As a software developer, I follow the technical solutions more closely so I love google, but actual business that results in revenue/profit points to other companies like IBM (based on other comments in this thread) making the actual money off of these technologies.

Whose strategy will pay off more in the long term is anyone's guess though.

And yes, sure IBM hasn't been about hardware for a long time, they've been a services company for decades now. But as far as AI/ML is concerned Google and Facebook are attracting the top talent these days, Apple and Microsoft much further down the line.

What would be nice is if they would take the opposite tack, rather than marketing the hell out of it quietly solve lots of problems that are hard to solve in a traditional way. Every time I hear about Watson it is in the context of something where I ask myself "What's the point of being able to do that?". If all there is to hype is the hype itself then it is hollow.

This strategy makes sense if you consider that even in it's heyday Watson was 95% data science consulting firm and 5% actual valuable technology.

I really think Watson is one of the biggest tech marketing bamboozles of the 21st century. Through Jeopardy they really had a segment of the business world and the general public convinced that they had cracked AI, but behind the scenes it was all one-off custom solutions under one trademark.

IBM have built several, individually successful pieces of technology, all branded as "Watson", and used the impression that they are a single entity to market it as far smarter than it actually is.

Under the hood "Watson" technologies seem to fall into 3 categories:

- The very successful publicity stunt on Jeopardy. The technology here was good, although from what I understood from tech talks given by IBM, it was a bit more brute force than you might think.

- Custom built software, often for medical and legal purposes, that is effective, if limited in scope, and comes with a hefty consulting and support contract. You're essentially buying a data science team at IBM.

- Productised machine learning APIs, that aren't particularly great, and are very isolated in their abilities.

(1) is fun but not useful to anyone really, (2) is useful, but expensive and no better than what you'd get from most other consultancies, or might be worse knowing IBM's consulting practices, and (3) is too limited to build the core of a business on, so will likely only ever be used to provide a step up until companies move technologies in house.

I can imagine someone who doesn't know at IBM selling a product:

"Hey we will solve all these problems like magic!"

Then IBM comes back:

"Hey do you have all this data in a specific format and a ton of time to enter and test it and maybe we'll get back to you???"

That's a big loss of trust there with the customer if you come back with that.

It seems like these are products where a lot of caveats needs to be made clear to customers and a real careful technical partnership formed with them to succeed long term. You have to bring the customer along for the ride and exploration and keep them excited for a long time it sounds to make it work.

It was a smart play by IBM, the sales guys want to say AI and machine learning, so give them some generic crap which gets loosely integrated into parent projects and they can have a field day on the phone selling it.

Watson would be a perfect study on modern big business software that these billion dollar consultancy companies engage in.

Plus IBM makes even more doing the “integration” than the original sale.

As a non-expert, it seems like the top end researchers are working for Google(Hinton, Bengio, etc), Facebook(LeCun), Baidu, Uber (ex CMU faculty). I don't really see a lot of machine learning research coming out of IBM comparable to the others.

IBM seems to running on the fumes of it's previous greatness while burning the ship to generate stock market returns.

If they are unable to attract talent and innovate in their core business, how are they supposedly pursuing sophisticated AI, and the biggest question, is why?

What other products or innovations have come out of IBM Research? What is their overall reputation, and why should we believe them? Why don't they release Watson to the world, like Microsoft did with their twitter bot?

If I were a recent grad or even mid level in my career and wanted to work on as interesting projects as I could, I wouldn't be going to IBM. My first priority would be access to interesting and varied datasets, such as what can be obtained at Facebook, Google, Amazon, or another such company. A close second would be any of the players in the hardware ML industry such as Nvidia.

I don't understand what's so special about Watson, it all seems like marketing BS to me for a company in the death throws.

Especially since most people who want to use AI would view Google as a competitor because of the number of services it operates, and IBM is more likely to support someone's desire for on-premises solutions. (The on-site enterprise solutions Google had for search and Earth, for comparison, have been recently discontinued.)

In recent years as news articles heralding the future of Watson for various industries (including healthcare and supply chain), I predicted a similar path. An amazing product in a very narrow environment designed specifically for marketing and selling purposes, and not very adaptable.

FTA: “And everybody’s very happy to claim to work with Watson,” Perlich said. “So I think right now Watson is monetizing primarily on the brand perception.”

This is painfully obvious, as this has been IBM for a very long time.

I don’t even know who those ads are targeting. Anyone who knows anything at all about this stuff will be dismayed at the sheer BS of it all. Everyone else seeing the ads isn’t in a position to steer customers towards IBM for all their AI needs. They really need to kill the whole ad campaign, surely it’s doing IBM more harm than good.

No, the problem was that Watson would be unable to help you learn anything new about enterprise data. IBM didn't even have a plausible, non-trivial proof of concept to trot out six years ago.

The Jeopardy thing was cool but since then it's turned into this mystery black box that will supposedly solve all your problems, but nobody's can seem to point to any real successes that would matter to a business. Honestly it seems mostly like marketing fluff built on some midly proprietary distributed computing technology.