at the beginning there was the one true watson. watson was a way to process, correlate and provide indsight on a corpus of knowledge expressed in natural language. the technology was good but had one major weakness: the knowledge extraction part had a large bulk of manual labor needed to weed out the noise from the relevant part, because to a processing engine each bit of information is equal to every other bit of information. so you needed domain expert to proviede an initial tuning and after that watson was a good solution for the problem statement.
this process however required non technical domain expert to be working closely with the watson analysts at the tuning for an unspecified and quite long amount of time, comopounding the already astronomical costs of the solution itself
now as you might imagine like any other company ibm has a lot divisions - cloud, services, intelligence etc. the watson division due the large research costs and the few clients that were able to afford and make use of the tech was scoring too much quarters in red.
ibm is also a financial company, so they did what they usually do when one division needs padding: they started moving everything remotedly related to intelligence and analytics under the watson moniker, to drive up quarterly reports. this had the side effect that the watson marketing is a clusterfuck of overlapping and unrelated solutions that more pften than not don't even work togheter natively, but are presented as a whole ecosistem.
now, of course anyone trying to make sense of the whole thing is going to be faced with all kind of claims against all kind of slutions, without any idea of what does what.
but originally the only omission from marketing was what watson actually required and how and what it could give back to a company. but the problem is... it's the kind of solution that you have to build to see where it goes. you cannot be sure of the results from the beginning.
at the beginning there was the one true watson. watson was a way to process, correlate and provide indsight on a corpus of knowledge expressed in natural language. the technology was good but had one major weakness: the knowledge extraction part had a large bulk of manual labor needed to weed out the noise from the relevant part, because to a processing engine each bit of information is equal to every other bit of information. so you needed domain expert to proviede an initial tuning and after that watson was a good solution for the problem statement.
this process however required non technical domain expert to be working closely with the watson analysts at the tuning for an unspecified and quite long amount of time, comopounding the already astronomical costs of the solution itself
now as you might imagine like any other company ibm has a lot divisions - cloud, services, intelligence etc. the watson division due the large research costs and the few clients that were able to afford and make use of the tech was scoring too much quarters in red.
ibm is also a financial company, so they did what they usually do when one division needs padding: they started moving everything remotedly related to intelligence and analytics under the watson moniker, to drive up quarterly reports. this had the side effect that the watson marketing is a clusterfuck of overlapping and unrelated solutions that more pften than not don't even work togheter natively, but are presented as a whole ecosistem.
now, of course anyone trying to make sense of the whole thing is going to be faced with all kind of claims against all kind of slutions, without any idea of what does what.
but originally the only omission from marketing was what watson actually required and how and what it could give back to a company. but the problem is... it's the kind of solution that you have to build to see where it goes. you cannot be sure of the results from the beginning.