Boston holds a special place in my life. When I was starting my senior year of high school, and my brother Max was applying for business school, he was invited to MIT for an interview at Sloan and thought it was a good idea for me to tag along on his visit. I did, and that trip was the trigger that made me consider going to college in the US. Continue reading...
Another year in San Francisco, another Outside Lands. After a few years in SF, I’ve been to several of these festivals, and honestly this year I was less excited than for previous ones. We had purchased the early bird tickets, and were a bit disappointed when the lineup came out. However, being less excited about the concerts meant that we’d spend less time going back and forth in the park, and that we’d be less stressed about what concerts we’d miss because something else had overlapped. As the day got closer, I started looking forward to it more, and once we were at the festival I was glad we had bought the tickets. Continue reading...
This brief explaining and expanding on some of David Glasner’s and Earl Thompson’s ideas on a labor standard is fascinating. If you’re interested in how money and central banking work, you should take a look. Hendrickson argues that instead of having the Fed aim for stable prices and full employment by managing interest rates tied to fiat, we build a set of policies that mix the ideas of the gold standard and the job guarantee that has gained some popularity recently. Essentially, instead of having the dollar trade for a fixed quantity of gold, the Fed would define the dollar as a fixed quantity of labor. This would tie the price level to changes in the real market, outsource monetary policy to the market, and provide the equivalent of a job guarantee to the citizenry. Obviously there are problems with this, such as fungibility (ie, not all hours of labor are equal) but this can be solved with some kind of indexing solution. I’m intrigued, so if you have anything else to read on this topic, I’d love to hear about it.
When so much of our lives is mediated by giant corporations like Apple, Amazon, and Google, how do we deal with our data? Sure, it is behind a password in the cloud, but someone at whichever storage provider you pick has the keys to some of your data, and most if not all your metadata. This is one of the reasons I like working at Apple - I believe in our commitment to privacy, even if it is just a ploy for market differentiation. Ultimately, this means that I trust Apple, and that the engineers who work on these products are doing the right thing. I could also trust Satoshi, or Vitalik, or Linus’ Law but ultimately, I have to trust someone, and hope that they’ve done their homework.
This is a topic I’ve discussed before here, but it’s nice to have some data to back up the story.
People idolize Steve Jobs, and at Apple he is still brought up often. I read this article around the same time that I was reading DFW’s Joseph Frank’s Dostoevsky, where he wrote that “to make someone an icon is to make him an abstraction, and abstractions are incapable of vital communication with living people.” Writing this must have been really tough for Brennan-Jobs, knowing how public it’d be. It is good to remember Jobs’ (very) flawed human side.
I’ve talked about this before, too. Google is pushing SoMa as “The East Cut” on their maps now. I literally spend half my waking hours in this neighborhood and the only times I’ve heard it in conversation were either (a) people making fun of Google, or (b) referring to the uniforms that cleanup crews wear, emblazoned with “The East Cut,” which ends up leading to (a). There is a very Orwellian aspect to this story, and to how the digital world can reshape the physical world.
I’m biased, so not much to say here, other than my full agreement with Noah. This broken city would just finish breaking if the tech industry collapsed.
Another one by Noah. It is very unusual for pundits to go back and revise their commentary, and to retract the data they’ve used to back up their claims. This one deserves applause.
An amazing intimate story involving Morgenstern, Einstein, and of course Gödel, on his naturalization to become a US citizen in 1947. I won’t spoil it.
One of the most fundamental tools for modern software development had a major security hole, and as usual the issue was a human one, not a technical one.
A critique of Morty Shapiro and Gary Saul Morson’s book on the intersection of economics and the humanities. I took their joint class at Northwestern a few years ago, and also thought it was lacking. The reading list was wonderful. It exposed me to many ideas/authors I did not know about, but their debates were disappointing. I hear a lot more Morson than Morty coming through in Hanson’s arguments. Maybe some day I’ll read their book.
The strategy described here makes a lot more sense when talking about high risk assets like venture and crypto, and like most of these rules of thumb it must be suboptimal, but I’ve been thinking about taking this approach for future investments. Dividing assets in three separate chunks to diversify away risk, and still remain exposed to the original theses, seems like a good idea.
