Infrastructure: Growth vs Wealth

I’m a big fan of Tyler Cowen’s book Stubborn Attachments and the philosophy that he outlines there. One of the core principles is that economic growth is more important than any random good thing for a society to have, because in the long run a richer society will be able to afford more of the good things, and economic growth compounds, so by optimizing for economic growth you will perform better in the long run anyway. I basically agree with this and only want to ponder about tweaking little details around the edge.

Wealth Plus

Clearly you don’t just want to optimize for plain GDP. There are other things that are valuable. In Stubborn Attachments Cowen’s term for this is “Wealth Plus” - you don’t just count money in the bank, you imagine adding in some term for free time, happy personal relationships, the other good things in life, et cetera.

I think there is another dimension that matters, though. Some economic activity is an end in and of itself. You pay someone to give you a massage. They give you a massage. It feels nice. The end. Versus, some economic activity builds on itself. It creates something either directly or as a byproduct that will make more economic activity possible. Kind of like “infrastructure”. You pay someone to build a bridge, now you have a valuable bridge, but also the existence of this bridge makes more new things possible, even if you charge for the use of the bridge.

Imagine two economies. In economy A the “end goal” economy grows 2% a year and the “infrastructure” economy grows 1% a year. In economy B it’s reversed. You won’t notice immediately, but before long won’t new innovation become fundamentally more possible in economy B?

I feel like normal economists should be analyzing things this way but I can’t really find anything along these lines.

What Counts as “Infrastructure”?

Last summer there were lots of arguments over what counted as infrastructure because there was some bill funding infrastructure and people were fighting about what should go into it. This is related in spirit - what parts of the economy are worth extra investment in? Although, really I don’t want to try to philosophically influence politics. Just too zero-sum. I am interested in this question more because it affects what I would like to be working on, to invest in, or to encourage my kids to get into.

According to my system I am thinking about here, the “infrastructure” parts of the economy are the ones that help other parts of the economy when they get better. Video games are not infrastructure. Cloud services are infrastructure. Those ones are easy.

Recently China has been trying to steer their economy in more particular ways. Read Dan Wang’s 2021 letter if you haven’t. Are they doing it in the right way? In general, Beijing seems to be anti “consumer internet”. But I think a lot of the consumer internet actually should count as infrastructure.

For example, food delivery. To me, food delivery apps seem like great infrastructure. It just saves you time when you can easily get food delivered, instead of picking it up yourself or using some slower, more inefficient delivery method. Anything that saves people time seems like infrastructure - those people will then be able to spend more time doing other things. Like work more. So I think food delivery should count as infrastructure. And personally grocery delivery is one of my favorite technological advances of the past decade.

The same goes for child care. Child care is pretty clearly infrastructure by this definition because it helps people work. It’s easier to get workers if it’s easy for your workers to get child care.

Tougher Questions

Education is an interesting question. I’m not sure what to think of the Chinese crackdown on online education. In theory, education should be infrastructure. When people learn more and become more intelligent, it helps out all sorts of sectors of the economy that depend on intelligent workers. But, maybe in practice some sorts of online education are like a pure game to get a credential, rather than learning something useful.

Is social media infrastructure? It sort of lets you do something, but it isn’t really helping you work. It’s closer to being an addictive waste of time. It’s kind of insufficient to only think of it from an individual’s point of view, though. From an advertiser’s point of view, targeted ads are great infrastructure. They help a lot of businesses get going. It’s tricky, though, because I think the sort of businesses that are most helped by targeted ads are the sort of consumerist businesses that are “not infrastructure” themselves. Like ads for games, clothes, any sort of random item that you consume yourself. This almost hints at a second category - the sort of infrastructure that helps other infrastructure. Shouldn’t that be a better sort of infrastructure to invest in? Yeah, this line of reasoning both makes sense and kind of reminds me of eigenvalues. There should be some “first eigenvector” that defines the optimal type of infrastructure investment. Maybe there’s some normality condition that our economy doesn’t obey, though…

Is cryptocurrency infrastructure? I was excited about working on cryptocurrency application platform stuff, because it seems like infrastructure. Some of the modern trendy crypto things, like NFTs, seem like they are not infrastructure, and I am less into them. A work of art is not infrastructure, blockchain or no blockchain.

