A weblog by Will Fitzgerald

What's the opposite of 'hype'?

There must be an antonym for ‘hype.’ To hype something is to engage in hyperbole about it: Apple products have generated their share of hype. (For example: Steve Jobs said, “We made the buttons on the screen look so good you’ll want to lick them.”) I don’t mean ‘anti-hype’ in the sense of telling the approximate truth about something, desengaño or dis-illusionment. But after the IPhone announcement, Steve Ballmer said, “There’s no chance that the iPhone is going to get any significant market share. No chance.” Ballmer was deliberately understating the case. In rhetoric, meiosis comes pretty close. And diss comes pretty close, too, though both of these lack that ‘the person doing this should really know better” connotation of ‘hype.’

Anyway, I got to thinking about this after listening to Marketplace’s piece on the company I work for, Powerset, in which Leo LaPorte “explains its efforts” to Kai Ryssdal.

Example 1: LaPorte says, “I just want to point out that artificial intelligence has been a horrendous failure since the day the term was coined.” Well, the term was coined approximately 50 years ago, and, although there have been very significant failures in AI, there have been plenty of successes as well (see, for example, the list on the AAAI website, and its article on the “The AI Effect“).

Example 2: LaPorte (having been asked about AskJeeves) says, “AskJeeves is a very good example. They’re still around, they’ve been around as long as Google, they’ve spent a lot of money on advertising. But they’re still a distant second.” In other words, a company is only successful if they have more than half the market share; and an implication that Powerset claims it can beat Google in market share. As far as I know, Powerset has never claimed we can take away Google’s lead in the search market place–we are working on things which we think are better than some of Google’s approaches in core search, but this isn’t a claim that we can beat Google in market share.

I’d have a little more respect for the Marketplace commentary if they’d managed to spell our company name correctly. You know, you could have googled it to get it right, Kai.


4 responses to “What's the opposite of 'hype'?

  1. brendan September 27, 2007 at 2:45 am

    The articles on the AAAI pages are great, thanks!

    Doesn’t sound like LaPorte is especially familiar with what are the challenges with search engines. For example, he seems to think that text extraction from HTML is a really big limitation for relevant results. I mean, sure it’s important, but it doesn’t seem like that’s the key place to improve search engines.

  2. Alexandre Rafalovitch September 27, 2007 at 7:45 am

    FUD – “Fear, uncertainty, and doubt”; that’s the word (well, abbreviation) you are looking for.

  3. Michael H. September 30, 2007 at 3:13 pm

    The timing of LaPorte’s comment on AI seems funny to me, given that Dr. Dobbs just had a 4-page article titled, “AI: It’s OK — Is AI on the rise again?”

    Final paragraph:

    Right now, the balance in AI work seems to be tipped toward applied over theoretical, and toward the connectionist over the symbolist. But if history is a guide, things could shift back. Another tilt noticeable in the AI work presented at AAAI this summer is modesty over hype. It’s something that’s been going on since the AI Winter of the ‘90s that followed the disappointment over the overpromising of the ‘80s. AI advances are not trumpeted as artificial intelligence so much these days, but are often seen as advances in some other field. “AI has become more important as it has become less conspicuous,” Winston says. “These days, it is hard to find a big system that does not work, in part, because of ideas developed or matured in the AI world.” And that note of modesty may be a good thing both for the work and for AI.

  4. Michael H. September 30, 2007 at 3:18 pm

    Ha, okay, I see the Michael Swaine article I referred to in DDJ is at the top of your “AI Effect” link. So, you’re already there.

    Also, the quotes by Rodney Brooks & Michael Kearns at the top of the page echo one of my frustrations with how AI is perceived. Constantly moving the fenceposts is unfair! No wonder people seem to prefer talking about “data mining” or “statistical inference” or other more specific terms, so they can avoid the questions that follow.

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