I wonder if Chinese newspapers write about the generation of Americans growing up without WeChat and Baidu. Probably not. Cultural relativism is a recurring theme in my life, and this is one of the most glaring examples I’ve seen recently.
The kinds of things that mathematics allow us to do are pretty insane. I spent a few hours trying to wrap my head around the ideas that Vitalik explains in this series, but a lot of it went over my head. Made me want to go back and learn higher level math.
This piece complains that Siri, Alexa, and the rest of the AI assistant pack can’t handle multiple languages. I fundamentally disagree with some of Larkin’s points. It’s a problem I experience often myself as a native Spanish speaker trying to communicate with these standard written english bots, so I totally understand where she’s coming from. However, not even addressing the speech to text part (which is what’s really broken with the accents), there just aren’t as many NLP tools/corpora/tagged datasets in other languages as there are in English. This is in part a historical/path dependence problem, and in part just economics. Can’t go much deeper than that, sadly.
Another one I probably can’t say much about. I am worried about the progress of technology and where this kind of censorship might take us, though.
Our views about ownership, and how radically they have changed in the last 15-20 years is a topic I’ve been reading a lot about recently. Cowen describes a symptom, and says it should cause us worry. His explanation of why this is a problem is flawed though. As a HN commenter mentions: “The problem isn’t that we own less stuff, it’s that the ownership is replaced by a dependency on a handful of corporations which we have no ability to influence or appeal to. The substitution of individual ownership for a communal one in which individuals retain a stake - a real community, or at a larger scale, a democracy - is not inherently bad. The problem with our recent trend is that we aren’t getting communal ownership in return; we’re getting nothing but convenience. […] You’re renting from a centralized company which outsources the generation of actual value to others, and pays them as little as possible. You aren’t shifting your dependence from yourself to a community, but from yourself to a company that wants nothing more than to make money.” A book I read earlier this year, Doctorow’s Information Doesn’t Want to Be Free, discusses this topic in depth, and I’m hoping to write more about it in the future.
A really good refresher on metrics and growth. They don’t say much new, but give a great overview. Don’t miss part two on engagement and retention. Listening to these made me wish I worked on a product where the metrics tracked translated to dollars.
Most people don’t know much about the millions of people who died in China during Mao’s era of collectivization. In this conversation, Dikotter explains some of its history, and explains the many ways in which its policies failed. It reminded me a lot of reading Seeing Like a State, and made me wonder about the relative success of the kibbutz, the analogous Israeli collective farm. I did a bit of research, and probably will not only add Dikotter’s book to my to-do list, but also this one on the Israeli experiment. The problem with listening to EconTalk is that it makes me want to understand the world more, and I can only do that by reading more. Guess that’s a good kind of problem to have.
It’s odd when ideas that sound like conspiracy theories are actually true. Turns out that there is a transnational scheme to subsidize the last-mile shipping of stuff that has moved across borders. This contributes to the skewed cost distribution of last-mile delivery, and affects local businesses where transportation cost represents a significant portion of the price of an item. This seems like a pretty messed up set of incentives waiting to explode in our faces.
People in the US love to talk about how different they are from the rest of the world. It’s inequality is truly exceptional among countries with developed economies, and seems fully self inflicted. As Milanovic notes, given the political environment in this contry, the solution must be multifaceted, with small changes on many dimensions - taxation, education, welfare, healthcare - which will be much easier to swallow individually than a single big change would.
Customers generally drive you to features they have seen elsewhere, not to new original ideas. Focus on the differentiation, and is more likely your company will succeed.
For all the talk going around about conservatives becoming Keynesians, it’s strange how government spending keeps sliding down. It’s easy to forget how much influence military spending had on Silicon Valley’s success, and how we’re still riding the momentum of previous waves of investment. Innovation isn’t free. It must come about from an empowered, educated citizenry, and the government can take part in that. As Manjoo explains, “every key component in a smartphone, from the battery to GPS, is based on research first done for the American government.” It’s time to fund more of these experiments.
What’s most illogical about the stance that Evans rails against here (policies around data that the gov makes inaccessible “for our security”) is that much of this data could be compiled from observation by the public. “X could lead to terrorism” is one of the worst possible arguments against X, ∀X.
