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>we found that answering factoid questions isn't the most critical function so we haven't prioritized it, but it's coming

This should be priority number one. As others ITT have been saying, your marketing and PR departments have been writing checks that the product can't cash.

When people see that Watson can't do what it does on TV, you lose a sale, and that potential customer is now going to be skeptical of IBM's future marketing claims.

It doesn't matter if "answering factoid questions" doesn't have much real-world value — it's first of all what you're marketing the product as, so it should have been done and omigod amazing yesterday, and second of all the reason why your very smart marketing and PR people are pushing that angle is because it's a demonstration that is immediately and intuitively impressive to technical and non-technical people alike.

Getting a computer to "answer factoid questions" viscerally screams "major breakthrough!" in a way that "general visual classification of earth imagery" simply doesn't. It wows people at the sales meeting instead of boring them.

IBM needs to make sales. You need to build up a userbase toot sweet before Google et al start moving into this sector in a major way, as indeed they already are. There's a limited pool of enterprise customers, they don't change vendors often, and you need to get as many as you can as fast as you can, before Google/Amazon/whoever does, or you're done.

> toot sweet

"Tout de suite" has never before sounded so appetizing!

And I thought toot sweet referred to cocaine[1], which might explain some marketing...

[1] https://books.google.com/books?id=FFMADAAAQBAJ&pg=PA80&lpg=P...

Tu cherches la petite bête !

It's the common spelling when used in English; I didn't want to seem pretentious. https://en.wiktionary.org/wiki/tout_de_suite#Alternative_for...

I'm beginning to believe that answering factoid questions is still too expensive, from a computational point of view, to put in an API.

I'm beginning to believe IBM is a sinking battleship. Considering the job losses and the - insane - direction set by the board, it's not obvious IBM will still be around five years from now.

Besides, a really good AI should literally be able to sell itself, surely?

Let's not make any grandstand statements - IBM may or may not be a sinking battleship (I'm inclined to think they are), but not being around in 5 years is a pretty specious prediction. They'll still be around, and still be peddling malformed solutions. They may be significantly different in leadership, presentation, and execution, but they'll still be around.

I'd love to see how IBM themselves have used Watson to improve their own business.

This, as a potential Watson customer, would give me a much better idea of Watson's potential and real world results. Plus it would establishes more confidence in IBM.

A lesson from my high school economics teacher that has always stuck with me is that you have to be your own product's biggest believer.

No. That's not the issue. We are actually able to shrink wrap it to a point that it has reasonable footprint (a few servers). The problem with factoids are twofold: - It's always a small part of a broader use case (how many queries do you do on Google that are answered by the factoid pipeline?). - It has a lot of domain dependency. It's fine to do it like Jeopardy for general domain, but our customer want domain specificity and that's non-trivial.

I agree. I think this is exactly why it isn't available as an API. They probably had supercomputers worth backing Watson, which they couldn't provide for every single API query. Although I still don't know why they didn't provide it and price it accordingly -- $1 / question or whatever it would require. Or shoot -- price it at expense as a loss leader. Even if they had a person filtering and approving each jeopardy answer they could price it to allow that.

That's all great to hear, and I don't mean to belittle the very real achievements behind Watson, but it seems to miss the core complaint here: Watson can't do any of what the advertising shows.

This isn't a matter of PR overhyping things a bit. Watson has (impressive) capabilities, and IBM's ads show Watson doing things, but the two circles essentially don't overlap. IBM is directly marketing Watson to the general public with promises that are entirely unsupported by the actual product. That's not just questionable business advertising, that's a level of inaccuracy that undermines AI work and understanding across the entire field.

>> Watson can't do any of what the advertising shows.

Google, Facebook and MS also can't (try using Google translate in any other language combination than English and some other Romance or Germanic language). Why is that a problem for IBM specifically, or why will IBM's overpromising bring about the next AI winder, like Schank says?

I'm not sure I've been seeing the same ads you have.

Granted, Facebook Graph Search was horribly oversold, and Cortana is in the same "smart enough to be stupid" bucket as Siri and Alexa and every other vaguely-feminine chatbot on the market. Google Translate is incredibly fragile, and will get me from English to French but not from French to Arabic, or even from French to Quebecois.

