Welcome to the home of Noah Brier. I'm the co-founder of Variance and general internet tinkerer. Most of my writing these days is happening over at Why is this interesting?, a daily email full of interesting stuff. This site has been around since 2004. Feel free to get in touch. Good places to get started are my Framework of the Day posts or my favorite books and podcasts. Get in touch.

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Remainders: From the aesthetic of Kubrick to the advocacy of Heston

Annnnnd here’s my 10th blog post of the month. Hit my goal. (Might even make it to 11 if I have a burst of inspiration.) Thanks again for reading and encouragement. I’m going for 10 again in May. As usual, feedback welcome and you can subscribe by email here (for those of you reading this via email, thanks and sorry about the wasted words, it just emails exactly what I put on the web).

It’s time for another Remainders. This is my chance to share all the stuff I didn’t get a chance to blog about this week. As for me, I’ve been back and forth from San Francisco again. I wrote one long pieces this week on satisficing and the two strategies of marketing. On the reading front I finished up Artemis, which was easy, but nowhere near as good as The Martian. New book is the Master Algorithm, which is all about the different approaches to machine learning. It’s a bit painful at times, but I’m almost to the other side. If you’re interested in machine learning I’d highly recommend this post from Andrej Karpathy on Recurrent Neural Networks.

Okay, onto the links …

By far the best thing I read this week was the New York Times Magazine story “Why America’s Black Mothers and Babies Are in a Life-or-Death Crisis.” It’s troubling and heartbreaking and shocking. Here’s one small bit:

Black infants in America are now more than twice as likely to die as white infants — 11.3 per 1,000 black babies, compared with 4.9 per 1,000 white babies, according to the most recent government data — a racial disparity that is actually wider than in 1850, 15 years before the end of slavery, when most black women were considered chattel. In one year, that racial gap adds up to more than 4,000 lost black babies. Education and income offer little protection. In fact, a black woman with an advanced degree is more likely to lose her baby than a white woman with less than an eighth-grade education.

Skip the time you’d spend reading the rest of my links and go read the whole article. When you’re done, go donate to the Birthmark Doulas.

Good piece from Felix Salmon on why congestion pricing won’t happen anytime soon in NYC (the gist: to do it right you’d have to lower the tolls on the bridges, but that won’t happen because the Verrazano raked in $417 million in 2017). Felix also had a nice Slate Money episode on brands.

The New Yorker on how Kubrick got the aesthetic of 2001 right:

By rendering a not-too-distant future, Kubrick set himself up for a test: thirty-three years later, his audiences would still be around to grade his predictions. Part of his genius was that he understood how to rig the results. Many elements from his set designs were contributions from major brands—Whirlpool, Macy’s, DuPont, Parker Pens, Nikon—which quickly cashed in on their big-screen exposure. If 2001 the year looked like “2001” the movie, it was partly because the film’s imaginary design trends were made real.

Wired on whether two-factor authentication codes are really random. Answer: They are, but we’re wired to see patterns in things.

Emily Nussbaum is the best TV writer working right now. Here she is on the Roseanne reboot:

The show offers a clever finger trap for critics. Call a hit dangerous and you imply that it’s really quite sexy. And, in fact, the seventh episode, which I won’t spoil, pulls a daring switcheroo, one that may offer a new lens through which to interpret Roseanne’s behavior. It’s not enough. The reboot nods at complexity without delivering—there are good people on many sides, on many sides. If you squint, you might see the show’s true hero as Darlene (Sara Gilbert), a broke single mom forced to move in with that charismatic bully Roseanne. But, if that were so, we might understand Darlene’s politics, too. We’d more fully feel her pain and also that of her two kids, transplanted to a place they find foreign and unwelcoming.

This story about a bot Instagram influencer is the weirdest thing I read this week.

Two Japanese words I learned this week:

  • Tsudonku: “Acquiring reading materials but letting them pile up in one’s home without reading them.”
  • Genchi Genbutsu: “This is a Japanese phrase meaning ‘go and see for yourself’, which is a central pillar of the Toyota Way, the famous management system adopted by the Japanese car company.”

An interesting critique of AI from an article about Zuckerberg and techno-optimism:

This is where the promise of artificial intelligence breaks down. At its heart is an assumption that historical patterns can reliably predict future norms. But the past—even the very recent past—is full of words and ideas that many of us now find repugnant. No system is deft enough to respond to the rapidly changing varieties of cultural expression in a single language, let alone a hundred. Slang is fleeting yet powerful; irony is hard enough for some people to read. If we rely on A.I. to write our rules of conduct, we risk favoring those rules over our own creativity. What’s more, we hand the policing of our discourse over to the people who set the system in motion in the first place, with all their biases and blind spots embedded in the code. Questions about what sorts of expressions are harmful to ourselves or others are difficult. We should not pretend that they will get easier.

Rukmini Callimachi wrote that great Isis piece from a few weeks ago, here she is with a Twitter thread on the latest announcement from the Isis spokesman.

I liked this definition of speed versus velocity from Farnam Street: “Speed doesn’t care if you are moving toward your goals or not. Velocity, on the other hand, measures displacement over time. To have velocity, you need to be moving toward your goal.”