The startup market in San Francisco feels less overheated than it was 2-3 years ago, but investors are already hedging theirs bets. The housing crisis is a real issue, and the fact is that lots of people who would like to be here just can’t. Without people, there’s less talent, and with less talent there are less companies. SF might have killed the goose that laid golden eggs.
This was a recommendation from Jon Evans from a very long time ago. I finally got around to it, and it is as good as advertised. It discusses hegemony through language, how we assign authority to individuals and institutions via standardized language, and more. This is a 20k word essay about the dictionary, and how language shapes our thoughts. I enjoyed it so much that decided to buy DFW’s Consider The Lobster and read more of his essays. Reading it in perspective 15+ years after it was written, in our Orwellian political environment made it extra interesting.
I didn’t know that Solem, the creator of Celery, is now working at Robinhood, but having used it for a bunch of things while in college, and then again at my last gig, I’m looking forward to testing out his code. From their docs, “Faust provides both stream processing and event processing, sharing similarity with tools such as Kafka Streams” and it runs modern python (3.6+ only) with RocksDB and uvloop under the hood. This is a project I’m very excited to try out.
By far, the most interesting aspect of this podcast was around the 1hr mark on why mega-corp moving into your niche business is not necessarily a problem, followed by a fascinating discussion of M&A vs buybacks. I had never thought about M&A in that way, but it is interesting to hear the public markets side of the coin after reading so many positive comments about acquisitions from people like Elad Gil and Marc Andreesen about the early startup stage M&A.
San Francisco is a mess. Things could be different.
On a recent article club, we discussed how people of different ages competed on different levels when we we’re kids - think your middle school’s basketball team, which wasn’t playing against high schoolers - and how those cutoffs are somewhat arbitrary. After all, a kid born right after the cutoff will still have an advantage over those kids who were born right before the next cutoff. The last such age-based differentiator happens when people apply to college (which was the context of our conversation), after which these boundaries disappear and competition becomes a free for all. This episode discusses a similar topic, not on age, but on gender, where the divide is a lot less clear.
This was an episode where the research presented little suprise in directionality, but disappointed me with the magnitudes. Alesina and his team study people’s attitude towards immigrants, focusing on legal immigrants only, and the findings are in many ways obvious. On average, people dislike immigrants (suprise!) and assume they are taking away jobs or free-riding on the local welfare programs. On average, people in the US are much more optimistic than they should be about whether a poor person can bootstrap their way out of poverty, while Europeans are much more pessimistic than they should be. What was suprising though, was how far off people’s guesses were against what the metrics really are. People vastly overestimate how many immigrants there are, how many of them are illegal, and how much they take from the welfare systems. This was a somewhat depressing but quite worthwhile conversation to listen to.
This episode has three different parts. They’re all good, but I’m mostly recommending it due to the second one, a conversation about Fritz Haber, questioning whether our good actions can outweigh our bad ones.
I’ve previously shared some of Simon’s work on generative corals. I totally should have looked at his previous work, too. These floorplans are not very efficient, but with the correct set of constraints could lead to better designs that a human would not come up with on their own.
An awesome data visualization of land use across the US. Breaking up the country into quarter million acre squares lets us say a lot about how the US really works, and what people value here.
This essay is full of questions about the philosophy of science vs engineering vs design. It tries to explain where AI fits in, and discusses the false certainty that powerful tools like these give us. Machine learning/artificial intelligence/deep learning/data science/call it what you want is full of pitfalls because it is so powerful. There’s not much actionable in it, but as someone who’s been pushing the story of automated retraining and continuous deployment to squeeze out performance out of ML models, it certainly gave me a lot to think about.
In Seeing Like a State, James C. Scott writes: “By a kind of fiscal Heisenberg principle, tax officials transform that which they take note of.” In this essay, Nielsen shows a few examples of this - from the roofs of Paris, to the facades of Amsterdam.
This article, recommended by Mike Davidson, discusses many ways we could fix journalism. Basing its recommendations on a bunch of communication and psycology research, the author tears apart a bunch of different situations in which the conversatin could have been nudged elsewhere, allowing for more productive outcomes. There’s a lot to unpack, and I was not expecting it to be so long (should’ve noticed the “39 min read” at the top!), but totally worth it. It reminded me of a tweet by Mason Hartman and the ensuing conversation: “When you ask a really useful question, most people will consciously or unconsciously try to determine if they have a cached answer that roughly fits what you asked. Getting people to consistently forget their lines is a skill worth mastering.”
