jrauser

A followup: The GNU project was born while I was in junior high, gcc started when I was a senior in high school. Linux was started when I was in college.

Stallman, in a very real sense, made my entire career possible. Likely yours too.

Wow, the close of Lessig's introduction is powerful. We have indeed not earned that freedom yet.

> I don’t know Stallman well. I know him well enough to know he is a hard man to like. He is driven, often impatient. His anger can flare at friend as easily as foe.

> He is uncompromising and persistent; patient in both. Yet when our world finally comes to understand the power and danger of code — when it finally sees that code, like laws, or like government, must be transparent to be free—then we will look back at this uncompromising and persistent programmer and recognize the vision he has fought to make real: the vision of a world where freedom and knowledge survives the compiler. And we will come to see that no man, through his deeds or words, has done as much to make possible the freedom that this next society could have.

> We have not earned that freedom yet. We may well fail in securing it. But whether we succeed or fail, in these essays is a picture of what that freedom could be. And in the life that produced these words and works, there is inspiration for anyone who would, like Stallman, fight to create this freedom.

Amazon, as an organization, cares more about thoughtful, evidence-based argument than any company I've ever worked for and, I suspect, any company I will ever work for. Having left Amazon (twice!), this is the thing I miss the most.

The article says that to make more money, FB must "acquire more users and show more advertisements to existing users". There is a third option, which is to show higher efficiency (higher CTR) advertising to existing customers.

This, of course, does not invalidate the main thrust of the article's argument, as the way to increase advertising efficiency is to accumulate and exploit ever more data about its users. Recent events suggest that this is not in users best interest, as FB has proven an untrustworthy custodian of user data.

You could gather empirical data in controlled settings and make a model that relates the things you can measure easily (speed and downward force) to the things you care about (rock distance and control). I don't know for certain, but I'd guess that's what's been done here.

According to http://pulse.ncpolicywatch.org/2017/08/22/analysis-large-eff..., NC's efficiency gap is around -11, while anything in excess of +/- 7 is considered a very large gap, so by the efficiency gap metric NC's map is definitely extreme.

Is it possible that the game isn't zero sum? To lift a phrase from your second paragraph, is it possible that globalism favors wealthy owners of multinationals AND everyone else?

You're right to point out the risks of vast wealth disparities and the corrupting influence of money in politics, but I think that problem needs to be combatted separately, and not by making everyone less well off.

I wrote a talk about this some years ago, "TCP and The Lower Bound of Web Performance." Here's a relatively recent video: https://www.youtube.com/watch?v=C8orjQLacTo

Even more than affecting my ability to achieve other goals, I think it might actually affect my health. After my last talk I tweeted[1]:

"In the days before my recent talk, my resting heart rate was ~50bpm. The morning after, it's ~45bpm. Be kind to your speakers, folks."

Long term low-level stress is pretty bad for you.

[1] https://twitter.com/jrauser/status/867055469700849664

As I wrote elsewhere in this thread, I write talks mainly because I want the finished talk to exist in the world. I think this is the same relationship an artist has with their art.

That said, having given some memorable talks[1] at high-profile conferences probably has helped my career more than a little bit.

[1] https://www.youtube.com/playlist?list=PLv3BG8BSXbeFNfR2Zk4n8...

This is roughly my cycle. I'm finding that step 10 gets stronger and stronger. After my first talk there was no noticeable step 10. Several years and many talks later, I'm currently in step 10 and I think I might really never get to step 11 again.

I write my talks mostly because I want them to exist. Why does an artist make art?

Almost certainly ggplot2 in R.

This is the correct answer. My advice for amazon SDEs is: either your manager puts operational excellence as their top priority or you need to find a new manager.

The most ferociously negative interview feedback I've ever written in my life was for a person who I thought lacked humility. In summation, I believe my exact words were "I don't care if he's God's gift to software engineering, we should not hire him."

:)

My point was not to qualify Jeff as a technical leader (though he is an excellent technical leader, IMO). Rather, my goal was to give people a sense for his leadership style, and what it's like to be in a high level meeting at Amazon.

I'm sorry you find the Rickover memo uncompelling. Speaking as an experienced engineer, I happen think it's among the best pieces of engineering writing ever produced.

This comment inspired me to recount a story from my time at Amazon: https://storify.com/jrauser/on-the-big-rewrite-and-bezos-as-...

I suppose if you've already memorized the arcane syntax of base R's plotting functions, along with a giant laundry list of highly customized visualizations available via libraries, then perhaps ggplot2 really is slower for exploratory plotting. But for anyone coming to R fresh, the expressiveness and coherence of ggplot2's grammar absolutely blows away base R for fast exploratory graphics.

For working data scientists in industry, there is an extremely important middle ground between exploratory plots that only I will ever see, and publication quality plots. The most important plots I make are those that I'll share with a small audience within my company. These need to be clear and aesthetically pleasing, but not polished to an extreme degree. Again, ggplot2 excels in this regime.

For more on this idea, have a look at pg's Before the Startup:

"So this is the third counterintuitive thing to remember about startups: starting a startup is where gaming the system stops working."

http://www.paulgraham.com/before.html

I have a talk in which I argue that if you can program, you have a huge advantage in learning statistics because you can simulate random processes and tinker with them to get an intuitive sense of the statistics involved.

At Data Driven NYC: https://www.youtube.com/watch?v=AfSM45ncAT8 Keynote at Strata+Hadoop World 2014: https://www.youtube.com/watch?v=5Dnw46eC-0o