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TIMOTHY JORDAN: Hi.
Timothy Jordan, your friendly developer advocate,
here at Google I/O 2017.
I'm in the machine learning area,
and we're gonna check out a lot of really cool stuff.
A reminder before I get to it.
If you'd like to see any of this footage,
or any of the other Sandbox tours that I've been doing,
go to g.co/io/guide.
First off, I'd like to check out the Cloud TPU in person.
Wow.
So much heat sink.
MAGNUS: This look like a skyscrapers.
It's like a miniature city down there.
It's amazing.
TIMOTHY JORDAN: This is seriously one of the best Tron
moments I've had in years.
MAGNUS: This is among the most amazing things
I've ever seen in my life.
TIMOTHY JORDAN: OK, Magnus.
Everybody, this is Magnus.
You may know him from, well, being Magnus,
and all sorts of things.
Hi, Magnus.
MAGNUS: Hi, how are you?
TIMOTHY JORDAN: I'm doing super well.
So you've been hanging out with all this really cool machine
learning stuff all day long.
MAGNUS: Yeah.
That's right.
We've been here all day doing different machine
learning stuff.
TIMOTHY JORDAN: I'd like to check out some of it,
and just play with it.
MAGNUS: OK.
TIMOTHY JORDAN: Let's try AI Duets first.
So what is this?
MAGNUS: So you can actually play on these things,
and then the network generates something back.
Yeah.
TIMOTHY JORDAN: OK.
So it's kind of like the machine playing music with you.
MAGNUS: Yeah.
It's kind of constructing music based on what you play.
It's trying to create something similar, but still different.
TIMOTHY JORDAN: OK I want to try it out.
MAGNUS: Yeah.
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That's a lot of fun.
It feels a little like that scene
in "Close Encounters of the Third Kind."
MAGNUS: Yeah.
Absolutely.
TIMOTHY JORDAN: All right, so there's
one other thing that I would like
to check out while we're here.
And that's the candy sorter.
MAGNUS: Yes.
It's an amazing thing.
It consists of so many different machine learning technologies
in one single demo.
TIMOTHY JORDAN: Should we check it out?
MAGNUS: Yeah, for sure.
TIMOTHY JORDAN: As promised, we're
gonna check out the candy sorter.
What is a candy sorter, you may ask?
Well, Dave's here to tell us what that is.
DAVE: OK, great.
So what we're gonna show here is how
you can infuse machine learning into your apps
without actually being a data scientist.
And the way we're gonna do it is through candy
and through labels.
Now, what we've done is we've gone through,
we've trained a model up in the cloud that for--
basically, we've taken an existing model,
and we've trained it for candy.
So we've put labels, and next to candies.
And we've got a little camera here
that's taking pictures of the candy.
And we put labels that have been associated with the candy.
We sent it up to the Google Cloud Machine Learning engine,
and we've trained the model, we used the Inception V3 model,
and using transfer learning.
And so what we're gonna show now is, now
that the model's been trained, is actually
the serving of the model.
So I'm gonna take candy here and just throw it out
in front of the camera.
And this is just any random candy
that we have trained this model for.
So I like gum.
I want to make sure there's plenty of gum out there.
And you'll want to make sure there's a little bit of space
in between there.
And again, when we train this, this image, it has been--
it has been a well-trained model that
has been modified with these images and these labels.
You can even write your own labels, which is awesome.
So now it's trained.
Now the fun part of this is actually
the serving, the prediction.
So you're gonna speak into this mike,
you're gonna hit this little mike button here,
you're gonna speak into this mike
and ask for some kind of candy.
And it's gonna make a call to our API,
it's gonna understand the text-- it's gonna do a Speech API, so
speech-to-text API, and then it's
gonna understand the intent of what you're
asking for using our natural language processing API,
and then it's going to make a prediction based
upon the model that's sitting out in the cloud.
And the best part is, hopefully--
cross your fingers--
it's gonna give you-- it's gonna pick-- make the prediction,
pick it, and then give it to you.
TIMOTHY JORDAN: Awesome.
OK.
DAVE: All right, so click on that, and speak into the mike.
TIMOTHY JORDAN: May I have some gum?
DAVE: So it understood what you said, May I have some gum.
Now it's going through natural language processing.
It's identifying the noun, the noun there, and gum.
So now it's trying to--
it will then match, based upon the model that's
been modified--
come on, come on, come on--
and it is picking chewing gum.
And there, the camera identified Extra long-lasting watermelon
gum.
Now, the camera's-- the--
and over, and there's your gum.
TIMOTHY JORDAN: That's great.
DAVE: Machine learning in and out.
TIMOTHY JORDAN: So I get to keep this, right?
DAVE: Yeah, actually, I've got like seven boxes back there.
So please, everybody take one.
TIMOTHY JORDAN: Dave, thanks so much.
DAVE: All right, thank you.
TIMOTHY JORDAN: That was pretty great.
All right, so that is the machine learning area.
I hope you've enjoyed these experiences as much as I had.
It's really cool to see machine learning up close and personal,
see how it can be used in real life through these demos.
And I hope it inspires you to do some cool stuff
with TensorFlow and with Cloud.
See you later.
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