This piece reminded me of Nick Szabo’s things as authorities, and how much of our interactions are intermediated by ideas that are tacitly embedded in culture. Society is built on the fact that we can agree without burning mental cycles on things. We encode accepted behavior in culture and technology, relying on those crystals of knowledge to abstract away complexity and layer even more complexity on top. We offload our question of who should go ahead first to traffic lights, and our questions of who must pay back for their actions to courts and judges. If we think of governments as platforms (an analogy from Tim O’Reilly’s WTF), we can see that government’s role is the construction of and upholding of these mechanisms that legitimize sources of authority. The platform coordinates behavior to reliably improve the relation between the individuals who build on top of it, and it does so by setting the rules of what’s admissible and what is not to the point that we don’t need to stop and think about them.
Also available as a podcast.This is not a new argument from Russ. He posits that our newfound tribalism isn’t all that new, and that it’s simply been exacerbated due to the incentives of the media industry, the filter bubbles of the internet, and the availability of content. He uses restaurants to illustrate the explosion of available choices, and contrasts how this explosion isn’t all that meaningful when choosing what to eat or shopping for shoes, becoming problematic only when there are high externality costs without a feedback mechanism that makes us pay the price from our mistakes. If we buy an uncomfortable pair of shoes, or order a bad plate of pasta, we suffer. Immediately. If we vote for the wrong candidate, our contribution to their election is minuscule, and their actions are diffused over many years - there’s no clear-cut feedback loop. This dynamic means that the ROI on truth isn’t all that high for any one individual, and in aggregate, we end up with a market failure in which media is louder and angrier, as it sells more than nuanced positions would, and each one of us becomes more entrenched in our beliefs, disconnected from each other. Let’s all try to be more nuanced?
Every time one of my friends has asked me what I think of the startup they’re about to join, I’ve said that they should discount the equity as if it were worth $0. The probabilities work out that way, and given that most of them have other offers on the table, its the rational thing to do. Semil’s post discusses the employee side, as well as the early investor’s side - one I had not considered before. If you want to read more on this, Dan Luu’s piece on startup vs. big co tradeoffs is wonderful, pushing the point that all things being equal taking the megacorp offer is a no-brainer for the employee. As someone who wanted to be in startup land and ended up at HugeCo by accident, I mostly agree with him.
Technology does not automatically make the world better. Most tools can be used for both good and bad. The solution to bad outcomes due to technology is not more of the same technology.
What kind of patterns arise if we look at the street grids in various cities? It’s not all orthogonal cross streets. Open Street Map data, and the tooling to manipulate it, seems to have evolved a lot since I looked at it a couple of years ago. Big props to Boeing for open sourcing OSMnx and sharing so much of his work. Maybe it’s time for a side project…
Say what you want about 10X engineers being a fantasy, but I’m convinced Michael Fogleman is one of them just by looking at his open source side projects. Here’s yet another super cool project from him that you should check out.
Value is a mindbending idea once you notice that it’s not tied to price, and that prices themselves are just numbers representing the opportunity cost between various goods. I was surprised there was no mention of supply and demand - this is often overlooked when discussing labor markets (ie, bankers don’t make big salaries because they produce that much value for the companies they work for, but because that’s the price the market bears). Culture might be different at facegoopplemazforce, but even if we’re not measured by “butts in seats” time, people value face time, and track who’s in first, and who leaves last. The input/output problem is pernicious in the org behavior experiences of office life, a la Dilbert. Lastly, the third section in the essay made me think of Russ Roberts’ recurring point that GDP per capita is a bad measure of our standard of living, and that we need to figure out another way to measure our progress. What are some realistic alternatives? Are there any?
I’m still going strong on my quest to fight recency bias by going back to old EconTalk episodes. I’m doing this partially to get away from the current “everything is politics” environment, but also to unlock knowledge that’s trapped in the recent past.
Most good photographs seem inevitable, almost incidental. Each one takes thought and effort. Hearing Sam Abell walk through his process was wonderful. I’d recommend this whether you do photography or not. What a great recommendation from Chris Michel. I took a few notes:
Trade wars are good and easy to win. Really cool economics data viz work from the NY Times, however sad the topic.