(applause)

Good morning.

(cheering)

Welcome to Google I/O.

It's a beautiful day; I think warmer than last year.

I hope you're all enjoying it. Thank you for joining us.

I think we have over 7,000 people here today.

As well as many, many people--

we're live streaming this to many locations around the world.

So, thank you all for joining us today. We have a lot to cover.

But, before we get started,

I had one important business which I wanted to get over with.

Towards the end of last year, it came to my attention

that we had a major bug in one of our core products.

- It turns out... - (laughter)

...we got the cheese wrong in our burger emoji.

Anyway, we went hard to work.

I never knew so many people cared about where the cheese is.

- (laughter) - We fixed it.

You know, the irony of the whole thing is I'm a vegetarian in the first place.

(laughter and applause)

So, we fixed it-- hopefully we got the cheese right,

but as we were working on this, this came to my attention.

(laughter)

I don't even want to tell you the explanation the team gave me

as to why the foam is floating above the beer.

(laughter)

...but we restored the natural laws of physics.

(laughter)

(cheering)

So, all is well. We can get back to business.

We can talk about all the progress since last year's I/O.

I'm sure all of you would agree

it's been an extraordinary year on many fronts.

I'm sure you've all felt it.

We're at an important inflection point in computing.

And it's exciting to be driving technology forward.

And it's made us even more reflective about our responsibilities.

Expectations for technology vary greatly,

depending on where you are in the world,

or what opportunities are available to you.

For someone like me, who grew up without a phone,

I can distinctly remember

how gaining access to technology can make a difference in your life.

And we see this in the work we do around the world.

You see it when someone gets access to a smartphone for the first time.

And you can feel it in the huge demand for digital skills we see.

That's why we've been so focused on bringing digital skills

to communities around the world.

So far, we have trained over 25 million people

and we expect that number to rise over 60 million

in the next five years.

It's clear technology can be a positive force.

But it's equally clear that we just can't be wide-eyed

about the innovations technology creates.

There are very real and important questions being raised

about the impact of these advances

and the role they'll play in our lives.

So, we know the path ahead needs to be navigated carefully

and deliberately.

And we feel a deep sense of responsibility to get this right.

That's the spirit with which we're approaching our core mission--

to make information more useful,

accessible, and beneficial to society.

I've always felt that we were fortunate as a company

to have a timeless mission

that feels as relevant today as when we started.

We're excited about how we're going to approach our mission

with renewed vigor,

thanks to the progress we see in AI.

AI is enabling for us to do this in new ways,

solving problems for our users around the world.

Last year, at Google I/O, we announced Google AI.

It's a collection of our teams and efforts

to bring the benefits of AI to everyone.

And we want this to work globally,

so we are opening AI centers around the world.

AI is going to impact many, many fields.

I want to give you a couple of examples today.

Healthcare is one of the most important fields AI is going to transform.

Last year we announced our work on diabetic retinopathy.

This is a leading cause of blindness,

and we used deep learning to help doctors diagnose it earlier.

And we've been running field trials since then

at Aravind and Sankara hospitals in India,

and the field trials are going really well.

We are bringing expert diagnosis to places

where trained doctors are scarce.

It turned out, using the same retinal scans,

there were things which humans quite didn't know to look for,

but our AI systems offered more insights.

Your same eye scan,

it turns out, holds information

with which we can predict the five-year risk

of you having an adverse cardiovascular event--

heart attack or strokes.

So, to me, the interesting thing is that,

more than what doctors could find in these eye scans,

the machine learning systems offered newer insights.

This could be the basis for a new, non-invasive way

to detect cardiovascular risk.

And we're working-- we just published the research--

and we're going to be working to bring this to field trials

with our partners.

Another area where AI can help

is to actually help doctors predict medical events.

It turns out, doctors have a lot of difficult decisions to make,

and for them, getting advanced notice--

say, 24-48 hours before a patient is likely to get very sick--

has a tremendous difference in the outcome.

And so, we put our machine learning systems to work.

We've been working with our partners

using de-identified medical records.

And it turns out if you go and analyze over 100,000 data points per patient--

more than any single doctor could analyze--

we can actually quantitatively predict

the chance of readmission,

24-48 hours earlier than traditional methods.

It gives doctors more time to act.

We are publishing our paper on this later today

and we're looking forward to partnering with hospitals and medical institutions.

Another area where AI can help is accessibility.

You know, we can make day-to-day use cases much easier for people.

Let's take a common use case.

You come back home at night and you turn your TV on.

It's not that uncommon to see two or more people

passionately talking over each other.

Imagine if you're hearing impaired

and you're relying on closed captioning to understand what's going on.

This is how it looks to you.

(two men talking over each other)

As you can see, it's gibberish-- you can't make sense of what's going on.

So, we have machine learning technology called looking to listen.

It not only looks for audio cues,

but combines it with visual cues

to clearly disambiguate the two voices.

Let's see how that can work, maybe, in YouTube.

(man on right) He's not on a Danny Ainge level.

But, he's above a Colangelo level.

In other words, he understands enough to...

(man on left) You said it was alright to lose on purpose.

You said it's alright to lose on purpose,

and advertise that to the fans.

It's perfectly okay. You said it's okay!

We have nothing else to talk about!

(Sundar) We have a lot to talk about. (chuckles)

(laughter)

(cheering)

But you can see how we can put technology to work

to make an important day-to-day use case profoundly better.

The great thing about technology is it's constantly evolving.

In fact, we can even apply machine learning

to a 200-year old technology-- Morse code--

and make an impact on someone's quality of life.

Let's take a look.

♪ (music) ♪ (beeping)

(computer's voice) Hi, I am Tania.

This is my voice.

I use Morse code by putting dots and dashes

with switches mounted near my head.

As a very young child,

I used a communication word board.

I used a head stick to point to the words.

It was very attractive, to say the least.

Once Morse code was incorporated into my life,

it was a feeling of pure liberation and freedom.

(boy) See you later. Love you.

I think that is why I like sky diving so much.

It is the same kind of feeling.

Through sky diving, I met Ken, the love of my life,

and partner in crime.

It's always been very, very difficult