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"Google began as a research project in 1996."
"This is a look at how search has evolved."
Gomes: Our goal is actually to make improvements to Search
that just answer the user's information need.
Get them to their answer faster and faster.
So that there's almost a seamless connection between
their thoughts and their information needs
and the search results that they find.
Singhal: Well, Google was started based upon algorithms
that Larry and Sergey developed in Stanford
called the PageRank algorithm.
And they used that algorithm to indeed build
a very novel way of searching the web.
Gomes: What was happening at that point was
there was this huge explosion of content in the web,
a bigger explosion of information
than had ever happened before.
And it was getting increasingly hard to find
the piece of content you wanted.
"Adwords"
Mayer: In the beginning,
we didn't have any advertisements at all.
And as we went to add advertisements,
it was very important to us that those ads be as relevant
to the search as the search results themselves.
It was also very important to us that they be distinguished
from the search results.
Gomes: There was a clear separation between ads
and Search from the very earliest times.
Search had one goal and one goal alone,
to provide the most relevant information for the user
in the fastest time possible.
"Universal Results"
Mayer: In 1999 and 2000, we had a search engine
that worked wonderfully,
and it worked wonderfully for web pages.
One of the things we saw was,
as Google got better and better,
users expected more and more from it.
They didn't want just web pages.
They wanted the best possible information available,
be that a picture or a book.
And so we started looking at how we could search new
and other forms of content.
And Image Search was the first of those
because we know that a picture is worth 1,000 words,
and there were a lot of times when people would say,
you know, what is turquoise?
You know, we got a search, "what is turquoise?"
And there's no way to answer that question
without a picture.
Singhal: When September 11th happened,
we as Google were failing our users.
Our users were searching for "New York Twin Towers,"
and our results had nothing relevant,
nothing related to the sad events of the day
because our index was crawled a month earlier,
and, of course, there was no news in that index.
So we placed links to all the news organizations like CNN
right on our front page saying please visit those sites
to get the news of the day,
because our search is failing you.
My friend Krishna and I were attending a conference
at the time, and Krishna started thinking about the problem,
saying, "If we could crawl news quickly,
"and we can provide multiple points of view
"about the same story to our users,
wouldn't it be amazing?"
That was the birth of Google News
specialized search service.
Mayer: Well, in 2002, one of the trends we started to see
was that the web had become a lot more rich.
More images, more video, different kinds of content.
And we started to realize that our users expected Google
to be able to find something if it existed on the web.
They didn't care if it was text or a web page or news,
they wanted it all in one place.
And so we came up with this notion of Universal Search,
the idea that you could just go to Google,
and no matter what type of content it was,
we could find it.
One of the challenges that came up in Universal Search is that
we were really comparing apples and oranges.
Singhal: You can imagine these apples are web pages,
and you can imagine an orange would be an image.
When we look at ranking images,
we know what the aspect ratio of an image is,
how big is the image, how many pixels this image is.
Is it a black and white image or a color image?
And all these signals are only relevant to images,
but are not relevant to web pages.
And that's why Universal Search was such a hard task
when we did it, because the science was not fully developed.
Mayer: We basically ended up putting things
either on the top of the page, on the bottom of the page,
or somewhere in the middle
because we didn't have a finer-grained way
of looking at the relevance,
especially across different media types.
Singhal: And over the years,
we developed our science tremendously,
and today we are beginning to place
several kinds of information in multiple positions
on our result page
as our algorithms get better and better.
"Quick Answers"
Gomes: Our goal is to make it so that the improvement we make
is so much what you wanted
and fits so cleanly into the flow
of what you are looking for
that you almost don't notice that it's happened.
And looking back at it, it seems obvious that that's the way
it should have always been in the first place.
Menzel: When you do need a specific bit of information,
Google tries to provide you exactly that
using our Quick Answers.
For example, take sport scores.
You kind of want to know what the score is right now.
You want to know how tall is the Empire State Building?
Wright: We want users to come to Google
and get their information as quickly as they possibly can.
And with Instant, you don't even have to type in
your full thought.
You don't have to hit enter.
You can type in something like, "bike h,"
and we'll just show you the results right there
before you've even finished your thoughts.
"The Future of Search"
Menzel: We are pushing the boundaries
of how you actually fundamentally interact
with the search engine itself.
With Search by Image, you can actually use that image
as an input for the search.
Singhal: The truth is that our users need
much more complex answers.
My dream has always been to build the "Star Trek" computer.
And in my ideal world,
I would be able to walk up to a computer and say,
"Hey, what is the best time for me to sow seeds in India,
given that monsoon was early this year?"
And once we can answer that question,
which we don't today,
people will be looking for answers
to even more complex questions.
These are all genuine information needs.
Genuine questions that, if we, Google, can answer,
our users would become more knowledgeable,
and they would be more satisfied in their quest for knowledge.