Of course you can't imagine anyone using it because (a) you are not the target audience and (b) you are being deliberately contemptuous about the product because it was built by IBM.
If you simply re-read all your own points from an objective standpoint, it should be apparent that this is geared towards individuals who have minimal or no machine learning (much less deep learning) experience; but nevertheless feel they need features like custom image recognition in their application. Rather than spending time and money hiring a 'seasoned ML engineer' such as yourself, they can try this and see if it works well enough for their purposes. Everything from the HTML interface, dearth of model customization, no parameter tuning, etc. points to this use case. Yes, it will be tedious, time consuming, and perhaps a bit unintuitive at first but it will be nowhere near as difficult for them than if they were to build an equivalent data pipeline, neural network, and evaluation setup on specialized hardware using Tensorflow. From that perspective, this could be a great product for application developers.
Finally, there are tons of REST APIs that enumerate all the functionality found here. They are all part of the Watson Cloud catalog. This includes loading data, training, and deploying models. Moreover, is it really necessary to insult IBM engineers by insinuating that they haven't kept up with the broader paradigm shifts in the field? They build what they are told to build by management (just like at the Big 4).
Achilles willingly left Greece, knowing he would die in Troy, so that he could be known as the greatest warrior in history. Alexander the Great supposedly broke down and cried when he felt he had nobody left to overcome. Julius Caesar in turn, after subduing all of Gaul, wept at the feet of Alexander's statue some 200 years later, lamenting that at the age of 38, he had accomplished nothing compared to Alexander. And there are plenty of such examples in non-Western societies where the losers didn't just get a silver medal; but were killed. This story is as old as humanity itself and just as ubiquitous. I think the fashionable, progressive approach to blaming society is wrong in this case. Seeking greatness over peaceful mediocrity may simply be a character 'flaw' in mankind. As such, failure has become one of our signature moves.
If you simply re-read all your own points from an objective standpoint, it should be apparent that this is geared towards individuals who have minimal or no machine learning (much less deep learning) experience; but nevertheless feel they need features like custom image recognition in their application. Rather than spending time and money hiring a 'seasoned ML engineer' such as yourself, they can try this and see if it works well enough for their purposes. Everything from the HTML interface, dearth of model customization, no parameter tuning, etc. points to this use case. Yes, it will be tedious, time consuming, and perhaps a bit unintuitive at first but it will be nowhere near as difficult for them than if they were to build an equivalent data pipeline, neural network, and evaluation setup on specialized hardware using Tensorflow. From that perspective, this could be a great product for application developers.
Finally, there are tons of REST APIs that enumerate all the functionality found here. They are all part of the Watson Cloud catalog. This includes loading data, training, and deploying models. Moreover, is it really necessary to insult IBM engineers by insinuating that they haven't kept up with the broader paradigm shifts in the field? They build what they are told to build by management (just like at the Big 4).