I only know specifically about the NLP stuff, e.g. Natural Language Understanding (AlchemyLanguage), Natural Language Classification (it's just a multi-label text classifier) and Watson Knowledge Studio (Basically allows you to create your own named entity recognition classifier (NERC), also supports relations and co-reference resolution. You manually hand-annotate examples through a Web UI).
So by platform I mean, lets say you train a NERC model using Watson Knowledge Studio. Obviously this model has to be "deployed" somewhere so you can call it using an API. They host it for you and they bill you per API call. Anyone can go create their own entity type system and manually annotate a training dataset. So it's definitely a re-usable platform, you don't need to pay for any IBM consultancy to use it. I found that the NLP offerings have many problems, and that the documentation alone is not enough to help resolve all of them. So eventually, IBM will just tell your employer you're stupid and that's why it's not working as it should and you should pay IBM to come in.
But make no mistake, these are all just standard machine learning tools that have been "packaged" so end-users can use them through a web front end. It is in no way, whatsoever, getting any input from any AI/Neural Network/Database/whatever you want to call it/ thing called "Watson".
I personally think it's disingenuous because when people hear Watson they think Jeopardy and they think that somehow that technology is involved when they use any of the Watson.* products.
> I personally think it's disingenuous because when people hear Watson they think Jeopardy and they think that somehow that technology is involved when they use any of the Watson.* products.
The use of the Watson name is a deliberate attempt to take advantage of the Jeopardy game. It's a name that has cachet, and I've seen just enough of the marketing perspective to know that marketing will push very hard to reuse a successful name.
So by platform I mean, lets say you train a NERC model using Watson Knowledge Studio. Obviously this model has to be "deployed" somewhere so you can call it using an API. They host it for you and they bill you per API call. Anyone can go create their own entity type system and manually annotate a training dataset. So it's definitely a re-usable platform, you don't need to pay for any IBM consultancy to use it. I found that the NLP offerings have many problems, and that the documentation alone is not enough to help resolve all of them. So eventually, IBM will just tell your employer you're stupid and that's why it's not working as it should and you should pay IBM to come in.
But make no mistake, these are all just standard machine learning tools that have been "packaged" so end-users can use them through a web front end. It is in no way, whatsoever, getting any input from any AI/Neural Network/Database/whatever you want to call it/ thing called "Watson".
I personally think it's disingenuous because when people hear Watson they think Jeopardy and they think that somehow that technology is involved when they use any of the Watson.* products.