Fact of the week: “More Americans work in museums than work in coal.” (The whole article on the real America is worth reading and was written by Rebecca Solnit who also wrote “The Loneliness of Donald Trump,” one of my favorite pieces of writing from last year.)

Amazon released an Echo update that encourages kids to say “please” to Alexa.

If you didn’t see Lebron dominate the end of the Cavs/Pacers playoff game on Wednesday night, here’s the last two plays: A block and a three. The guy is amazing.

On the other end of the sporting spectrum, the Times got a hold of tapes from a meeting between players and owners and I can’t imagine it making the NFL look worse. Here’s a small example from Buffalo Bills owner Terry Pegula: “For years we’ve watched the National Rifle Association use Charlton Heston as a figurehead … We need a spokesman.” These guys are such bad news.

Last, but not least, I had no idea radio buttons were … radio buttons.

That’s it for this week. As usual, let me know what I’ve missed and thanks for reading. Have a great weekend.

April 27, 2018 // This post is about: , , , , , , , , , , , , , , , ,

Why Coke Cost a Nickel for 70 Years Video Style

I’ve set a reasonably modest goal for myself of writing 10 blog posts in April. Let’s see if I can get back on this bike (since I really miss it). This is post number 1.

One of my favorite Planet Money episodes (and maybe favorite podcast episodes period) is about why, despite everything we know about economics, Coke stayed five cents for 70 years. I wrote about it back in 2012 and just a few years ago Planet Money did a 3:45 video version of the episode.

April 2, 2018 // This post is about: , , , , ,

Subway Uncertainty vs Coconut Uncertainty

From the MITSloan Management Review article on “Why Forecasts Fail” (2010) comes this nice little explanation of the different kinds of uncertainty you can face in forecasts (and elsewhere). There is subway uncertainty, which assumes a relatively narrow window of uncertainty. It’s called subway uncertainty because even on the worst day, your subway voyage almost definitely won’t take you more than say 30 minutes more than your plan (even if you are trying to navigate rush hour L trains). On the other end, there’s coconut uncertainty, which is a way to account for relatively common uncommon experiences (if that makes any sense). Here’s how the article explains the difference:

In technical terms, coconut uncertainty can’t be modeled statistically using, say, the normal distribution. That’s because there are more rare and unexpected events than, well, you’d expect. In addition, there’s no regularity in the occurrence of coconuts that can be modeled. And we’re not just talking about Taleb’s “black swans” — truly bizarre events that we couldn’t have imagined. There are also bubbles, recessions and financial crises, which may not occur often but do repeat at infrequent and irregular intervals. Coconuts, in our view, are less rare than you’d think. They don’t need to be big and hairy and come from space. They can also be small and prickly and occur without warning. Coconuts can even be positive: an inheritance from a long-lost relative, a lottery win or a yachting invitation from a rich client.

Knowing which one you’re working with and accounting for both is ultimately how you build a good forecast.

Also from the article is a great story into some research around the efficacy of simple versus complex models. A research in the 1970s collected a whole bunch of forecasts and compared how close they were to reality assuming that the more complex the model was, the more accurate it would be. The results, in the end, showed exactly the opposite, it’s the simpler models that outperformed. Here’s the statisticians attempt to explain the findings:

His rationale: Complex models try to find nonexistent patterns in past data; simple models ignore such “patterns” and just extrapolate trends. The professor also went on to repeat the “forecasting with hindsight” experiment many times over the years, using increasingly large sets of data and more powerful computers.ii But the same empirical truth came back each time: Simple statistical models are better at forecasting than complex ones.

January 6, 2016 // This post is about: , , ,

Basketball versus Business

And I’m back …

Thought this was a really interesting comment from ESPN’s Ryen Russillo during the Grantland Basketball Hour in December. He was talking about the moves by Sacramento Kings owner Vivek Ranadivé (also known for Gladwell’s writeup of his all press all the time approach to his daughter’s basketball team) and generally what it’s like for these guys who have made a lot of money in the business world coming into sports.

New owners can’t help themselves because you think about how successful these guys are at amassing their wealth. They go, “I’m the man, and now I’ll just buy a team, I’ll apply the same analytics, the same principles … I’ll just go win.” But the model in business allows many companies to be successful, the model in sports only allows one.

I never really thought about it like that, but it’s true. Although many think of business as being zero sum, it isn’t really, especially in the world of technology where people are bound to use multiple devices and applications (that’s not to say within a specific category it can’t be zero sum). Sports is different in that there is only one winner. Of course the counter-argument here is that something can’t really be zero sum when everyone gets rich, but it’s interesting to consider nonetheless.

January 6, 2015 // This post is about: , , ,

Meeting Rules at Percolate

This Tweet/post of mine really blew up and I thought I would share it here as well. When we first started Percolate I wanted to make sure that we didn’t become a company that became taken over by meetings as we grew. To that end I set a few simple rules in place, most important of which was that no phones or computers were allowed in meetings. Below are the rules or you can check out the whole post at the Percolate blog.

June 13, 2014 // This post is about: , , , ,