We may get to a point where they have a hard time distinguishing. Perhaps it can be made in their interest to open the API for everyone (i.e. convince the bean counters)
My understanding is that unchecked wealth only remains that way until its owner acts irrationally on a stock exchange, at which point it is quite rapidly checked and becomes someone else's unchecked wealth.
Which is to say that Elon Musk can inflate any market he wants, but only by losing sums of money that will become increasingly significant as more and more people find out about the free cash giveaway.
There’s no functional difference in how markets work when 99% of wealth is owned by a handful of kings vs 99% of wealth being owned by a handful of oligarchs.
I don't really think so. You just swapped the term king to Oligarchs. In fact the Oligarchs are even worse because people think that they have freedom when they might not in fact have such freedom in the first place.
I don’t have an opinion on if it’s worse or not because some people mistakenly think they are free.
I meant that from the perspective of how market forces play out, hyper concentration of wealth into a few actors looks the same whether the title of the those actors is “king” or “oligarch”.
You start losing the wisdom of the crowds effect the market gives if you have a handful of people making the decisions for the entire market
> Trouble is that, [...], even if they include the charging and refilling bits they can be cheap enough to throw away after use.
Well that is fixable, it's even one of the solutions posited here. Just make them artificially expensive by adding a deposit, which you'll get back when you return it to the shop (instead of throwing it away).
They should really update those links. Could be a coincidence but about half seemed to redirect me to a service that was discontinued or continued under a different name.
Both of these do, in a way. They just differ in which gaussian distribution they're fitting to.
And how I suppose. PCA is effectively moment matching, least squares is max likelihood. These correspond to the two ways of minimizing the Kullback Leibler divergence to or from a gaussian distribution.
Although that likely only lasts until they learn how to block LLMs effectively.
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