LinkedIn·Thursday, 2 July 2026·02 Jul 2026
When a controller needs retuning on every new machine variant, the cost shows up in two ways: the hours it takes, and whose hours they have…
Leap Technologies
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When a controller needs retuning on every new machine variant, the cost shows up in two ways: the hours it takes, and whose hours they have to be.
We worked on a project where both constraints were compounding each other. The parameter space was too large to sweep quickly, and navigating it required someone with real feel for the system. That combination made every new variant a significant claim on a specific person's time.
Bayesian optimization gave us a way to separate those two problems. The expert's knowledge stayed in the loop, their time didn't have to.
Full breakdown in the carousel. Happy to trade notes if this pattern sounds familiar.
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