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Cake day: June 10th, 2023

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  • I think that even if Trump were to win, Musk would loose. Trump seems to loathe Musk, having publicly humiliated Musk before, and then snubbing Twitter after Musk unbanned him, at least for a while. Secondly, Trump has a habit of not paying bills, which probably translates into not returning favors. Trump’s alliance with Musk will end once Musk is no longer useful, which will be once the election is over.

    In fact, Trump winning might be worse for Musk than Harris winning, because the Democrats probably won’t retaliate against him for helping Trump. But Trump, well, for one thing, somebody like Trump might see it as a humiliation that he had to work with Musk. And secondly, electric cars don’t fit into the Republican worldview Trump champions.

    Looking at a larger scope, capital tends to screw themselves over by aligning themselves with authoritarians. It’s easier to hold on to power than it is to seize power, and if all you bring to the table is money, then you won’t be needed once power is seized. Because money is something humans made up to facilitate the exchange of resources and labor.








  • Market Cap of a company is sort of a meaningless number. As in, it’s shares in existence times price per share, which is just another way of saying its the share price. If somebody were to sell $100 Billion worth of Tesla shares, the market price would plummet and he’d not get the $100 Billion the shares were originally worth.

    Of course, a rule of thumb is that a company is worth 20 times it’s annual profit, or its revenue. So, by that valuation, Tesla is worth 28 Billion dollars, or 25.5 Billion dollars if we go by revenue. (I’m surprised that both approaches lead to results so close to each other) Compare with a market cap of 682,47 billion, we can see that Tesla is ridiculously overvalued. So, I guess you should go and buy puts on Tesla. Or sell your shares if you have any.


  • Current neural networks do really fancy statistics. To make the model better, you need to make the statistics more precise. Leading to marginal improvements of accuracy requiring exponentially growing marginal amounts of training data. This leads to exponentially decaying marginal utility coupled with exponentially growing marginal expense. Which quickly becomes unsustainable. Edit: On the plus side, this likely means you won’t have to give up much utility when the market adjusts.