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1
Definitely. Everyone is still painfully assembling systems based on open source libraries many of which have their origins in research. It‘s not enough to assemble „ML platforms“ that integrate with as many of them as possible.
2
@lalleal What is needed is products that solve actual use cases and provide a real value add beyond training ML models. Not sure if it is hard to generalize or we just haven‘t found ways to do so yet.