Are hedge funds infrastructure? My instinct is no but it probably depends on what exactly they are doing. There are certainly some financial services which make other businesses possible. And there are certainly some financial entities which are just making money via shuffling stuff around cleverly and nothing else really depends on them.

Conclusion

I think people should be proud to work on “infrastructure”. It is underrated because the creators don’t capture all of its indirect benefits.

Resolutions for 2022

Why make New Year’s resolutions? It seems like a cliché that people don’t follow through on them. I think I can do it, though. Let’s jump in.

1. Calorie Counting

I’ve tried a few different diet strategies in the past. I have never really done the mundane thing of counting calories and trying to stick to a certain limit, though. The most success I have had is from doing a low-carb diet. The main problem I have with sticking to a low-carb diet is that I end up eating with other people, like my family, and my kids in particular do not want or seem to need anything like a low-carb diet. So it’s both a huge pain and a huge temptation to be making high-carb food and then not eating it.

As far as I can tell, low-carb diets mostly work by annoying you into eating less. The upside is that they are conceptually simpler to stick with than counting calories. When you count calories you have to constantly do a whole lot of arithmetic. However, I feel like of all people I should be okay with constantly doing a whole lot of arithmetic as a way of life. So, let’s give it a try.

When my diet plans fail, it tends to be after a period of some success. At first things are going well, I have a lot of energy to keep it going, then after a while I lose emotional energy and stop wanting to continue. This is sort of what I am worried about with the calorie counting plan. Hence, this blog post about New Year’s resolutions. I hate admitting failure so if I can work up the emotional energy to quasi-publicly commit to something, it’s like transferring energy into the future via a subconscious emotional battery.

So, this resolution is simply to count calories. I’ve been at it for a day and a half or so. Just using the default iOS health app, I tried some more complicated apps but they all seemed optimized for me to quickly enter the wrong data and to encourage me to engage in complicated retention schemes.

2. Astronomy Publication

Well, if you only know me from this blog and don’t talk to me in person this might seem crazy, but this goal for 2022 is to get my work published in some sort of astronomy journal. I’ve been doing some volunteer work with the Berkeley SETI people and some of it seems pretty promising. I should blog more on this later, I suppose, because I think a lot of the details will be interesting to other programmer types.

Basically, modern astronomy is more and more a “big science” thing. At least for radio astronomy, which is the sub-part of astronomy that I’ve been getting into. There are a few enormous radio telescopes, there are a relatively small number of teams that buy time on these telescopes, and the telescopes create a huge amount of data. The analyses that astronomers could do manually 20 years ago, nowadays require large-scale computer analysis.

My rough take on the field is, the astronomers could use a lot more software engineering support. You have ratios like 10 astronomers to 1 software engineer and it seems like they could use a ratio of 1 astronomer to 10 software engineers. So, that means that the marginal value of software engineering contribution is high.

If you are curious, you can check out turboSETI which I have contributed to a bit - it’s currently the gold standard analysis software for looking through the output of a radio telescope and seeing if there are any “alien-looking” signals. And you can also check out Peti which is an alternative way of doing things (tldr more GPU specific) that I have been working on.

Besides those, I’ve also been working on some “data pipeline” type stuff which isn’t public but is much more of a mundane, well every one in a while we get a petabyte of data from this telescope, let’s make sure all the machines do the various processing we want them to do and that data gets compressed and filtered and analyzed and indexed and stored and cross-analyzed.

So most of this work in radio astronomy isn’t like, a single person thinks hard and creates some theory and publishes it. It’s more like, there’s ten authors and everyone is doing some aspect of making this data analysis work. That’s fine. I just want to get my fingers in there. I need a sub-goal that happens before “finding aliens” because that’s too big a goal to just stick in a New Year’s resolution.

