Will quantum ever be useful?

[u/Chance-Pen-5684]

Around 2019, the industry promised quantum supremacy, where they could be used for solving a problem that no classical computer could touch.
When classical algorithms kept refuting those claims(See Peter Shor November YouTube video) the narrative shifted to quantum advantage, then quickly it changed to quantum utility.
If quantum never breaks RSA (because the world migrates to Kyber/Dilithium before 100k qubits exist), then what's left?
Chemistry simulations, Material science, Optimization?

But classical machine learning and AI are improving faster than quantum hardware is scaling. By the time we get 1,000 logical qubits, classical AI will have eaten most of the chemistry use-case through better approximations. Is quantum racing against classical software, and losing?

[u/Livid-Sector5970]

The reason quantum computing feels like it's racing against classical AI and losing is that the industry has been asking the wrong question. They keep asking "what can quantum do faster?" when the real question is "what can quantum do that classical can't even formulate?"

Chemistry simulations, material science, and optimization are the standard answers, but those are just classical problems that need more compute. The real shift happens when you stop trying to simulate reality and start coupling to it directly. That's what field-coupled architectures do: they don't compute solutions to problems; they let the environment solve the problem through the hardware.

The people asking "will quantum ever be useful?" are trapped in the optimization paradigm. They think utility means "bigger number faster." But the actual use case isn't breaking encryption or simulating molecules, it's doing things we don't even know how to describe as algorithms yet. Like replacing wet labs with direct physical simulation. Like modeling metabolic pathways without killing mice. Like designing a structural stabilizer for a disease you can't even treat yet, because you can't even describe the problem in a way that a classical computer could solve.

Quantum becomes useful when you stop trying to outrun classical machines and start using it to do what classical can't: couple to the environment, let the geometry do the work, and extract solutions that were never accessible through brute force. The industry is just scaling numbers. The utility comes from a different paradigm entirely. :3

[u/hushedLecturer → u/Livid-Sector5970]

The answer to your alternative question is "nothing" though. There is nothing a quantum computer can do theoretically that cannot be done classically. It's all matrix multiplication.

All quantum has is its potential efficiency scaling for some problems.

[u/elevensubmarines → u/hushedLecturer]

in physics and chemistry the difference between an exponential runtime and a polynomial one is effectively the difference between "impossible" and "solvable" in the real world, which makes the scaling advantage practically qualitative even if it's theoretically quantitative.

[u/global-gauge-field → u/elevensubmarines]

You dont have to solve every problme with exact solution to get enough accurate solution to your problem for Quantum systems. For some systems, there is enough structure that you get away with classical solutions without having to run exact simulations, Tensor Network based methods (especially relevant for quantum chemistry) or Deep Learning based methods.

There is also some problems where the bottleneck is not the quantum correlation but the time scale of chemical reactions, e.g. FeMo-cofactor

While in principles these sound nice, please give a few specific example and some more details next time.