of many-body problem in quantum chemistry that may be one of the most immediate applications of quantum computers and quantum machine learning. A main goal of quantum chemistry is to predict the structure, stability, and reactivity of molecules. Modelling how each of these particles interact and affect each other is essentially impossible. In principle, this requires solving the Schrödinger equation for the many-electron problem, a task that is so computationally intensive that even our modern supercomputers fail to perform them fast enough.

The Trade-Off Every AI Company Will Face

Machines learn faster with more data, and more data is generated when machines are deployed in the wild. However, bad things can happen in the wild and harm the company brand. Putting products in the wild earlier accelerates learning but risks harming the brand; putting products in the wild later slows learning but allows for more time to improve the product in-house and protect the brand.

Commercialize quantum technologies in five years

The field of quantum computing will soon achieve a historic milestone — quantum supremacy. It is still unknown whether application-related algorithms will be able to deliver big increases in speed using the sorts of processors that will soon be available. But when quantum hardware becomes sufficiently powerful, it will become possible to test this and develop new types of algorithms.