3. Exercise

In 2022 my goal is to work out four times a week. This one feels like a gimme, surprisingly enough, because I’ve been doing this pretty successfully in 2021. The key to making it work is that my wife and I do it together at a regular time; we have an extra room in our basement that we have now filled with some weights and some exercise machines and we go work out at the same time so that one of us can’t weak out without admitting we are skipping to the other.

So, I just think it’s okay to have a resolution that is essentially a “maintainance goal” from the previous year. Diet and exercise things don’t just automatically stay in place, often stuff works for a while and then it stops working. So it really is important and nontrivial to keep this up. So I hereby resolve for it.

4. Blogging

Well, I was going to just have three resolutions. Then I was reading about the Law of Fives and thought how cool it would be to have five resolutions. So I thought for a while and I only really came up with a fourth one. So, fine. My goal for 2022 is to blog at least once a week.

Why? I don’t really want to get attention or page views, per se. It’s more that I think the rigor of writing things down forces me to think harder about things. I usually feel good about writing a blog post once I do it, but I just don’t end up doing it.

This resolution, I feel like it’s the most likely one to fail because I just stop caring about it. But, it’s also the easiest one to just phone it in and take some minimum action to technically achieve it. I find that once I start writing a blog post, though, I usually write a decent amount and think a decent amount about it. So let’s give this a try.

Now what?

I was thinking about a resolution about reading a lot of books. But, I just enjoy doing that. I don’t really need to resolve to read books because I will read books anyway.

When I think about a goal-setting process, the first thing that comes to mind is Facebook corporate goal-setting. Which seemed to work pretty well. So maybe at the end of Q1 I will write a little update about how goal-setting is going. Or maybe at the spring equinox, that’s more how the astronomy world paces itself. Nah… Q1 just feels right. Stay tuned!

The Random Number Generator Hypothesis

Life In A Simulation

Imagine an alien civilization with such advanced technology, they can construct a computer many orders of magnitude more powerful than ours. It’s powerful enough to simulate our entire universe. 10^10^100 operations is easy, for these alien computers.

One of these aliens sits down one day and starts to code. Before they get to the real interesting programming, they’ll have to import some libraries. File formats, network protocols, secure handshakes, cryptographically secure random number generators.

How do these aliens generate random numbers? Like our random number generators, they develop some basic rules to convert one state of computer memory to another, seed it with something like the current time, and run these rules forward a while. In practice, when a set of rules passes a variety of statistical tests, it is deemed “random enough” for practical uses. Eventually you discard the vast majority of the information, and just extract a few bits to use for your random numbers.

Of course, these alien computers are extremely powerful. So powerful, they can easily spare 10^10^50 bits for a random number generator. And these rules for their random number generator… we call them the “laws of physics”.

Long ago, the aliens running our simulation seeded the Big Bang. They’re going to run our universe for a hundred billion years. At the end of it, they’ll count the number of electrons. If it’s an odd number, the output is a one. If it’s an even number, the output is a zero. And there you go. One random bit! Random bits are useful for practical applications, of course. It’s not like our universe is going to waste. There’s a real meaning to it.

Okay, cool story, so what?

Philosophically, the simulation hypothesis suggests that humans are living in a simulation. There’s a simple argument for it: if a civilization creates simulations, then there are more simulations than “natural” civilizations. Therefore any particular civilization is probably in a simulation.

But this doesn’t tell us anything about the nature of the simulation. Think of a scenario like the one I described above as the “random number generator hypothesis” or “RNG hypothesis” - that humans are living in a simulation. But it’s just a random number generator. The creators of the simulation don’t care about us at all. They will never intervene. And there’s no way for us to interact with the outside of the simulation.

I claim that the RNG hypothesis is more likely than a simulation in which the simulators care about any intelligent life in the universe. The argument is simple. Lots of programs need random number generators! But it’s fairly rare to write a simulation that is aimed to simulate some sort of being where you inspect its behavior. If the aliens’ programming behavior is remotely like our own, we are far more likely to be in a random number generator than in the sort of simulation where the simulators are paying any attention.

