> I want a jet airplane, but I can't afford one, and all the ones that exist are proprietary.
I guess if you worked together with some people who all put some money into a fund, and by using very modern technologies like 3D printing and modern CAD modelling etc., it should be possible even for private people to build a jet airplane.
The problem rather is that the government does an insane amount of gatekeeping to prevent this from happening (enforcing expensive and time-consuming certifications on airplanes and pilots etc.).
> Why aren't mathematicians excited about the frontiers being unlocked by AI?
For the mathematicians who still are in academia: I guess because the competition for research positions (in particular permanent ones) is already insane; they probably feel that AI makes this kind of competition even worse.
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There's one of mine in there where I predicted in 2023 that it would be 20 years until AI would be reliably able to entirely build and deploy arbitrary applications from a prompt. I was off by about 18 years on that one!
If you take "arbitrary" seriously, we are still very far away from it.
What is the strict definition of arbitrary you feel we haven’t reached? Right now the limit is scale and complexity, not domain or “type” of application.
> reliably able to entirely build and deploy arbitrary applications from a prompt
You're maybe thinking that we can build and deploy arbitrary "kinds" of application. Being able to "build and deploy arbitrary applications" would mean I could ask for any scale or complexity in my application.
Now that is moving the goalposts. The entire subthread has nothing to do with whether AI can match humans in any particular endeavour. It's simply about one user's past prediction about an AI capability.
> I don't think there'd be any controversy if the problem statement said "common applications"
I would claim "common applications" is also controversial because what is a "common application" depends insanely on the area in which you work. Even if you exclude some highly advanced scientific applications (because you don't consider these to be common), in many industrial sectors there exist applications that have grown over multiple decades, and which encode an insane amount of knowledge about the respective sector and its workflows; this is a central reason why these applications are so hard to replace.
Well, it depends on how you define "complexity." LLMs are totally rewriting the notions of what's hard for a computer but easy for a human. LLMs have really bad spatial reasoning. I would have to play around a bit, but I'm very certain you could come up with a prompt where an AI is incapable of properly generating a "simple" app that has some important layout constraints.
And just generally, anything that requires the LLM to understand something LLMs don't understand, it's going to fail. I'd hesitate to give an exact example without trying Astra/Fable but I'm sure they exist.
One-shot a minesweeper clone that isn't screwed up in an insane way. Bonus points if you choose a language/platform that LLMs aren't likely to have already seen a minesweeper clone done in/for already.
Right now, they can't build anything without help that isn't buggy in unintelligible ways. If you push the thing feature by feature, have a lot of tests and a lot of instrumenting, and you check that it isn't cheating or lying after every step, you can get a lot of work done.
- Even if we have P=NP, it is not even known whether there will ever exist a "practically useful/fast" algorithm for solving NP-complete decision problems.
- If P != NP, it is perfectly reasonable that there exists an algorithm that is for all practical purposes "fast" algorithm (say, some O(n^{log log log log log log log n}) algorithm with a very small hidden constant) for solving NP-complete decision problems.
- It is entirely possible that average case complexity is the much more important complexity measure than the worst-time measure that is used for defining the P and NP complexity classes. If you are into this kind of questions, you might enjoy the article
Fifty Years of P vs. NP and the Possibility of the Impossible
Also, in the realm of complexity theory, the question of P vs NP is just a small puzzle piece.
Just to give one example: isn't the question of P vs PSPACE much more exciting. If you believe in P != NP, P != PSPACE is a trivial corollary. But we can't even exclude P = PSPACE.
Seriously: there exist so many complexity classes (some of high potential practical importance) for which we often basically know nothing except for the trivial inclusions.
In Germany, there is a reason why the term "akademisches Prekariat" (academic precariat/precarity) exists, meaning that people who stay in academia are often in a precarious job situation and are paid quite badly. But these people are very intelligent and well-educated.
That doesn't really contradict what I said. This definition of intelligence can be useful in some contexts, but on average neither women nor capital are particularly attracted to people who have it
> This definition of intelligence can be useful in some contexts, but on average neither women nor capital are particularly attracted to people who have it[.]
Was my point really that hard to follow? I'm not saying "intelligence" in the strict psychological definition of the word. I mean, perhaps, the thing they claim was the independent variable was in fact a proxy for something else I hypothecated as "intelligence", by which I really meant some as yet undefined thing that on average leads to higher incomes, which could be intelligence in the colloquial sense, because that sort of has that trait and is pretty influential in attractiveness.
> Similar/compatible education level? Just a proxy for income.
This clearly does not hold in Germany. There, you often can earn much more money with a vocational training than with a humanities degree, in particular in the current messed up job market.
On the other hand, people with different education levels often have very different psychometric traits (similarity here is very important for the relationship to work).
> Similar/compatible hobbies? Guess what, also a proxy for income!
There do exist some hobbies that are somewhat correlated to social classes (think of who plays soccer/tennis/golf (replace "soccer" by a different sport if you live in the USA)), even though these associations are much less pronounced than in former days.
On the other hand, for example, a person who loves sports climbing or parachuting will likely have very different psychometric traits from people who are into stamp collecting.
Thus, in many cases, hobbies are thus rather a proxy for some psychometric traits.
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If you have a phone (or other device that connects to mobile networks), your government knows your daily routine anyway.
Because of this reason, quite a lot of people
- don't actually own a mobile phone,
- formally own a mobile phone, but only carry it around if the likelihood is very high that they will need it
- if they need to be available via mobile phone for job reasons (and are thus survived), they prefer to use a feature phone or if it must be a smart phone, they don't install any additional apps or remove the additional surveillance functions from the operating system as far as easily possible
I guess if you worked together with some people who all put some money into a fund, and by using very modern technologies like 3D printing and modern CAD modelling etc., it should be possible even for private people to build a jet airplane.
The problem rather is that the government does an insane amount of gatekeeping to prevent this from happening (enforcing expensive and time-consuming certifications on airplanes and pilots etc.).
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