[MUSIC PLAYING]
[CHEERING AND APPLAUSE]
JOSH WOODWARD: Thanks, Thomas.
Our work is enabling businesses.
And it's also empowering developers.
PaLM 2, our most capable language model
that Sundar talked about, powers the PaLM API.
Since March, we've been running a private preview
with our PaLM API.
And it's been amazing to see how quickly developers have used it
in their applications.
Like CHAPTR, who are generating stories
so you can choose your own adventure, forever changing
story time, or GameOn Technology,
a company that makes chat apps for sports fans
and retail brands to connect with their audiences.
And there's also Wendy's.
They're using the PaLM API to help customers
place that correct order for the Junior Bacon Cheeseburger
they talked about in their talk to menu feature.
But I'm most excited about the response
we've gotten from the developer tools community.
Developers want choice when it comes to language models.
And we're working with leading developer tools companies
like LangChain, Chroma, and many more to support the PaLM API.
We've also integrated it into Google Developer tools
like Firebase and Colab.
[CHEERING AND APPLAUSE]
You can hear a lot more about the PaLM API in the developer
keynote and sign up today.
Now, to show you just how powerful the PaLM API is,
I want to share one concept that five engineers at Google
put together over the last few weeks.
The idea is called Project Tailwind.
And we think of it as an AI first notebook
that helps you learn faster.
Like a real notebook, your notes and your sources power
Tailwind.
How it works is you can simply pick
the files from Google Drive.
And it effectively creates a personalized and private AI
model that has expertise in the information that you give it.
We've been developing this idea with authors like Stephen
Johnson and testing it at universities like Arizona State
and the University of Oklahoma, where I went to school.
You want to see how it works?
[CHEERING]
Let's do a live demo.
[APPLAUSE]
Now, imagine I'm a student taking a computer science
history class.
I'll open up Tailwind.
And I can quickly see in Google Drive
all my different notes and assignments and readings.
I can insert them.
And what'll happen when Tailwind loads up,
as you can see, my different notes and articles on the side.
Here they are in the middle.
And it instantly creates a study guide
on the right to give me bearings.
You can see it's pulling out key concepts and questions grounded
in the materials that I've given it.
Now, I can come over here and quickly
change it to go across all the different sources and type
something like "create glossary for Hopper."
And what's going to happen behind the scenes
is it'll automatically compile a glossary associated
with all the different notes and articles
relating to Grace Hopper, the computer science history
pioneer.
Look at this.
Flowmatic, COBOL, compiler, all created based on my notes.
[APPLAUSE]
Now, let's try one more.
I'm going to try something else called "different viewpoints
on Dynabook."
So the Dynabook, this was a concept from Alan Kay.
Again, Tailwind going out, finding
all the different things.
You can see how quick it comes back.
There it is.
And what's interesting here is it's helping
me think through the concept.
So it's giving me different viewpoints.
It was a visionary product.
It was a missed opportunity.
But my favorite part is it shows its work.
You can see the citations here.
When I hover over, here's something from my class notes.
Here's something from an article the teacher assigned.
It's all right here grounded in my sources.
[CHEERING AND APPLAUSE]
Now, Project Tailwind is still in its early days.
But we've had so much fun making this prototype.
And we realized it's not just for students.
It's helpful for anyone synthesizing information
from many different sources that you choose, like writers
researching an article or analysts
going through earnings calls or even
lawyers preparing for a case.
Imagine collaborating with an AI that's
grounded in what you've read in all of your notes.
We want to make it available to try it out
if you want to see it.
[CHEERING AND APPLAUSE]
There's a lot more can do with PaLM 2.
And we can't wait to see what you build using the PaLM API.
Generative AI is changing what it
means to develop new products.
At Google, we offer the best ML infrastructure
with powerful models, including those in Vertex,
and the APIs and tools to quickly generate
your own applications.