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Huge spectrum of capability (Cognitive Services, ML Services, Deep RL Bons.AI, AutoML, Data Labelling, advanced model lifecycle management) and pace of innovation.
The ease of use from a data scientist perspective, they can collaborate on the code how much they want and that the underlying infrastructure can scale to their needs automatically
Modular cloud service architecture so there is some enablement work required by the customer to get the integrated machine learning platform working seamlessly for data scientists. The flip side of this is the flexibility for the customer to have an implemented that aligns better to the eco-system of data platforms and deployment targets (systems of record, edge etc)
There are some hassels to put everything together to work well, many stand alone product that needs some thinking to make them work effectively