Quantum Machine Learning
Most useful work today is hybrid: a classical pipeline with a quantum-inspired or quantum-capable block.
Classical ML is production-ready. QML is experimental. It may help with certain kernels, sampling or optimisation. It does not replace an ordinary business model in 2026.
The founder is pursuing a PhD in Quantum AI. No invented papers. Continue to Quantum AI and Research.
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