“Oh, people can come up with statistics to prove anything, Kent. 14% of people know that.”
-Homer Simpson

Is that intended as a legal or moral position?

As far as I know, the law doesn’t care much if you make money off of IP violations. There are many cases of individuals getting hefty fines for both the personal use and free distribution of IP. I think if there is commercial use of IP the profits are forfeit to the IP holder. I’m not a lawyer though, so don’t bank on that.

There’s still the initial question too. At present, we let the courts decide if the usage, whether profitable or not, meets the standard of IP violation. Artists routinely take inspiration from one another and sometimes they take it too far. Why should we assume that AI automatically takes it too far and always meets the standard of IP violation?

Yes but there’s a threshold of how much you need to copy before it’s an IP violation.

Copying a single word is usually only enough if it’s a neologism.
Two matching words in a row usually isn’t enough either.
At some point it is enough though and it’s not clear what that point is.

On the other hand it can still be considered an IP violation if there are no exact word matches but it seems sufficiently similar.

Until now we’ve basically asked courts to step in and decide where the line should be on a case by case basis.

We never set the level of allowable copying to 0, we set it to “reasonable”. In theory it’s supposed to be at a level that’s sufficient to, “promote the Progress of Science and useful Arts, by securing for limited Times to Authors and Inventors the exclusive Right to their respective Writings and Discoveries.” (US Constitution, Article I, Section 8, Clause 8).

Why is it that with AI we take the extreme position of thinking that an AI that makes use of any information from humans should automatically be considered to be in violation of IP law?

Yeah. Even 6 year olds know their Lego houses will fall apart if they don’t interleave the bricks.

If a cop just acts like some random “guy with a gun” who might shoot you at the slightest provocation they probably shouldn’t have a gun.
Or be a cop.
An honest cop should be keeping a close eye on that guy.

I’m not talking about any particular language.

Modern programming languages are as complex as natural languages. They have sophisticated and flexible grammars. They have huge vocabularies. They’re rich enough that individual projects will have a particular “style”. Programming languages tend to emphasize the imperative and the interrogative over the indicative but they’re all there.

Most programming languages have a few common elements:
Some way to remember things
Some way to repeat sets of instructions
Some way to tell the user what it’s done
Some way to make decisions (ie if X then do Y)

Programmers mix and match those and, depending on the skill of the people involved, end up with Shakespear, Bulwer-Lytton, or something in between.

The essence of programming is to arrange those elements into a configuration that does something useful for you. It’s going to be hard to know what kinds of useful things you can do if you’re completely fresh to the field.

Python and Javascript are great. The main reasons I wouldn’t recommend them for an absolute beginner is that it takes some time to set up and, even after that, there’s a bit of a curve before you can do something interesting.
If they go and change configuration settings in an app, they’re learning to manipulate variables.
If they click a “do this N times” they’ve learned to create a loop.
etc.

I’d actually start by playing around with the automation and customization functionality you already have. Learn to set email sorting filters, get some cool browser extensions and configure them, maybe even start by customizing your windows preferences or making some red stone stuff in Minecraft.

Computers are just tools. Programs are just stuff you tell a computer to do over and over again. All the fancy programming languages give you really good control over how you talk to a computer but I’d start with the computer equivalent of “Me Tarzan, you Jane.”

Insurance can work just fine for things like hurricanes. Insurance companies have several methods to address it. They’re all effectively variations of buying insurance policies themselves.

Re-insurance pools are a close analog. It’s basically a bunch of insurance companies from around the planet getting together and agreeing to pool risks. Big companies also use a bunch of funky financial instruments to simulate insurance.

There’s some risk of increased systemic correlation (eg climate change may increase the risk that major hurricanes hit multiple areas around the planet simultaneously). That’s largely mitigated in that we can see it coming. Climate change is pretty prominent in their models and they can adjust premiums or stop offering policies, over time.

The bigger risk is in synthetic systemic risk. It’s burned us a bunch of times already and it’s gonna do it again. Those giant global re-insurance pools are almost certainly fine, and worth the risk, if we just use them for their intended purpose. But history shows that we’ll end up creating derivatives contracts on them and those contracts will get leveraged. Those leveraged pools end up merging and turning into giant financial time bombs.

Debt is likely less of an issue here. These are PhDs and they tend to be funded by grants. Students typically pay no tuition and get some stipend for expenses.

Of course, graduating debt free with a PhD in molecular biology from a top program is less exciting when you can’t land a single interview for a junior faculty role.

Industry may pay twice as much but if you love research and China offers you lab space, you’ll consider it.

I think it’s primarily two things.

China now graduates almost twice as many STEM PhDs as the US does. A lot of people move after their PhD but they tend to stay in country.

I also think, anecdotally, that new PhDs have a harder time finding a job here.

Overall China just seems to make more effort to attract scientists. They promise, and deliver, the two things scientists care about, funding and academic freedom.

There’s a bigger picture at play too. China has been making itself attractive for researchers in general. It’s not just Chinese scientists moving back. An increasing number of other scientists are choosing to work in China over the U.S.

In fields where China was pushing it earlier we’re starting to see the results already. There are several fields where a plurality of top tier publications come from China.

This has been going on for much longer than Starlink.

There were a number of observatories built in or near cities. They became mostly useless once we figured out electric lights but we still use them for education sometimes.

SpaceX has been working with the NSF so they can continue to dim Starlink https://spacenews.com/nsf-and-spacex-reach-agreement-to-reduce-starlink-effects-on-astronomy/

Now we’re putting more and more observation capabilities deep into space. JWT is already getting images better than anything you could get on earth, even if you eliminated Starlink and turned off every light on the planet. Ground based astronomical observation is still relevant but we keep coming up with better alternatives.

Adding some detail. Evaporating water takes way more energy than just heating it up.
When you put energy (heat) into water that’s below 100c it gets hotter. When you add 4,184 to a liter of water the temperature goes up by 1c. If the water is already at 100c it takes 2,260,000 to turn that into 100c steam. The energy that goes into turning water into steam isn’t going into the steak.
So if you put a wet steak on the grill it will create an insulating layer of steam that keeps the steak at around 100c (even if the pan is above 100c).
That’s also why you only salt your steak right before or after heating it. If you let salt sit on the steak it will draw out moisture, reducing the Maillard reaction and drying out the steak.

For a great practical way to grill the steak perfectly, check out videos on “cold searing”.