Bezos
Article
Bezos is a recurring person in the Astral Codex Ten archive, appearing 3 times across 3 issues between August 31, 2022 and June 27, 2025. The archive places it in contexts such as “people in some kind of abstract counterfactual competition with Bezos”; “But part of Bezos’ accomplishment was causing this particular slot to exist”; “The majority of Bezos’s wealth is essentially from gambling on Amazon stock”. It most often appears alongside Jeff Bezos, SpaceX, Amazon.
Metadata
- Category: People
- Mention count: 3
- Issue count: 3
- First seen: August 31, 2022
- Last seen: June 27, 2025
Appears In
- Billionaires, Surplus, And Replaceability
- Highlights From The Comments On Billionaire Replaceability
- Your Review: Alpha School
Related Pages
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- Jeff Bezos (3 shared issues)
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- SpaceX (3 shared issues)
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- Amazon (2 shared issues)
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- Bill Gates (2 shared issues)
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- Bryan Caplan (2 shared issues)
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- Florida (2 shared issues)
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- Scott (2 shared issues)
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- 10,000 hour rule (1 shared issues)
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- 2 Hour Learning, Inc (1 shared issues)
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- 2-hour Learning (1 shared issues)
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- Adam Neumann (1 shared issues)
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- Alex Amplifier (1 shared issues)
External Links
Source Context
Recovered passages from the original issue text. When the raw archive preserved outbound links inside the source passage, they are listed directly under the quote.
Suppose Amazon creates $1 trillion in extra value for the world, it gets split 50-50 with consumers, Amazon makes $500 billion, that gets split 50-50 with labor and other stockholders, and Jeff Bezos ends up with $250 billion. The standard argument would say that this is fair compensation for the $1 trillion Amazon provided to the world.
But suppose that we go back in time and prevent Jeff Bezos from ever being born. Does this mean Amazon wouldn’t exist today? Probably not by that name. But does it mean that we wouldn’t be buying things online today? That we would have to walk to the brick-and-mortar store every time we wanted a book? Does it mean that Internet retail would be split across a hundred different storefronts, none of which had a good selection or was easy to use?
It might mean that. But I think “Internet retail giant which dominates the market through economies of scale” is a natural niche which Jeff Bezos won the race to fill. When I say “natural niche”, I don’t want to discount Bezos’ accomplishment - I certainly didn’t notice that niche in 1994, and even if I had, I wouldn’t have had the business acumen to fill it effectively. I just mean that, probably sometime between 1994 and today, someone with business acumen would have noticed that niche and filled it successfully. Maybe not quite as successfully as Bezos. But successfully.
But I also want to make an economic response: I’m not sure “what rewards need to be offered to incentivize people?” is the right question. Suppose Jeff Bezos just really loved founding businesses, and couldn’t imagine working for anyone else, and he would found and run Amazon for $10/day, just enough to live in a tent in one of his warehouses and eat cold beans. Does that mean society would optimally pay him that amount? Maybe this isn’t true because in some kind of hypothetical perfect society, all money would be distributed evenly, so nobody should get less than GDP/population, but sometimes we need to give people more, and we’re just trying to figure out how much more, when?
We can go back further: Jeff Bezos’ parents invested $300,000 in Amazon in 1995; sources say that’s now worth $30 billion. A warehouse worker who got paid in stock that year (this is hypothetical: there were no warehouses or public shares) would now have $3 billion.
Inline links: sources say
How much actual spending power does Jeff Bezos have access to?
They keep the kids motivated so they put in the daily effort and don’t get burned out What Alpha is doing is not rocket science. They are just “following the science” for what has been proven to work, and then designing a school around the best way (or “a way”) to deliver that science - personalized instruction, mastery focus, spaced repetition and incentives. It should not be too surprising that when it all comes together it spits out measurable results. But will it hold? Part Six: A Response to Bryan Caplan "When the data and anecdotes disagree, the anecdotes are usually right. It’s usually not that the data is being miscollected. It’s usually that you’re not measuring the right thing." — Jeff Bezos (on multiple occasions) Not only does Bryan Caplan convincingly argue that education is mostly signalling in his book “The Case Against Education”, he goes even further to pour cold buckets of water on aspirational parents in his book “Selfish Reasons to have more Kids”. In that latter book he makes a compelling case with unimpeachable data that how kids turn out is almost entirely due to their genes plus “non-shared environment” (i.e., random things not having to do with parenting). According to Caplan helicopter-parenting does not hurt your kids, it is just a waste of everyone’s time (and maybe their enjoyment during their childhood). You might be able to influence some of your kids' behavior in the short term, but once they become an adult and move out of your house they will revert to the biases of their genes. As Caplan says, the most important parenting decision you can make that will affect how your kids turn out is your choice of spouse (or more accurately your choice of the genes you use to build your kids). Caplan does put one caveat on his data: range restriction. He admits that all of his adoption studies focus on middle class Americans (and Europeans). He is the first to admit that if you take a baby out of extreme poverty in the developing world and raise him in a middle class American family, he will have better economic outcomes than if you leave him in rural Mauritania (see his “Open Borders” book). He may even grant that moving from the poorest broken families in America to the middle class also may make a difference – since all the data available comes from families who were approved by administrators as acceptable to raise adopted kids. But is the same thing true when you move from the middle of the bell curve to the right? When the Data Set Gets Bigger Raj Chetty’s neighbourhood-impact study cracked the range challenge open. Chetty had access to all IRS filing data for generations. He was able to focus on families with multiple children that moved to significantly different zip codes, and follow those children over extended periods of time. By having millions of data points he could tease apart the impact of moving to a “better” zip code for older vs younger siblings. The younger sibling had the same family environment (and 50% of the same genes), but some number of more years in the “better” neighborhood. Chetty found that better neighborhoods made a difference to long term outcomes. But isn’t the neighborhood where a family lives in a “shared environment”? Clearly some adopted families lived in better neighborhoods than others? Why didn’t Caplan’s adoption studies pick that up? I think part of the answer is noise. Chetty had millions of data points vs hundreds of thousands for the adoption studies. But mostly I think the reason Chetty found this impact while the adoption studies did not is that he was looking for different things. No one took the adoption studies and grouped the zip codes as the relevant input variable. As Bezos says, the data wasn’t miscollected, they were just looking at the wrong things. So what does a good zip code look like? Chetty summarizes a good zip code as: Short commutes