Thing is that the media doesn't pay proportional attention and respect they do to other companies that haven't proven anything yet.
Where's Google thing that they showed last I/O where an AI would call a business to schedule an appointment? Vaporware.
Some of the insider postmortems on Watson Health that are floating around on the internet are... interesting.
It's being rolled out at right now: https://www.theverge.com/2018/12/5/18123785/google-duplex-ho...
IBMs biggest problems are still cultural, middle management and recruiting / retaining skilled developers. This is why they cannot deliver on the hype their amazing marketing teams create.
They have plenty of very, very smart people. The researchers are not IBM's problem but the management that is not capable of bringing that research to market.
It seems FB and Google have had more negative societal impacts (ie fake news, public manipulation) than IBM, Salesforce, and numerous other niche AI companies.
We all need a more nuanced perspective on all thinks than this absolutism we have embraced as a society, online.
IBM are much more open to mixing up statistical machine learning and symbolic AI, and benefit from the advantages of both. For instance, Watson used a chart parser with transitions learned using deep learning [1] to fill in frames [2] from a natural-language sentence (the challenge sentence in the Jeopardy game) and also Prolog to identify relations between elements of the parse so as to figure out the sentence's context.
Other big AI players are pretty much exclusively focused on statistical machine learning and, in particular, deep learning, and then again for very specialised tasks like image recognition, speech recognition and machine translation. IBM on the other hand is building broader-scope systems, that perform more nuanced, less strict functions; like in this example, debating, or question answering (essentially) with Watson.
So yes, in some sense, IBM is way ahead of the others in creating powerful AI systems. Just let's not confuse IBM's research with the products it tries to sell based on that research.
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[1] You'll have to take my word for that- I've read the Watson research papers but my pdf copies of them are now all on a hard-drive that has since crashed and I don't remember how to find them online.
[2] A cognitive data structure first proposed by Minsky in the '70s:
https://en.wikipedia.org/wiki/Frame_(artificial_intelligence...
Yeah I don't know about that. At best they are starting to incorporate deep learning into Watson. I'm guessing Watson has always been a rules engine and more specifically one designed with a lot of statistical analysis. That's far below the level of sophistication we're at with NNs.
This is IBMs page on deep learning:
https://www.ibm.com/cloud/deep-learning
While it might be nice to use whatever that tool is - it's a wrapper on top of Tensorflow/Keras or Pytorch... Wouldn't it make sense for it to be a wrapper on top of "Watson's API" whatever that is.
There's so much confusion in the market as to what Watson is, and much of it is IBM Marketing's fault. Watson is a Natural Language Processing platform. At a low level it does all the standard NLP stuff - tokenization, part of speech tagging, lemmatization, dependency parsing, co-reference resolution, stopword removal, synonym expansion, etc. Some of this is rule based, some is ML based. Building on top of that you have stuff like an Intent Classifier, Passage Retrieval with a Ranker, Named Entity extraction, Relationship extraction, and Sentiment tagging. Building on top of that, you have the actual commercial applications - chatbot/assistant, semantic search engine, knowledge graph, etc. That's what it is. It's not vaporware or smoke and mirrors, but it's obviously not AGI either.
Sounds like they are gearing up for a launch.