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The title implies that it's going to replace ML models. But it seems that it still uses ML models, but provides a different interface. It also seems that it's u
by plain4 6y ago
The title implies that it's going to replace ML models. But it seems that it still uses ML models, but provides a different interface. It also seems that it's using some AutoML training system, so that in theory little ML expertise is required to use the system.
- FridgeSeal 6y ago> in theory little ML expertise is required to use the system Maybe I'm just a cynical data scientist, but this is how we get people using and interpreting models that they don't necessarily understand the complexities of. If some data violates an underlying assumption or has some complexities around representation and meaning then there's nothing really stopping someone getting a model that appears to fit correctly but gives answers that are meaningless or just wrong.
- arauhala 6y agoIt's not just different interface, but different workflow. In traditional ML you need to a) define model to do prediction A -> B b) train the model, which may take minutes c) then do the predictions form A -> B, which takes (1, 10, 100) microseconds With predictive queries, you: a) Ask prediction for any X based on any A, B and C and expect answers in (1, 10, 100) milliseconds You basically trade throughput and latency to get higher productivity, faster iteration and simplified overall sysstem