Does this matter in any way? If the RNG hypothesis is true, it is indistinguishable from a world in which we are not in a simulation, where the laws of physics simply exist and always have existed. So, in a sense the hypothesis is scientifically meaningless.

And that’s my point, really. Whether we are in a simulation or not, it doesn’t mean anything. If we could communicate with the aliens that created our universe, yeah that would mean something. If we could discover useful things about the laws of physics by analogy to the rules of a simulation, yeah that would mean something. But just being in a simulation, by itself, is meaningless. Don’t lose any sleep over it.

Thoughts On AI Risk

There are two ways that people think about AI risk and I am not a big fan of either of them.

One is the “paper clip” scenario. Some group of software engineers is working on AI, and all of a sudden, it works. Boom, there is now a superintelligent AI, it’s so much smarter than people it takes over the world. Now it does whatever it wants, probably some crazy thing like turning the world into paper clips. The solution is to develop better programming methods, so that when you build an all-powerful AGI (artificial general intelligence), it will do good for humanity, rather than turning us all into paper clips.

The other is the “management consultant” method of analyzing risk. You basically list off a bunch of different practical problems with AI that don’t sound like science fiction and think about it the same way that you would think about the risk of currency exchange rate fluctuation. The solution is to run your business in a slightly different way.

I do think that AI has the potential to become smarter than humans, and a world where that happened would be quite unusual, with weird things happening. I don’t think the “management consultant” method is really taking that into account. I don’t believe the scenario where AI basically works, but its impact on the world is no greater than the fax machine’s.

On the other hand, I don’t believe that AI will make a quantum leap to generic superhuman ability. Computers tend to be very good at some things, and very bad at other things. Computers can destroy me at chess, but no robot can come close to my performance at folding laundry. The sort of mastery of the real world required to turn the planet into paper clips is a lot harder than folding laundry.

It’s possible that AI will be superhuman in every way, at some point. But if we go down the path to get there, I think we will first encounter other world events that revolutionize our understanding of what AI is capable of.

The AI Apocalypse

Generic superhuman intelligence is just not necessary for AI to destroy the world. There are several ways for just a superhuman narrow AI to cause an apocalyptic disaster.

How can a superhuman narrow AI cause an apocalyptic disaster? One possibility is via hacking. Imagine an AI that worked like:

• Scan the internet for unprotected systems
• Hack into them
• Whatever you get access to, hold it hostage for money
• Spend that money on more computing power
• Repeat

If the AI gets access to nuclear weapons it can blow up the whole world.

This scenario does not require general artificial intelligence. The AI only needs to be a superhuman hacker. Once it has systems access, it can do the hostage negotiations with the equivalent of 80 IQ.

Another possibility is via real-world violence. Imagine an AI that worked like:

• Build some killer robots
• Capture some people
• Hold it hostage for money
• Spend that money building more killer robots
• Repeat

This seems harder, to me, because it seems harder to build killer robots than to build an AI hacking program. But I could be wrong.

You might wonder why anyone would build such a disastrous AI. At the beginning, it might just be a way for a criminal to make money. Build one of these AIs, hardwire it to send 10% of its take into your account, now you have a plan to make money. One day, the original creator disappears, and the killer robots just keep on going.

It does seem like a dangerous AI it likely to need access to the financial system. Cryptocurrency seems particularly risky here, because an AI can perform crypto transactions just as easily as a human can. Cryptocurrency dark markets could also enable an AI that doesn’t have to do all the hacking itself. Instead, it buys exploits with its earnings.

Don’t Worry About AGI

People worrying about AGI should be good Bayesian reasoners. If hypotheses A and B both imply an apocalypse, but A implies B, then it is more likely that B causes the apocalypse, than that A implies the apocalypse. Superhuman generic intelligence implies superhuman narrow intelligence, so fill in the blanks, A = AGI, B = narrow AI, and worry about the dangers of superhuman narrow intelligence instead.

