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sckuzzle t1_iu2aa7o wrote

We use models to control things in real-time. We need to be able to predict what is going to happen in 5 or 15 minutes and proactively take actions NOW. If it takes 5 minutes to predict what is going to happen 5 minutes in the future, the model is useless.

So yes. We care about speed. The faster it runs the more we can include in the model (making it more accurate).

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GPUaccelerated OP t1_iu4w6oh wrote

The perspective of your use case makes so much sense. I appreciate you sharing that info!

Mind sharing which use case that would be? I'm also trying to pin point which industries care about model speed.

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sckuzzle t1_iu5mxmx wrote

This kind of thing is likely applicable to digital twins of many fields. The idea is to create a digital representation of whatever you are trying to model and run it alongside the real thing. It has applications in control engineering and predictive / prescriptive analytics. Depending on the application this could be done many ways (not necessarily using neural nets at all) and be fast or slow to run.

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