> In other words, why would anyone invest in ML as a service with so many potential forces acting against your continued success? a) You see little chance of r

> In other words, why would anyone invest in ML as a service with so many potential forces acting against your continued success? a) You see little chance of remaining relevant in your field without biting the bullet & providing training data as part of the package deal b) You see "product/service takes off" as a far off dream, with many near-term wins that will make the tradeoff worth it for you. For now. And that has to be good enough. c) You wonder aloud what kind of data that might be, that could be combined into something else, along with your data. Your best strategy people tell you it's not worth getting bothered over, given the nature of your project. Now is the time to take risks. > In other words, why would anyone invest in ML as a service with so many potential forces acting against your continued success? Because those "forces" are wayyyy out there compared to the bigger risk, namely "not having any better ideas" Nobody said MS has to market this to companies that see MS as a potential competitor.