Another important milestone in quantum computing:
In “Quantum Advantage in Learning from Experiments”, a collaboration with researchers at Caltech, Harvard, Berkeley, and Microsoft published in Science, we show that a quantum learning agent can perform exponentially better than a classical learning agent at many tasks. Using Google’s quantum computer, Sycamore, we demonstrate the tremendous advantage that a quantum machine learning (QML) algorithm has over the best possible classical algorithm. Unlike previous quantum advantage demonstrations, no advances in classical computing power could overcome this gap. This is the first demonstration of a provable exponential advantage in learning about quantum systems that is robust even on today's noisy hardware.
https://ai.googleblog.com/2022/06/quant ... -from.html
BTW, here's the difference between the more-familiar "quantum supremacy" and "quantum advantage":
Quantum Supremacy: This term still retains Preskill’s original context and is considered the first major step to prove quantum computing is feasible. Specifically, it means: “demonstrating that a programmable quantum device can solve any problem that no classical computing device can solve in a feasible amount of time, irrespective of the usefulness of the problem.” Based on the definition, this threshold has been passed since October 2019, in fact at this point it has been shown by several different companies beyond Google and this is why I refer to the current hurdles as engineering challenges rather that theoretical ones.
Quantum Advantage: Refers to the demonstrated and measured success in processing a real-world problem faster on a Quantum Computer than on a classical computer. While it is generally accepted that we have achieved quantum supremacy, it is anticipated that quantum advantage is still some years away.
Note: The above quote came from an article written
only seven months ago.