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Social status is a big part of what makes a person attractive especially if you're a man.


Sure, but - by definition - half the population is below average social status. At least here in the US, those people are still partnering up.


Oh, you forget - we lie about social status, including to ourselves. Women and men. And as for what determines status ... first rule of social interaction: you can't ask a woman her age and you can't ask a man his wage (in other words: humans are social animals and this information is only available through playing the social game of deception).

So in practice 80% or so of the population is below "average social status". People who don't absolutely need to pair up (historically women can't earn, but require, money and men can't take care of a home/place to sleep, but have to), will refuse to pair up with someone below their signaled social status. In other words: there are TWO average social statuses. First, there is what people believe their own social status is. Second there is what people, on average, see as others social status.

In a "natural" human society, it's basically impossible for anyone over 25 or so to "pair up", unless they have a partner, which is not common at all. Since social status ALSO determines the distribution of food, at that point the first real period of weakness (you get sick, you hurt your leg, you ...) is the end. You can delay this by forming cliques, but not by that much.

Oh and of course, that has an analog in our society. Look how much a plumber gets paid (ie. it's pretty disappointing), despite the shortage. There are low status and high status jobs, and even where it doesn't make sense they determine pay. E.g. there are a lot of cities with a total glut of lawyers ... it makes no sense to give 7 figure wages for people when 70% of whom can't find work, but we do. By contrast there is an incredible shortage of construction workers, and still they're not paid half what a lawyer gets. Rather we'll get immigrants to do it. Why? Because a great many people would rather signal that they're above manual labor than get 7 figures a year.

In other words: I will live in destitution rather than admit I'm low social status, even if low social status would pay well.

Oh and don't forget credit cards: 80%+ of people worldwide consider feeling rich (and showing off) more important than, ironically, money. Note also the many complaints about the economy, which are never about having or not having money, the big complaint seen everywhere is that people who don't have money "feel poor". One might think it should be perfectly normal to not have money and feel poor.

Which also is the big lesson in investment that's coming up: countries will raise inflation to any level rather than cut expenditures. That's how we got to 20% inflation in the 80s. That's how Argentina or even Zimbabwe got there. Ie: when we're getting close to that point, for the love of God, don't buy government bonds.

Preventing obvious human habits from destroying us seems to me the best reason to really give developing AI your best effort. Because the whole "job destruction" argument has a hole in it you could fit a planet through: people don't want to do the destroyed jobs. What do you think is the best: AI taking jobs? Or, that we force young people into nursing, plumbing, construction, ... through more and more extreme measures and making everyone a lot poorer? That's how the system rebalances after all, make people poorer until the plumbing gets done.

Those are the choices. AI it is. At least for me.


> Bayesian inference assumes the observed data are fixed and aims to quantify the evidentiary support for all possible levels of treatment effectiveness based on the data at hand.

The problem with this approach is that we can only observe ONE level of treatment effectiveness, i.e., the level of treatment effectiveness that the treatment actually possesses. All other possible levels of effectiveness are entirely hypothetical. There's no data about all these other possible levels of effectiveness because they don't occur in reality. So the data cannot possibly tell you anything about how likely is the observed outcome, because the observed outcome is the only outcome that you observe. I

This criticism was made over 100 years ago, and Bayesians still don't have an answer. They just keep going as if nothing happened, but the reality is their methodology is utterly and fatally flawed.


> So the data cannot possibly tell you anything about how likely is the observed outcome, because the observed outcome is the only outcome that you observe.

This could also be viewed as supporting the Bayesian perspective, where the observed data are not viewed as random variables - they are fixed. This is because, as you say, the observed outcome is the only outcome that you observe. It is the classical setting, in comparison, where we instead do our analysis by treating the sample as a random variable, placing the counterfactual on other non-observed values ("what if I had drawn a different sample?"), even though we didn't. Bayesian methods treat the data as gospel truth, and place the counterfactual on the different parameters ("what if the population were different?"), even though it isn't.

The other criticism you have is

> The problem with this approach is that we can only observe ONE level of treatment effectiveness, i.e., the level of treatment effectiveness that the treatment actually possesses. All other possible levels of effectiveness are entirely hypothetical.

This is true of both Bayesian and classical methods. We build models that would explain how different hypothetical levels of effectiveness would affect what data we should expect to see - that is the whole point. Classical methods also involve exploring scenarios in which purely hypothetical values of the parameter may be potentially true, and characterizing counterfactual samples that could have been drawn from them, even though in real life they couldn't have been.


Statistical inference is based on random sampling. The data has to be random, otherwise it doesn't work.

I wrote another comment here clarifying my point, if you're interested: https://news.ycombinator.com/item?id=47566033


It’s hard to understand what criticism you are making, or what alternative this criticism doesn’t apply to, in contrast. Would you care to elaborate?


Imagine we want to know the ratio of men to women in a particular population. We could count all men and women one by one, but it would take too long, so instead we take a random sample and count the men and women in the sample, and from that we infer the quantity that we want to know. This is statistical inference.

