
How Facebook M Works - rajathagasthya
http://www.buzzfeed.com/alexkantrowitz/time-to-meet-the-wizard-facebooks-messenger-head-pulls-back?utm_term=.eu56k25XK#.elB0eQL23
======
Shank
> The trainers are a group of a few dozen human contractors working in
> Facebook’s headquarters. These humans, as Marcus explained it, review each
> of the AI’s responses and decide whether they’re good enough to pass along,
> or whether they need revising. When the trainers revise, the AI watches and
> learns: “With every single one of these interactions, that data is fed back
> into that AI instance that will then use the data to learn how to automate
> more and more answers or how to get better and better at those things,”
> Marcus said.

The unfortunate side effect of this is that the training elements won't work
on a larger scale. Yes, the underlying AI can, but the training system can't
handle thousands of requests per day.

People previewing M post things like this
([https://twitter.com/neilkod/status/654442151837831168?ref_sr...](https://twitter.com/neilkod/status/654442151837831168?ref_src=twsrc%5Etfw))
where M does "magical" things like lowering Comcast bills, but this is all
stuff that trainers would either have to intervene for or train some system
for. The result is that people beg for it to go public, expecting this level
of assistance -- even though M won't have nearly the same level of
"intelligence" on the backend.

Google Now, Siri, and Cortana could all have the same level of "usefulness" if
there was an army of "trainers" on the backend, constantly adding new features
for very odd requests, but they wouldn't respond quickly and probably wouldn't
be available.

~~~
artifaxx
They do claim the quality of responses is improving. Will it get to the point
where they can send responses without trainer approval? Who knows, but if they
can get to that point for a majority of responses then it might work.

------
blazespin
The only thing that has me confused is why Apple, Amazon, Google and MSFT
aren't doing this .. or at least one of them. It seems like the right
approach, but I'm surprised by the lack of competition and wondering if there
is a reason for it.

I guess they're in wait and see mode. I guess theoretically, if it works out
you could always throw 100s of millions at contractors to "train". My only
thought though is that there are a lot of automated toolsets being built that
aren't typical deep learning. Things like APIs / screen scraping / automated
voice / etc etc. You can't build that sort of stuff over night.

------
revelation
I'm lead to believe that the AI misspelled "price" as "prince"?

I guess it's in the cracks that we see the human shine through.

------
Hydraulix989
Buzzfeed, on MY Hacker News?!

~~~
danso
They've been doing significant, important stories for at least the last 2
years, after having built up what is now maybe one of the largest
investigative teams with several Pulitzer winners:

[http://www.capitalnewyork.com/article/media/2014/04/8543804/...](http://www.capitalnewyork.com/article/media/2014/04/8543804/chris-
hamby-joins-buzzfeed-pulitzer-hand)

At some point, HN removed the ban against the domain, and so BuzzFeed stories
have been appearing with some frequency:

[https://news.ycombinator.com/from?site=buzzfeed.com](https://news.ycombinator.com/from?site=buzzfeed.com)

------
tzm
From wit.ai (FB acq)..

> Wit.ai works bottom-up. Let your end-users express their intents freely, and
> have your app learn from that and adapt. Not the other way around.

> Each item in your Inbox is something you can act on in order to improve the
> accuracy of your Wit.ai app. A good practice is to start having beta users
> test your app as soon as possible, even if the initial configuration is the
> bare minimum with just a few intents, and then use the Inbox to improve your
> app.

[https://wit.ai/docs/console/complete-guide#extract-
entities-...](https://wit.ai/docs/console/complete-guide#extract-entities-
link)

------
username223
> The trainers are a group of a few dozen human contractors working in
> Facebook’s headquarters. These humans, as Marcus explained it, review each
> of the AI’s responses and decide whether they’re good enough to pass along,
> or whether they need revising.

So the AI of the future is being trained by a group of stressed-out and
underpaid humans screening machine output as quickly as possible. _How could
this possibly go wrong?_

