StanfordMLOctave/machine-learning-ex6/ex6/easy_ham/0917.d223f4992983dd7eda98b3...

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----- Original Message -----
From: "Gary Lawrence Murphy" <garym@canada.com>
> ... and the one thing I think we've learned in all that time is that,
> as a help-desk, it doesn't work.
I'm not sure they are doing strictly help-desk stuff.
But the whole 'who in their right mind would use that? it doesn't have all
these cool features!' isn't always a guarantee of failure - maybe there is a
strength in this approach (agents and/or IM as ui) than can find a nich
application space.
>
> In all the prolog-based NL database query systems of the 1980's and
> other later chatterbot helpdesk projects like Shallow Red, even
> simpler tries like Ask Jeeves, people very quickly know they're
> talking to a robot, and the queries anneal to short, truncated and
> terse database-like verb-noun or just noun-keyword requests.
Kind of like a web query - and with google, someone else can turn them into
a link so you don't even have to type anything.
>
> People are just too quick to adapt, and too impatient to forgive a
> clunky interface, and for now, especially when the /average/ computer
> user still can't type more than maybe 5-10wpm, NL is a painfully slow
> clunky interface.
Yes - true true.
>
> Put it this way: Would you login, wake the bot and ask for the Seattle
> weather, or would you do as we /all/ do and just click the weather
> icon sitting there on your desktop?
What about a situation where you don't directly ask/talk to the bot, but
they listen in and advise/correct/interject/etc?
example: two people discussing trips, etc. may trigger a weather bot to
mention what the forecast says - without directly being asked.