b.) quantum digital is boring, quantum analog, now that’s flavortown
b.) quantum digital is boring, quantum analog, now that’s flavortown
What I've recently been doing is using NLP for document classification. It's the type of problem you can solve with many different solutions, but 'Watson' is the one we're using.
I rewrote my initial draft of that sentence to deny IBM their strategy of using Watson as a human name, which is part of the problem. You shouldn't really use a possessive on Watson, because nothing is Watson's as it isn't a person, grammatically or otherwise. Watson is a collective noun, which is a suite of products. Even if you nominally know better, it fools your brain if you let them frame Watson as a proper name of a person.
Watson Knowledge Studio - This is actually just something called SIRE (Statistical Information and Relation Extraction toolkit). The "Watson" in the name means nothing.
Watson Natural Language Understanding API (Note: This is just a product that was called AlchemyLanguage -- something they bought and renamed to include the word "Watson") - I can tell you everything that makes it crippled (you can build a NERC model using Watson Knowledge Studio, but the API has no way for you to extract e.g. negations, sub-entity types, etc. basically any entity attributes). Again, Watson means nothing, it's rebranding an aquisition.
Watson Analytics - It doesn't integrate into anything Watsony except maybe Cognos. I.e. It's completely useless for doing any analytics from any of the other Watson NLU/Classification products. The Social Media component has no way for you to integrate your own data. It's nothing big a big toy meant to be shown in demos. It is 100% useless in practice. I have no idea what they bought and rebranded here. I mean c'mon, I'm using your Watson sentiment analysis crap to do sentiment on Tweets and Facebook and your Watson Analytics product has no way of me getting this analyzed data back in to build visualization and see trends? With a lot of effort, basically somehow normalizing the JSON output from NLU maybe, but there is no icon that says "Import Watson NLU data".
Watson Natural Language Classification - This is just a multi-label text classifier. It's not too bad to be honest, except I don't like the limit of the number of texts per classifier and the limit of the number of characters per text. I also think they need to handle hierarchical multi-label classifications. My biggest problem is... I can't feed the output of NLC into any other Watson tool. How the fuck do I do my analytics? C'mon IBM, throw a man a bone here why must I do everything myself. Why can't I plug the output into Watson Analytics?
Basically everything is branded under a label called "Watson", but none of the products even _remotely_ integrate with one another. There are so many deep flaws in the products. The documentation often does not correspond to reality.
If someone at IBM would just sit down and try and make all these Watson products actually "talk to one another" this would be a really good enterprise quality suite of products. I really think they are close, but they're fucking it up in such a stupid way it dumbfounds me. I honestly don't think anyone at IBM will fix this. They are so big and so stupid at the same time.
Believe nothing you see at an IBM demo or any presentation. It is smokescreen and mirrors. You will have to build something yourself to see the flaws.
What do you mean by that? You mean simulating on analogical classical computers? Or quantum computers without qbits?
I imagine error resistance would become incredibly harder. Does information density grow fast enough to compensate it?