Every activity had an underlying purpose to increase the participants’ understanding of a technology or business issue, or make them more (in the parlance of the company) “Googley.”

Larry Page’s PageRank was powerful because it cleverly analyzed those links and assigned a number to them, a metric on a scale of 1 to 10, that allowed you to see the page’s prominence in comparison to every other page on the web.

was pretty clear to everyone who saw this demo that this was a very good, very powerful way to order things.”

“He was brilliant,”

At that point the engine needs some help to figure out how to rank those pages. So it looks for signals—traits that can help the engine figure out which pages will satisfy the query.

A bedrock principle of Google was serving its users—but a goal was building a giant artificial intelligence learning machine that would bring uncertain consequences to the way all of us live.

long term. There would eventually be a joke among Googlers that Page “went to the future and came back to tell us about it.”

‘Wow, the big problem here is not annotation. We should now use it not just for ranking annotations, but for ranking searches.’”

So the problem became finding the right data to determine whose comments were more trustworthy, or interesting, than others. Page realized that such data already existed and no one else was really using it. He asked Brin, “Why don’t we use the links on the web to do that?”