From The Verge:
And it's learning as you do it
One of the most amazing things you can do with Wolfram Alpha is ask it
what planes are overhead. If you're on your phone, it will pull your
location, then cross reference that with a database of flights,
including their altitude, angle, and even their flight number and
aircraft type. But in many ways, Stephen Wolfram's latest search tool
is more impressive. It's designed to identify anything in a picture.
You just upload a photo, and get a computer-generated guess just a few
seconds later.
"It won’t always get it right, but most of the time I think it does remarkably well," Wolfram writes.
"And to me what’s particularly fascinating is that when it does get
something wrong, the mistakes it makes mostly seem remarkably human." In
some brief testing, that's a pretty fair assessment. I plugged in
things like Yosemite National Park's Half Dome and was told it was
"elevation," while a photo of a gecko was identified as a "night
lizard." Remarkably though, it identified a picture of a cow as "black
angus," and two cups of ice cream as "frozen yogurt." Close enough.
The system was trained with cats, sloths, and Chewbacca
How all this ascends beyond assaulting a website with photos of your
last vacation or what's in your kitchen, is tantalizing. Wolfram says he
imagines the project could be useful if applied to large collections of
photos to attempt to identify and categorize them. The technology can
also be used by others to build image identification into their apps.
Think about the visual recognition found within Google+'s photos, but in other photo apps and services....MORE
Way back in 2012 we saw "
Artificial Intelligence: Why There is No Reason to Fear The Singularity/HAL 9000":
Google researchers and Stanford scientists have discovered that if you show a large enough computing system millions of images from random YouTube videos for three days, the computer will teach itself to recognize ... cats.
