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Collections of Value Investing articles, interviews and videos, especially on Warren Buffett and Charlie Munger and articles from various disciplines to build "Latticework of Mental Models"
Monday, August 01, 2011
In The Plex by Steven Levy
Below are some interesting quotes from "In The Plex" book, written by Steven Levy. Great read. A must-read book for those who own Google and also for people who want to understand about online/internet companies.
In The Plex
by Steven Levy
What I discovered was a company exulting in creative disorganization,
general principle that everyone should think big and then make big things happen. He believed that the only true failure was not attempting the audacious. “Even if you fail at your ambitious thing, it’s very hard to fail completely,” he says. “That’s the thing that people don’t get.”
But those who spent time talking to Larry and Sergey knew that there was something special about them and their company. The two founders had already sketched a road map that struck observers as ludicrously grandiose. But their determination and confidence when they explained their vision imbued an almost hypnotic plausibility into their wild expectations.
The OKR embodied ambition. “It sanctions the ability to take risks,” says Doerr. Even worse than failing to make an OKR was exceeding the standard by a large measure; it implied that an employee had sandbagged it, played it safe, thought small. Google had no place for an audacity-challenged person whose grasp exceeded his reach.
huge data centers spread around the world, costing more than a billion dollars each,
(According to an industry observer, Data Center Knowledge, there were twenty-four major facilities by 2009, a number Google didn’t confirm or dispute.)
Google would not say how many servers it had in those centers. (Google did, however, eventually say that it is the largest computer manufacturer in the world—making its own servers requires it to build more units every year than the industry giants HP, Dell, and Lenovo.
“We owned the fiber. It was ours. Pushing the traffic was nothing,” says Sacca. How much fiber did Google own? “More than anyone else on the planet.”
According to Sacca, the shell cost about $50 million, but its contents were valued close to a billion dollars. There was more than 200,000 square feet of space for the servers and infrastructure and another 18,000-square-foot building for cooling towers. In addition, there was a 20,000-square-foot administration building that included a Google-esque cafeteria and a dormitory-style building almost as large for transient workers. The exterior gave no clue about its contents.
Forty-five containers, each holding 1,160 servers, are arranged in a two-story setup. The cold aisles on those buildings ran at 81 degrees.
“We had written enough scripts and basic infrastructure so that the data centers all over the world could be run from Mountain View,” says Jim Reese. “It didn’t matter whether you have 500 or 500,000 computers—you could run them remotely. We designed it for scale. We need physical hands only to get computers in place and replace the hard drives and motherboards when they fail. Even at the point where we had 50,000 computers, there were maybe six of us maintaining them.”
Credit Suisse in April 2009 calculated that YouTube was spending more than $350 million a year to stream an estimated 75 billion video plays to users. Google would privately tell journalists that those guesses were based on what others had to pay to move such massive numbers of bits. With its superefficient cloud infrastructure and its private fiber-optic network, Google’s costs were less, much less. (Exactly how much less, the company wasn’t saying, but Ramp-Rate, another company conversant with infrastructure costs, made its own assessment of $83 million.)
How many books were ever printed? Around 30 million? Even if the cost was $10 a book, the price tag would only be $300 million.
Since its earliest days, Brin and Page have been consistent in framing Google as an artificial intelligence company—one that gathers massive amounts of data and processes that information with learning algorithms to create a machinelike intelligence that augments the collective brain of humanity.
“I just feel like people aren’t working enough on impactful things,” he said. “People are really afraid of failure on things, and so it’s hard for them to do ambitious stuff. And also, they don’t realize the power of technological solutions to things, especially computers.”