So, in the post you’re replying to, it’s laid out how insurance wouldn’t work, and your reply is “Have you considered insurance?”
So, in the post you’re replying to, it’s laid out how insurance wouldn’t work, and your reply is “Have you considered insurance?”
Well, given time, prices will move to where the businesses make the most profit. If relationship between price and demand is linear, then an increase in expenses will move the ideal price point by half as much.
Assuming a linear relationship between price and demand, then if you increase the cost of product, the price where the most profit is generated moves by half of this amount.
I suppose that’s true. But it just bothers me when people talk about the market cap like it’s an amount of money that exists somewhere, instead of being an abstract valuation.
Looking at a different example, Ford’s market cap is $42.61e9, and its revenue is $47.81e9, while the profit is $1.83e9, 20 times of which is $36.6e9. If we average both of them we get $42.205e9. So Ford seems to have about the right valuation.
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.
4 hours in, can still read it. Agree with your assessment, too.
That’s a quite thorough debunk. Can you provide some sources for your claims?
It’s sort of a strange approach, because this will leave you with the workers who can’t find employment elsewhere.
Suppliers will charge whatever gives them the highest profit, and if their costs go up by x, said optimal pricepoint goes up by x/2, assuming a linear correlation between price and demand.
So, what do you not like about the Freetube’s UI and UX?
If you spent a year practicing IQ tests, you’ll score a genius IQ, but you won’t be better at anything else.
So you’re a sadist, but you try to convince yourself it’s okay because you only want to torture people you think deserve it. Of course, no one deserves to be tortured.
Yeah, it does. Perfect opsec is impossible even with encryption.
The easiest way to cheat on an IQ test is to simply practice. As far as I know, nobody has yet managed to design an IQ test where you can’t get better with practice.
Wild corn dogs are an outright plague where I live. When I was younger, me and my buddies would lay snares to catch to corn dogs. When we caught one, we’d roast it over a fire to make popcorn. Corn dog cutlets served with popcorn from the same corn dog is popular meal, especially among the less fortunate. Even though some of the affluent consider it the equivalent to eating rat meat. When me pa got me first rifle when I turned 14, I spent a few days just shooting corn dogs.
You need more training material to train a new AI. Once the AI is there, it produce as many pictures as you want. And you can get good results even with models that can be run locally on a regular computer.
That said, it’s misleading and inaccurate to state that neural networks are just statistics. In fact they are substantially more than just advanced statistics. Certainly statistics is a component—but so too is probability, calculus, network/graph theory, linear algebra, not to mention computer science to program, tune, and train and infer them. Information theory (hello, entropy) plays a part sometimes.
What I meant when I said that they are advanced statistics is that that is what they do. I know that a lot of disciplines play a part in creating them. I know it’s incredible complicated, it took me quite a while to wrap my head around what the back-propagation algorithm.
I also know that neural networks can do some really cool stuff. Recognizing tumors, for example. But it’s equally dangerous to overestimate them, so we have to be aware of their limitations.
Edit: All that being said, I do recognize that you have spent much more time learning about and working with neural networks than I have.
Idea: Governments maintain a list of entities that are evading the law like that, and then doesn’t prosecute people who are accused of crimes against such entities. The idea being that if you place yourself outside of the law’s reach, you also place yourself outside of the law’s protection.