4 answers
Where quantum and physics-informed methods beat classical ones today, and where they do not.
For a narrow class of simulation and optimisation problems, yes — usually via quantum-inspired and physics-informed methods on classical hardware rather than on a quantum computer.
Read the full answerA neural network trained with the governing physical equations built into its loss function, so it needs far less data than a purely data-driven surrogate.
Read the full answerOn the problems where the structure fits, quantum-inspired methods have cut training from weeks to hours — roughly 97× — but the speedup is problem-specific, not general.
Read the full answerNo. The methods that pay off today run on classical hardware — quantum hardware access matters for research, not for the production systems these techniques currently serve.
Read the full answerTell us one thing your business does by hand today. In two weeks, we’ll show you how superintelligence would do it.
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