10d • General discussion
đź”— Why Quantum (Today) Is Always Part of a Hybrid System
One thing I want to be very clear about — and this is based on how things are actually done today — is this:
Quantum computers do not work in isolation.
Every serious quantum workflow today is:
- driven by classical computation
- controlled by classical optimization or ML
- evaluated with classical metrics
The quantum part, when used, is a small component inside a much larger classical pipeline.
For example:
- Data preprocessing is classical
- Model selection is classical
- Training loops are classical
- Decision-making is classical
The quantum system, if used at all, acts as:
- a feature generator
- a sampler
- a structured model component
- or an experimental subroutine
This is why framing quantum as a “replacement” for classical computing is misleading.
A more accurate way to think about it is:
Quantum is a new modeling ingredient — not a standalone solution.
This hybrid view is not a compromise. It’s simply how current hardware, algorithms, and theory actually work.
In this community, we’ll always discuss quantum in this hybrid, realistic context, because that’s the only way it connects to real ML systems and real business workflows.
Question:
When you think about quantum, do you imagine it replacing something — or augmenting something that already exists?
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đź”— Why Quantum (Today) Is Always Part of a Hybrid System
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