But all of that is roughly consistent with their advertising. Obscenely selective demos have a long history in software, and it seems standard (though not good) to assume that you're seeing the best-case uses of whatever product is being advertised. Car ads don't work any differently.

Watson's advertising seems to take things to a whole different level. There's that Bob Dylan ad. They've got a North Face ad where Watson recommends an appropriate jacket for the Pacific Northwest in early spring. And so on. The commercial product Watson can't do those things. They aren't just showing off fragile best-case features, they're making stuff up, or hardcoding specific answers, or offering the North Face a different Watson than what you can get on their developer site.

That bothers me. It bothers me when Google claims Translate can live-interpret foreign street signs, too, but even that's a less wild claim than IBM is making. Promising people a product you simply haven't made isn't kosher, and that's especially true when you're selling AI kool-aid, which is a field that's already ripe with hysterical (and baseless) warnings and promises.

>> Promising people a product you simply haven't made isn't kosher

Agreed- but I'm saying that that's exactly what I get from ads of the products you mention, Siri, Alexa et al.

Case in point: that real-time Skype translation ad that made the rounds a while ago.

In any case, I don't pay that much attention to what is advertised. But I do pay attention to two things: on the one hand, (scientific) papers published by the various teams and on the other hand, the announcements those teams make in the technology press.

I've read most of the Watson papers and quite a few of the NLP stuff from Google and followed the assorted tech press announcements. I have to say that my impression is that Google is brazenly overhyping their stuff, they constantly try to fudge things as much as they can.

Their dependency parser beats previous efforts on the Brown corpus? It's the best natural language parser ever! Their image recognition beats imagenet? It's showing superhuman ability! And so on. IBM's advertisement is relatively tame in comparison.

All the other major players in this are equally unscrupulous and there's no point in singling anyone out.

This is an interesting take - I hadn't really considered it, but on reflections Google's more academic claims are hyped up in a way that IBM doesn't seem especially guilty of. Some of their image recognition breakthroughs have been truly remarkable, but I agree the claims are a bit out of line.

I think I was probably put on edge by the Watson ads not just because of their scope (the Skype thing is similarly inaccurate) but because they conform to a very specific pattern of AI over-promising that I've grown to hate.

To a lot of nontechnical (or even just non-CS) people, strong AI is synonymous with Samantha from Her. We've been seeing people mistake existing tech for that since the 60s, when people were taking ELIZA seriously. Cue Cleverbot, Siri, and most obnoxiously Eugene Goostman (you don't get to claim you passed the Turing Test by convincing 30% of English speaking observers that you're a Ukranian child!)

So I look at the Watson ads and see exactly this pattern at work, but worse than ever. Most people know by now that Siri and Alexa are just voice assistants, and as good as the ads look no one is really claiming otherwise. The Watson ads, by contrast, throw around "cognitive computing" to imply real understanding, and then air scripted exchanges that are simply false, rather than selective. Worse, they're doing mass-market ads for a developer-only product, so viewers won't even try it out and see that it doesn't do what's being shown.

It may not be the worst on an overall-inaccuracy level, but I get twitchy when I hear people respond to discussions of strong AI with "Oh, basically what that Watson thing does?" And I do hear that, somewhat regularly. Crappy product hype is annoying, but I really wish we could stop telling people we've built real intelligence when we haven't.

Have used the google translate app with a camera to translate Japanese menus, museum cards, etc. It wasn't perfect, but considering there are three separate 'alphabets' for it to handle it was pretty amazing.

Produce independently reviewed citation that you are state of the art, or even close to it, in any of these functionality.

Sure here are two (you may have to follow some links to go to the actual publications):

Speech to text: https://developer.ibm.com/watson/blog/2016/04/28/recent-adva...

Emotion: https://developer.ibm.com/watson/blog/2016/02/29/another-ste...

In my experience, Speech to text has been a huge disapointment. I do give you that in the country where I live (Argentina) we speak a different... "dialect" of Spanish that what you've probably used to train your engine. Even then, it's entirely useless for my country, whereas Google has zero problems.

Very fair point. Our STT service, even though it is based on a technology with the very best results for public benchmarks, is not as robust to accents at the moment - for the exact reason you mention, we didn't train it on all the dialects. But that will come with usage in the field. Google has a head start on this but with the usage of our services growing quickly we will be able to catch up quickly.