One problem with dangerous narrow AI is that better AI methods don’t really do anything to help. The problem isn’t AI that was intended to be good and gets out of control of the humans building it. When there’s money to be made, humans will happily build AI that is intended to be evil. In general, AI research is just making this problem worse.

Instead, we should be worrying about the security of the systems that narrow AI would subvert to cause a disaster. Can we make a crypto wallet that is impossible to hack? Can we make it impossible to hack a hospital IT system? To me, research and development here seems underrated.

How To Get Promoted

Recently I read Slava’s post on How to get promoted. I have a lot of respect for Slava, but I don’t agree with this post. So I thought I would share how I think about it.

The Common Mistake

Slava is right about one important thing, that many people in Silicon Valley misunderstand what it takes to get promoted. Many people assume that promotions just come naturally to people who deserve them, and this is incorrect. The mentality here is like

1. Do good work
2. ???
3. Promotion!

To get promoted, you need to figure out Step 2. But how?

“Getting Promoted” Is Passive

I mean this in a linguistic sense! If you think about it as “getting promoted”, you are using the passive voice. You’re omitting information. The laws of nature aren’t promoting you. Some specific person at your company is the most important decisionmaker for your promotion. To get promoted, you need to understand who that decisionmaker is, and what sort of performance they want from you to get a promotion. The mentality here is like

1. Do good work
2. Convince the key decisionmaker that your work deserves a promotion
3. Promotion!

Who is the key decisionmaker? It depends on what your role is. If you’re a software engineer, the key decisionmaker is probably just your manager. Maybe it’s your manager’s manager. If your company is smaller, maybe it’s just the CEO. But if you’re trying to get promoted, you need to figure out who this person is, and what they want.

Dysfunctional Management

If you have a good manager, you can simply ask them. Ask your manager how promotion decisions are made, who the key decisionmakers are, and more specifically ask them what you need to achieve in order to get promoted.

If you have an inexperienced manager, maybe they aren’t able to explain this to you. Or, maybe you just won’t accept what your manager telling you, that you aren’t ready for a promotion because you need to do better work.

Sometimes, it sounds like your manager is asking the impossible of you, in order to get promoted. Sorry! That may or may not be your manager’s fault, or your fault. I don’t know. At least you’re having the conversation.

Sometimes it is impossible for you to get promoted on your current team. You’re a senior engineer, and you want to make staff engineer, but what you’re working on just isn’t important enough to merit a promotion. This isn’t necessarily your manager’s fault, although often a good manager can help you figure out how to navigate this.

If You Only Care About Promotions

So what’s the right strategy for someone who only cares about promotion? Slava’s thoughts:

The winning strategy is to ignore company metrics completely and move between projects every eighteen months so that nobody notices.

Wouldn’t people notice anyway? Rank and file employees will, but not the management. In a fast growing company things change very quickly.

To me, this just sounds like a case of bad management. It’s hard to manage a fast-growing startup, and bad management happens. But you won’t find bad management everywhere. And often, what seems like bad management from afar, is actually decent management grappling with a seemingly impossible problem, once you dig into the details.

Instead, I think the best strategy for someone who only cares about promotion is to do the unsexy work that management thinks is important, but is having a hard time recruiting people for. Everybody wants to work on the VR project. Nobody wants to fix the billing system. Everybody wants to add a new feature to the consumer app. Nobody wants to be responsible for fixing the database service that recently caused a big outage. Work on the important stuff that nobody wants to do.

People who do this are incredibly valuable to an organization, and usually end up rewarded. Part of being a good manager is to figure out who is willing to do the unsexy but critical work, and to reward these people when they succeed at it.

Conclusion

In summary, my career advice for opportunists is to ask your manager what it will take to get promoted, and then do it. If that isn’t working, try working on a project that nobody wants to work on, but management thinks it’s really important. The rituals and management fashions, don’t worry about it. Spend your mental energy on getting stuff done.