Joe Cortright, writing for cityobservatory.org:

But even markets with large amounts of affordable housing demonstrate the contradiction. Since at least the second half of the 20th century, the vast majority of actually affordable housing has been created via “filtering”: that is, the falling relative prices of market-rate housing as it ages, or its neighborhood loses social status, often as a result of racial changes. Low-income affordability, where it does exist, is predicated on large portions of the housing market acting as terrible investments.

Huh? This is only a contradiction if the type of housing remains constant, which it does in zero-development, extreme-construction-cost markets like San Francisco where public policy forbids the modification of (almost) any housing to increase density.

Here’s how it would work otherwise: family buys single family home in year A for $100k. Lives there for a while, then sells in year B for $200k. The buyer is a developer, who then constructs a larger building on that same lot consisting of 4 apartments that now each sell for $100k again. Original family gains in wealth, developer makes tidy profit, new families can still buy a place to live for $100k. All numbers inflation-adjusted, you pick A and B to make whatever return you think is reasonable.

This is how densification happened almost everywhere until zoning laws went crazy mid-century.

Note what you don’t get out of this arrangement: a neighborhood that doesn’t change for 40 years; the ability to live in the same type of house your parents did, in the same neighborhood, for the same price. But you could have the same amount of (indoor) space they did, and outdoor space through public parks and the like.

What’s not sustainable is everyone having a suburban style detached single family home without increasing density in perpetuity. That is what leads to this contradiction.

The non-density alternative is sprawl, where prices rise in long-established neighborhoods, and outlying new developments are where you can buy new houses for less—which is what you observe all over California.

(via news.yc)

Charles Duhigg, writing for the New Yorker:

One day in 2011, a Google executive named Isaac Taylor learned that, while he was on paternity leave, Levandowski had modified the cars’ software so that he could take them on otherwise forbidden routes. A Google executive recalls witnessing Taylor and Levandowski shouting at each other. Levandowski told Taylor that the only way to show him why his approach was necessary was to take a ride together. The men, both still furious, jumped into a self-driving Prius and headed off.

The car went onto a freeway, where it travelled past an on-ramp. According to people with knowledge of events that day, the Prius accidentally boxed in another vehicle, a Camry. A human driver could easily have handled the situation by slowing down and letting the Camry merge into traffic, but Google’s software wasn’t prepared for this scenario. The cars continued speeding down the freeway side by side. The Camry’s driver jerked his car onto the right shoulder. Then, apparently trying to avoid a guardrail, he veered to the left; the Camry pinwheeled across the freeway and into the median. Levandowski, who was acting as the safety driver, swerved hard to avoid colliding with the Camry, causing Taylor to injure his spine so severely that he eventually required multiple surgeries.

The Prius regained control and turned a corner on the freeway, leaving the Camry behind. Levandowski and Taylor didn’t know how badly damaged the Camry was. They didn’t go back to check on the other driver or to see if anyone else had been hurt. Neither they nor other Google executives made inquiries with the authorities. The police were not informed that a self-driving algorithm had contributed to the accident.

Levandowski, rather than being cowed by the incident, later defended it as an invaluable source of data, an opportunity to learn how to avoid similar mistakes. He sent colleagues an e-mail with video of the near-collision. Its subject line was “Prius vs. Camry.” (Google refused to show me a copy of the video or to divulge the exact date and location of the incident.) He remained in his leadership role and continued taking cars on non-official routes.

JFC.

Josh Koppel, on his blog Path-Sensitive:

This, I dub the Partial Control Fallacy. It’s where, if there’s some outcome you want, and you only control a couple factors that affect that outcome, you decide how much to try to improve those factors as if you were actually improving the entire outcome. It’s closely connected to the 80/20 principle: it’s when you only have control over that last 20%, but you pretend it’s the whole thing and work on it accordingly. It’s when the 80/20 principle would suggest doing nothing at all.

It’s very tempting to do “whatever you can” to control the outcome of some process where you have very little control. I’ve certainly been guilty of this!

Losing this mindset has been huge for my personal happiness and professional success.

Tim Babb:

You can use a Kalman filter in any place where you have uncertain information about some dynamic system, and you can make an educated guess about what the system is going to do next. Even if messy reality comes along and interferes with the clean motion you guessed about, the Kalman filter will often do a very good job of figuring out what actually happened. And it can take advantage of correlations between crazy phenomena that you maybe wouldn’t have thought to exploit!

Kalman filters are ideal for systems which are continuously changing. They have the advantage that they are light on memory (they don’t need to keep any history other than the previous state), and they are very fast, making them well suited for real time problems and embedded systems.

Perhaps useful for robots?

(via news.yc)

Holy cow! This blew my mind.

When I first played the sound, in the “middle” position, it sounded so much like “Yanny” that I could not imagine anyone possibly thinking it was “Laurel”. Even as I slid towards Laurel, it still sounded like Yanny, until I finally hit Laurel, almost at the end of the slider.

But then I could slide it almost all the way back to Yanny and still hear Laurel. The same sound sounded different to my brain depending on what I most recently heard. This is clearly a dynamic system.

It’s also clear that the Yanny and Laurel sounds are different frequencies.

I suspect this is a similar phenomenon to the “hello?” phone answer — it exists to prime your brain to understand the voice on the other end of the line. Hearing a particular voice primes you to pick out that voice from the noise. So once I started hearing Laurel, I was primed to hear the Laurel-speaking “voice” in the original sound.

Reminds me also of the McGurk effect.

Charlotte Edmond, writing for the World Economic Forum:

First a drone scans the topography to create a 3D map. Then the most efficient planting pattern for that area is calculated using algorithms.

Wait, how exactly are they finding the most efficient planting pattern?

Oh, right, with algorithms. Obviously.

Snark aside, though, this is a cool project!

Aaron Harris, writing on Y Combinator’s Blog:

This lesson is something I should have been able to absorb much more easily. I had 4 different jobs, and 4 different career paths, in the 10 years after college. I was an investment banker, an analyst at a hedge fund, a founder, and then a partner at YC. Each time I started something new, I expected myself to be immediately great, and was hugely disappointed when it became clear that I was nothing of the sort. Each time I switched jobs and discovered this, I also realized that I’d gotten older, and started to fear that I did not have the time to get great. Maybe I did not even have the time to get good.

Apt.

In New York City the public health commissioner, Royal S. Copeland, eliminated rush hour by staggering shop, school and factory opening times. He was under pressure to close schools, but after infancy children were relatively unaffected by the virus, and Copeland argued that schools could help disseminate health advice to their communities. He opened 150 health centres to deal with the sick, and insisted that all flu patients who lived in shared accommodation be hospitalised. Public health information was distributed by an obliging press: the Italian-language Progresso Italo-Americano sold close to a hundred thousand copies a day in New York alone, and raised funds for an Italian hospital in Brooklyn. Copeland allowed children to go to school, but he banned them from theatres. When Charlie Chaplin’s Shoulder Arms came to New York in October, Harold Edel, the manager of the Strand Theatre, wrote: ‘We think it a most wonderful appreciation of Shoulder Arms that people should veritably take their lives in their hands to see it.’ Edel was dead within a week, of flu.

Terrifying.

(via news.yc)

Sometimes you just need a little perspective.

(via reddit)

Every software engineer should listen to this talk — it contains many brilliant insights into how to structure and create sane interfaces.

Easily one of the most enlightening talks I’ve ever watched.

(via news.yc)