More like a foot fetishist :-p

Not to be mean, but this is a terrible question for this subreddit. You could have just looked it up on wiki dictionary (or any dictionary).

You’re a guy so you can’t technically have a dike. I mean you could but she wouldn’t be into you.

After reading /u/TurboThrobber 's comment:

In German this is more obvious because it's "Pedometer" and "Pädophiler" (ä = ae).

A "Pedophiler" in German would actually have a foot fetish.

It comes from the Greek 'philos' meaning "loving"

Yes

It's used in lots of words, often meaning like or love or interest of some kind. It does't always mean like romantic love; but love of food, or arts, or something like that.

Yes. And phobe is the opposite

Hydrophilic (attracted to water), hydrophobic (repelled by water)

So a pedophile can be a file for your feet? :-)

So then what does phile mean? Attracted?

Oh....I can't ride my dike without my helmet. I Always wear protection.

It’s like carbon dioxide and sodium bicarbonate. Bi and do both mean two in Greek or Latin.

We should start a movement to change bicycle to dicycle. But then it would get shortened to “dike” and that might cause problems.

One is greek and one is latin. I once offered a foot massage to a girl who was not a native English speaker and she asked if I was a pedophile. I assured her I was not. 20 years married now.

There's a similar one with Homo,
Homo - Latin = man
Home - Greek = same

Thank you. It's been bugging me for years.

No, ped- means child in Greek, where as ped- means foot in Latin. Different root words for different subjects.

'ped-' relating to "foot" is from Latin 'pēs', gen. 'pedis'. 'ped-',

'paed-', relating to children is from Ancient Greek 'pais', genitive 'paidos'

The word is actually paedophile but that was too difficult for Americans to spell.

OP's question is specifically about startups, though.

Maybe rare with "startups" but "companies" do pay distributions and dividends to their shareholders. Some companies aren't looking to IPO or have a large exit and are just cash-flow generating machines

It's actually pretty rare for a startup to be turning enough of a profit (or indeed, any at all, although that's changing recently) for investors to make money directly off of dividends. Their money usually comes by selling their share of the company during an acquisition or IPO.

I buy 20% if a company for 1 million dollars. Now the evaluation of the company is 5 million.

The company goes public. It is now selling great in the market and the total evaluation is now 50 million.

If said investor sells all of his stock (20%) to people that want to buy it he now has 10 million. So he made 9 million total.

This is obviously not taking into account things like how him selling all his stock effect price, but we need to make it simple.

In an IPO, the shares that the angel investor owns is now traded publicly. Each share is now worth the open market share price and can be sold for cash.

If the startup is acquired, the amount the purchaser pays is distributed to the existing shareholders (angels, founders etc) according to the portion of shares they own.

Shares represent ownership. The buyer has to pay the owner to purchase. That is the straightforward concept.

Think of a business as an engine that is designed to generate money.

The business plan is the engine's blueprint.

But for the engine to actually run, you have to machine its parts, assemble them, test the engine, and make a few adjustments before it will reliably generate revenue. These require startup capital.

Engines also need fuel (cash). But the idea is that so long as it generates more cash than it consumes, then the engine does its job.

Angel capital is what lets a startup begin building the pieces needed for its money engine to run. Once the engine starts running, cash is diverted back to investors in proportion to what was agreed upon in exchange for their equity.

Even if the business is sold or acquired, the initial investors still retain their share of the business's output.

An acquisition usually means buying the existing shares. Since initial investors got their shares at very low valuation (roughly, "the stock price was low", though the company isn't publicly traded at that stage), a high-value acquisition usually buys shares for much more than the investor paid for them. That means the investor gains money.

The same goes for an IPO. In that case, the stock becomes publicly traded, usually at an initial price far above the valuation per share at the time the investor invested, and the investor can sell their stock for much more than they bought it for.

In broader terms: the investor owns part of the company as part of their investment. If the company becomes worth more, their share also becomes worth more.

All species have their own nutritional needs.

The genetically closer 2 species are, the more similar will be their nutritional needs, but it's still not the same.

Mammals are a large group with very distinct diets, so their nutritional needs are very distinct.

Our nutritional needs are more similar to chimp and primates in general.

All animals need energy (as carbs including fibers for the ones with bacteria that can ferment them, fat and/or proteins) and minerals (including nitrogen for the ones who have bacteria that uses nitrogen to make proteins). The ones that don't have bacteria that produces proteins, must also eat proteins, but they don't need nitrogen outside of the proteins.

Vitamin need aren't shared by all animals.

Imagine you do an experiment. You find somebody from every age from 1 to 100 and you measure their height. Then, you plot these on a graph. Experience tells you that for the first 20 years or so (probably less, but let's roll with it) you get taller and taller. This happens quickly at first, but slows down as you approach 20. Then, your height stays flat for the next 50 years or so, until 70. Then, beyond that, you begin to lose a bit of height. The "line of best fit" of the data you've collected should fit that pattern. It should be a smooth curve that peaks around 20 and plateaus for a while, before gradually dropping at the end.

Say instead you tread your data like a dot-to-dot. You connect 1 to 2 to 3 to 4... with straight lines and sharp corners. This would be overfitting the line. Instead of seeing the whole smooth progression, your line might make you think or heights go up and down constantly. Maybe you happened to pick a tall, early-developing 12 year old and then a short, late-developing 13 year old. The line you've drawn makes it look like we peak at 12, then immediately shrink, before slowly growing again. Perhaps the 50s were all shorter women and the 60s taller men, or maybe they even alternated!

Point is, you're giving too much weight to each individual datapoint rather than to the general trend.

This is similar to overfitting in machine learning. Every part of your training dataset has certain flukes and random features. If you train on too small a set for too much, you end up with a system that is very good at dealing with the training images but not so good at stuff beyond that.