Expectations Exceed Reality
The current hype in AI leads many projects to set an unreasonable target or unclear success criteria leading them to over promise and under deliver.
Machine learning appears accessible because of the availability of many open source toolkits. But once you get started, it can be difficult to decipher why a particular model isn’t working, leading to wasted time on unsuccessful approaches.
The challenge is that there is no one-size-fits-all solution. The best approach often takes a lot of experimentation, and the most efficient path is dependent on understanding your data.