

IBM creating pocket-sized Watson in $16 billion sales push - robdoherty2
http://www.kurzweilai.net/ibm-creating-pocket-sized-watson-in-16-billion-sales-push

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kevinalexbrown
_It also takes a while for Watson to do the “machine learning” necessary to
become a reliable assistant in an area._

This could make a great pay-per-package product. Matlab and Mathematica do
this, for instance, by making easy-to-use statistical or signal processing
packages by subfield.

To expand on the example in the article, taking this into an easier to use
interface for people like medical professionals would be awesome. A friend of
mine who worked in an ER told me Wikipedia is actually used quite frequently.
A program that could intelligently parse medical documents could be a great
next step. It doesn't need to make actual diagnoses, but to jog the memory, an
intelligent "these symptoms are consistent with pneumonia, bronchitis, or
whooping cough" would probably be well-used.

Or for double-checking contraindications at pharmacies. Or for advising
lawyers about applicable case-law. Or for reminding me about relevant studies
as I do literature searches. Cool.

Edit: I imagine this will draw some comparisons to Siri, or its factual
backend, wolfram Alpha. While wolfram Alpha is pretty sweet, I imagine
context-specific question-parsing and machine learning would be much more
powerful here (although I suppose wolfram Alpha/Mathematica could get into
that game, too).

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CodeCube
"A friend of mine who worked in an ER told me Wikipedia is actually used quite
frequently"

God help us, God help us all

~~~
shardling
Yes, surely a random internet commenter is in a better position to understand
what is useful than _someone who actually works in ER._

~~~
CodeCube
It wasn't a comment on the ER doctor's ability to extract value out of
wikipedia. It was a comment on the fact that Wikipedia is the wild west. Far
as I can tell, most erroneous edits on popular subjects are quickly caught.
But I wonder how vigilant those wikipedia editors are on obscure medical
topics that require an expensive medical education to truly understand.

I'd feel better about it if Wikipedia was innovating above and beyond the
implementation of a wiki ... even if the solution is still crowdsourced. For
example I would love to see the application of machine learning to the process
of moderation, not unlike what Stackexchange is working on these days
([http://blog.stackoverflow.com/2012/08/stack-exchange-
machine...](http://blog.stackoverflow.com/2012/08/stack-exchange-machine-
learning-contest/)).

Circling back to the topic at hand, I would actually love it if "Watson"
eventually has all of the data currently available in wikipedia. But with each
fact cross-checked for validity against everything else he already knows.

~~~
justincormack
You mean like Cyc? Its not an easy project as facts are not as tidy as you
might hope <http://en.wikipedia.org/wiki/Cyc>

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jaysonelliot
_Watson’s nerve center is 10 racks of IBM Power750 servers running in Yorktown
Heights, New York, that have the same processing power as 6,000 desktop
computers. Even though most of the computations occur at the data center, a
Watson smartphone application would still consume too much power for it to be
practical today._

So not actually a pocket-sized Watson, but a smartphone app that will connect
to Watson. As long as you've got reliable internet access.

~~~
gradys
That was also the conclusion I drew, but it makes me wonder why that would
take too much power to be practical on a smartphone as the article suggests.
It seems like it would only need to capture the text of the question and push
it over the network to IBM's servers.

~~~
zyb09
I think what they mean is, the datacenters actually running Watson would
consume too much power. A mobile app with millions of users would require many
many instances of Watson running, so 10 racks of servers per instance doesn't
sound feasible.

~~~
alok-g
While I agree with this interpretation, here's an explicit quote from the OP:

"Even though most of the computations occur at the data center, a Watson
smartphone application would still consume too much power for it to be
practical today."

~~~
JanezStupar
Its called lousy writing.

They need to optimize Watson server side for it to become commercially.

p.s.: I for one welcome our new Blue Overlord.

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ChuckMcM
Did anyone else think that if they did this their version would answer with a
question?

A: Watson, the best hamburger I've ever eaten. Q: Where is St. John's bar and
grill?

It would be the RPN of voice activated assistants.

I got a bit annoyed when the article kept conflating 'power' with 'number of
cpu cycles running in parallel to get an answer.' I can tell you that we are
no where near having the compute pipeline of 10 racks of Power750 servers in a
co-processor in a smartphone.

~~~
bicknergseng
Love me some St. John's.

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jonathanyc
Please tell me Apple isn't going to sue IBM for putting a voice-activated
assistant on smartphones...

~~~
ConstantineXVI
I'd wager IBM is the absolute last person anyone would want to tick off on
patents.

~~~
dude_abides
Incidentally, Nuance, the company behind the speech recognition tech in Siri,
licenses several patents from IBM.

I doubt if there exists any technology today that doesn't infringe on any IBM
patent.

~~~
spitfire
I thought nuance was just a mac based GUI over IBM's dragon speech recognition
engine. (IBM bought dragon naturally speaking a few years ago)

~~~
sureshv
Scansoft bought Dragon before merging with Nuance.

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MPSimmons
I've been waiting on this. I've come to the conclusion that half of Tony
Stark's JARVIS is essentially Watson.

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kruhft
Watson in your pocket or a UI on your phone to a Watson in the cloud? Given
the number of servers they used for the Jeopardy Watson I'm sure it's more
like the latter.

~~~
sp332
For Jeopardy, they had to beat 2 champions in 3 seconds on a wide range of
subjects. For a more specific topic or "good enough" answers, you would not
need so much hardware. For example, they kept the whole database in 16TB of
RAM!

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teeja
It'll be a while before I'll take medical advice from a machine that "thought"
Toronto is in the US.

~~~
minikites
Because human doctors never make mistakes?

Run the numbers: who makes more mistakes in aggregate: machines like Watson or
human doctors? I'll take whichever is less.

~~~
viscanti
This would (possibly) be true if all mistakes were weighted equally. As soon
as some mistakes have more weight (like maybe the machine killed you on
accident because it thought your spleen was in your ear), then looking at
aggregate numbers doesn't cut it. You'd need to look at both the frequency of
errors, as well as severity of errors. I'll take the guy who messes up 50% of
the time, but at worst will give me a paper cut over the hypothetical machine
who only makes mistakes 1% of the time, but they're always fatal.

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Grovara123
Does Watson 'learn'?

