Steve Yegge quits Google in the middle of his speech [OSCON Data 2011]

Anyway...

He starts by talking about how he joined Google because he believed they really wanted to change the world. They are basically the only ones fighting for Net Neutrality, etc. He said Amazon had a similar culture when he was there. He goes on to talk about scaling and how it might be the biggest problem for a lot of companies. Basically, everyone is working on some kind of scaling problem and it's usually for a stupid "cat picture project" (social networking). Later in life, you realize there are more important things (specifically, health related in the video), but it's too late because these tasks require math, stats and domain-specific knowledge. We are mostly lacking the domain-specific knowledge. He talks about how you may wish you could go back in time to tell your younger self to do something more meaningful. He challenges everyone to learn something new and make a difference. With about a minute to go he's puts his money where his mouth is and quits his job.

Having worked in academia, you rapidly appreciate that the people who keep the lights on - administrators, lab techs, librarians - are about the most important people there.

And that system? Depends on taxpayer funding. If you're doing things which are ethical, and you're doing them well, then you're helping cure cancer and all the rest, even if only indirectly. Maybe you could do something more direct; that's your call to make. But don't minimize the impact of doing good work.

Over the past 20 years, we've gone from writing software that runs on a single desktop with a very limited set of data to systems like Amazon and Google that accumulate large sets of data and needed to solve scalability problems. Now that we have all this data available, and the scalability problems are FAR more in hand than they were previously, the ? is what do we do with this data.

There are lots of ways we can use big data to solve real-world problems, but to solve real-world problems requires a degree of fluency in the language of the problem you're trying to solve. Most data-mining knowledge is being used to sell ads or to make it easier to share and find pictures of cats on social networking site, when with a little bit of domain knowledge you could literally change the world by solving a big, data-driven problem. Go do that. Learn on your own time and do something worth doing instead of finding new ways to earn a buck by sharing pictures of cats.

I'm Steve Yegge and I quit.