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I'm curious what you want to model; what's an example phenomenon you'd like to be able to demonstrate?

Atmospheric circulation. hadley cell, polar cell, and mid-latitude cells. It would also be interesting to see how new bands would occur if we increased the rotational speed of the earth, thus increasing the strength of the coriolis effect. It would also be neat to draw your own continents and orography and see how that impacts climate. which places become more wet/dry, etc. Change how much long wave radiation is absorbed by the atmosphere as the composition of the atmosphere changes. I'm not interested in actually making weather or climate predictions but using it as a tool to educate people on how the climate works.

Interestingly, most large-scale atmospheric models I know of use a (mostly) incompressble fluid approximation, even though air is obviously compressible at human scales. It just isn't at the flow speeds and length scales of global-scale fluid models. Where compressibility is important for those models is where density changes due to temperature. Look into the Boussinesq and anelastic approximations if you're interested!

that's interesting because my understanding was that a lot of models used pressure as the vertical (height) coordinate and with tracking temperature at any given coordinate lets you know the density of the air at any point.

That's typical of models that use the anelastic approximation, where it's useful for a number of reasons to rewrite the equations replacing the true vertical with a vertically stratified variable. I've seen density, pressure and temperature used.

That's less of a different model and more a different way to rewrite the equations to make them easier to analyse or simulate.

We might be talking at slightly different angles here. There's a strong difference in the equations between compressibity of the fluid due to compression and changes in density due to temperature, chemical concentration, etc. The term compressibility usually refers to the first usage, and modelling it leads to sound waves in the system and has major implications for how the system is simulated, I mean it's an entirely different class of algorithms. The second, where density still changes but not due to compression, so no sound waves, that can be easily modelled without including full compressibility. This allows (generally simpler) incompressible models to still incorporate useful thermal physics where important, like in climate and weather. Also, the smaller the scale of the system the more compressibility matters so I wouldn't be surprised if compressibility starts to matter for e.g. Tornados. But I'm not certain on that...


yes it's called "actually having democratic elections"

What does "democratic elections" even mean in this new world where traditional politicians don't understand these dynamics?

Then vote for politicians who do.

Few of those are ever running. Mostly we have just two brands of smooth-brains whose only policy aim is “preventing that other group of assholes from gaining any power, because they and their supporters are pure evil!”

Each side gets the smooth brains they crave because for ~50% of the population it's become a team sport / religion situation. A majority of people have not thought through 1/10th of the policy positions they automatically support/reject based on the team hat color.

There's a quote I will mangle and I forget the source of that's something like "If you agree with all the positions of your chosen political party, either you have thought through every option and came to the same conclusions on dozens of topics, or you haven't thought through anything".


Comment is spot on, though I'd like to point out:

> because for ~50% of the population it's become a team sport / religion situation

It's kinda even worse. We can only have two parties because of FPTP, and turnout is about 60% of voting-eligible population on average. We know from recent popular vote that that 60% is split roughly 50-50.

So 30% of the voting population is Team Blue Hat, and 30% is Team Red Hat.

If you can get 15.1% of the population to vote for an unserious clown, they'll win their respective party's nomination. And in most states, one of the parties is a pretty sure lock in the general.

15% is a pretty low bar. Compare: Up to 30% of people think "chemtrails" are at least a "somewhat" real thing, and 5% of people believe vaccines contain microchips. So the bar for getting a guaranteed win is somewhere between those two wacky and easily disproven beliefs.

https://www.cnn.com/us/chemtrails-conspiracy-theory-explaine...

https://www.rutgers.edu/news/nearly-half-americans-still-uns...


Correction: "So 30% of the voting population is Team Blue Hat, and 30% is Team Red Hat." should have said "of the voting-eligible population"

Not a true democracy, then /s

also for ones fully into AI

too new, trinoo, ping -f, synflood, teardrop!


If only we had some way of signing messages


The technology isn't there yet (。•́︿•̀。)


Though in a case like this attackers would likely revoke (or publish) the private key.


Ah, perhaps we could put it on the blockchain! /s


delays between increasing capacity to produce and bringing production to market naturally lead to cycles of over and under production. https://thesystemsthinker.com/balancing-loops-with-delays/


where's a good irc chat these days?


It depends on the time of day, but #emacs, #nethack, #archlinux, #lobsters, #security, #openbsd usually have enough users for good convos. It depends on what you are into, really.


The develop-test-refine feedback loop for this kind of attack is so long (or expensive) that it seems likely to limit its real world use. Poison training data, wait months? a year? for the model to come out, see how well it worked, refine... or do you see a faster way to iterate?


Continual learning is the next major architectural milestone for the frontier labs. That’d reduce the iteration loop to days instead of years.

If your attacker assumes that all or most software will be generated from language models, the time penalty is worth paying.


if you don't know much math, it's easy to confuse the two


"what you see is all there is." it's generally much easier to verify something you've been made aware of than it is to know of it in the first place (and still verify it.)


The irony is that licensed interpreters / translators usually perform worse than AI.

Only the liability shifts from OpenAI to them.

Furthermore, where the alternative to a licensed professional was nothing, or a random untrained person or a weak professional, then it's harming the user on the pretext of protecting him.

(like in the other mentioned contexts).


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