In Bayesian inference, the population ratio is seen as a quantity that can take different values each with a associated probability (i.e. a random variable), and the result of Bayesian inference is an estimate of the probability distribution of the population parameter, in this case the population ratio. Now, in reality the population ratio is a concrete number, say 9-to-10, meaning that there are 9 men for every 10 women in the population. But Bayesians don't care. They'll tell you that the population ratio is a random variable which can take many values, and that the probability that it is equal to 9-to-10 is whatever number between 0 and 100%.

This is nonsense because the population ratio is NOT a random variable. People don't come in and out of existence randomly, right? In a way, they're saying there are infinitely many possible universes, each with a different population ratio, and then they come up with an estimate of the probability that the universe in which the ratio is 9-to-10 has whatever probability of occurring. This is absolutely BIZARRE. (I hope you agree). And it's wrong because it's impossible to know how likely one universe is compared to all other possible universes, since we live in our universe and this is all we can hope to observe.


> In Bayesian statistics, on the other hand, the parameter is not a point but a distribution.

To be more precise, in Bayesian statistics a parameter is random variable. But what does that mean? A parameter is a characteristic of a population (as opposed to a characteristic of a sample, which is called a statistic). A quantity, such as the average cars per household right now. That's a parameter. To think of a parameter as a random variable is like regarding reality as just one realisation of an infinite number of alternate realities that could have been. The problem is we only observe our reality. All the data samples that we can ever study come from this reality. As a result, it's impossible to infer anything about the probability distribution of the parameter. The whole Bayesian approach to statistical inference is nonsensical.


Retained earnings are not taxed per se. A company pays taxes on profits. Whether the profits are distributed to shareholders or retained makes no difference whatsoever as far as taxes are concerned.


They are taxed; they are taxed because they are a subset of profits, which is a taxed category. They are not taxed more than other profits, but that doesn’t mean they’re ’not taxed’.


they are not

retained earnings by definition are the accumulation of net incomes, and net income by definition is post tax

what went into the produce the retained earnings (profit) has been taxed

but the retained earnings themselves are not subject to additional taxation (with a few exceptions)


How does exactly "breaking windows" improve the lives of people?


By creating work that needs to be done, and thus forcing people to start spending.


To bring things back to the original point, there's always a way for health centers to spend money improving patient care. They could hire more nurses and give the existing ones more sleep, for example. In the context of the analogy, a broken window is diverting resources from the broken plumbing and refrigerator motor instead of creating an incentive to spend where none existed.


I can't imagine a situation in which I'd want to explain what I want to do on the command line to an LLM, instead of typing the commands myself.


Use ffmpeg to extract the audio from the first ten seconds of an mp4 file and save it as mp3.


I wish the scroll bar was a little less invisible.


As expected. This is why we don't use nominal dollars for measuring changes in prices over long time periods. It's meaningless.


Assets like gold are also reaching new highs in real terms, which is giving people reason to be skeptical of the adjustments made for inflation.

But really none of it is as objective as it tries to pretend to be.


I think it's just a meaningless sentence.


Why would a stablecoin granting yield keep the banking system from working?


The theory, at least, is that everyone would eventually be incentivized to move deposits out of the banking system and into this.

(I am not sufficiently expert here to comment on the odds of an outcome like that)


Considering that stablecoins don't pay interest to the holder, I don't know why anyone would be incentivised to move their funds into stablecoins.


USDC gets me 4% on Coinbase, and USDB and other Bridge-issued custom stablecoins also give the customer rewards that they can pass onto the holder (thanks to MMF/similar cash equivalents behind the scenes etc).

But yes - this is why banks want to prevent stablecoin issuers from being allowed to grant rewards


If I deposit dollars in a savings account I will get paid interest, but that is different from the dollar itself being an interest-bearing asset. I think the same thing applies to stablecoins. Does USDC pay interest to the holder or do I have to make a USDC deposit at Coinbase in order to get paid interest? Also, banks already offer a ton of products that generate yield. I don't see why a product that seems relatively similar to many products that banks already offer would destroy their business... unless such a product is much better than what banks offer, but that doesn't seem to be the case.


>unless such a product is much better than what banks offer, but that doesn't seem to be the case.

I think you're basically correct here. I think the fear of the banks - and why they are insistent on prohibiting stablecoins from generating yield/interest (via the GENIUS act) - is that that doesn't stay true in the long-term, as stablecoins ascend as a cross-border payment/storage rail.

>Does USDC pay interest to the holder or do I have to make a USDC deposit at Coinbase in order to get paid interest?

I believe USDC from Coinbase is framed as "reward", and is downstream of an agreement Coinbase has with Circle to get that "reward" from Circle for all USDC deposits it holds on platform. Other "rates" you can get on centralized stablecoins tend to be similar AFAICT.


Meanwhile a 4-week T-bill has a 4.16% coupon equivalent with almost no counterparty risk relative to the 4% USDC.

USDC should be paying more than T-bills to compensate for the counterparty risk.


In that case, wouldnt sp500 or vanguard be bigger risks to banks existing?

I think most people think banks make money by holding your money and giving you some interest when they actually make money by bringing money into existance out of nowhere when they issue mortgages.


I don't see why not - I'm sure the banks (or others more expert than me) would argue for stablecoins being somehow distinct in this regard, but yeah don't know why eg. Vanguard wouldn't also be a credible cause of deposit flight.

(I do vaguely remember reading that banks were concerned about people moving to money-market fund products that had bank-like functionality)


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