aleph_minus_one

P vs NP does not mean what people think it means:

- 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

https://cacm.acm.org/research/fifty-years-of-p-vs-np-and-the...

and the paper

R. Impagliazzo

A personal view of average-case complexity

https://www.karlin.mff.cuni.cz/~krajicek/ri5svetu.pdf

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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.

> 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.

> I'm not specifically familiar with swiss tax law but european taxes are typically far more simple than american taxes.

The German tax system is one of the most complicated one in the world.

> 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.

> really meant some as yet undefined thing that on average leads to higher incomes, which could be intelligence in the colloquial sense

What you are looking for are "dark triad traits", i.e.

- machiavellianism,

- (sub-clinical) narcissism, and

- (sub-clinical) psychopathy.

> https://en.wikipedia.org/wiki/Dark_triad

These are quite correlated to higher incomes and higher-status jobs.

> 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 is actually a reformulation of the point that I made in https://news.ycombinator.com/item?id=49920421 that income is not a proxy for intelligence. :-)

> It is, if you define intelligence as "how to do well in life"

"Intelligence" is a term that is defined very precisely in psychology (psychometrics):

> https://en.wikipedia.org/wiki/G_factor_(psychometrics)

> But you can definitely do a lot worse than what citizens of Singapore actually get...

People who have a pronounced anti-surveillance stance will strongly object this claim.

> Or income is a proxy for, say, intelligence.

It clearly isn't.

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.

> 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.

> 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

> the three YCombinator startups I worked at had founders who hired their significant others.

Often, this is done for tax reasons.

> Cute. Of course, beyond basic deal breakers, neither do people know their preferences

Scott Alexander disagrees:

> https://www.astralcodexten.com/p/in-defense-of-describable-d...

(see also the follow-up article https://www.astralcodexten.com/p/highlights-from-the-comment...).

Important quote from this article concerning your point:

"Here are some things that are so obvious they sound like cheating:

Unless you’re bisexual, you probably care if someone is a man or a woman

Many people care whether their partner prefers polyamorous or monogamous relationships.

Many people want a partner of the same religion and level of religiosity.

Many people want a partner who matches their preference about whether to have children, and how many to have.

…because in practice, people end up very closely matched on some criteria

Only about 4% of marriages are between Democrats and Republicans

Only about 3% of high school dropouts marry a spouse with a college degree, compared to more than 80% of PhDs.

90% of whites marry other whites; 80% of blacks marry other blacks.

Husbands and wives’ social classes correlate at about 0.8

If 96% of Democrats are marrying non-Republicans, it seems like Democrats must have a strong preference against marrying Republicans, and ought to value having information about someone’s politics before they date them. Realistically, this underestimates the level of political sorting; I don’t think I’d be a good match for an extremely woke person, even if we were both technically “Democrats”."

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> Specifically, interests, hobbies, daily routines, objectives, etc. have nothing to do with compatibility.

Of course your claim "'We like the same things!' is the compatibility signal of a naive 22-yr old…" is correct, but I am very certain that there exist quite a lot of interests, hobbies and objectives that require a partner that is "compatible" with these (and in most cases, people who have such interests, hobbies and objectives know this very well). This obviously does not mean that the partner has to have the same hobbies and interests. :-)

For example,

- there do exist good reasons why in university time, sports climbing was basically a dating market

- a person who has hobbies that are associated with semi-legal activities (which clearly does not mean that he/she does anything illegal!) like hacking in the classical sense will likely not be a good fit for a spouse who works in law enforcement

- a person who is a climate activist will likely be a bad fit for a spouse who works in the oil/gas industry

- a person who is very into internet privacy topics (think cypherpunk) will likely not be compatible with a social media influencer

> If we theoretically hit the point where it could do all of its research itself, better than a human, things _would_ be different.

If we theoretically found a way to shield or reverse gravity, things in aviation or space travel would be different. Or if we theoretically found a way to make cold fusion work, things would be very different. :-)

It is in my opinion not a good idea to invest in companies for which the feasibility of the business models depends on the capability of making science-fiction stories work.

> The problem is twofold. One, even a monopoly AI provider wouldn't have pricing power against its suppliers. Its suppliers are energy, semiconductors, and real estate. Semiconductors maybe they could get some leverage on but energy and real estate have plenty of other buyers.

Concerning the leverage on energy and real estate: don't forget that the AI companies have quite a lot of choice where to build their data centers. So AI companies have lots of opportunities to play several parties off against each other (in particular also for real estate and energy).

> From a business perspective a frontier model does not make much sense anymore if you are not a startup. Neither for Amazon, nor for Google. Their clouds need models that are fast and perform well in their agent frameworks nothing w[h]ere a frontier model excels at.

A good consideration; just one point from my side: as far as I am aware (but I may be wrong), Gemini is not known to perform well in an agentic framework.

This is no contradiction to your other claims, quite the opposite: perhaps (or even likely) Google wants to avoid that their models become a commodity in some (agentic?) application where the middleman who actually writes this application gets a disproportionate of the money that the customer of the application pays for it.

> China will always be generations behind until they crack domestic EUV

Are you sure?

--

China Just Built What TSMC Said Was Impossible

https://www.youtube.com/watch?v=Pk-w279ESHg

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China Just Built What ASML Feared Most

https://www.youtube.com/watch?v=YiPgSm62fiM

> Then why have they been lagging behind OpenAI and Anthropic for most of the last few years, and only briefly been at the frontier?

One possible explanation: because Google is a little bit more frugal and focuses on how to make providing AI models financially feasible - combined with some willingness to burn money so that they don't strongly fall behind on their AI models.

On the other hand, OpenAI and Anthropic at least formerly concentrated on building and providing the best models that they could with concerns about financial feasibility taking a backseat.

Just to be clear: I do have the impression that by now (likely because of pressure from investors) OpenAI and Anthropic take these financial concerns more seriously, but nevertheless Google's vs OpenAI's/Anthropic's "DNAs" concerning on what to focus on differ.

> I guess if one of them hits singularity, it could in theory just wipe out all the rest

The story that some AI company might reach singularity and then "everything will be different" is another science-fiction story that executives of AI companies love to tell to justify the staggering amount of necessary investments and cash burn. :-)

> The famous theory of Dario Amodei was that AI was this winner-takes-all field where the first team to get a head start would never cede ground back.

This is the kind of story that ones tells to investors to justify the huge amount of cash burn. :-)

Why don't you simply ask the respective model which model is best for a specific task? :-)

As far as I know, this depended a lot on the individual game:

Games that had quite a bit of code that profited from the higher-level abstractions that C/Pascal provided, such as

- resource management (including dynamic asset loading/unloading)

- enemy AI

- pathfinding

- ...

of course typically contained a lot more C/Pascal code than games that were more on the "multimedia demo" side with a simpler game logic.

> it was called Cactus Data Shield.

Indeed:

> https://en.wikipedia.org/wiki/Cactus_Data_Shield

Additionally, I remember from this time (perhaps this was a very German thing) that bands and stars whose CDs used Cactus Data Shield or a similar copy protection system suddely got hated and abandoned by parts of their fanbase.

> Nope, they were mostly written in Assembly.

It depends: for the classic 8 bit home computers, games were mostly written in assembly. Later DOS games were commonly either written in Pascal or C, but quite a bit off Assembler code was often used for the more performance-critical code sections.

> Presumably this is a so-called “chicken bit”.

For those who are out of the loop:

> https://lwn.net/Articles/744840/

See also

> https://en.wiktionary.org/wiki/chicken_bit

(click on "quotations") for a list of scientific texts in which this term occurs.

> It's not every day you see someone so incredibly dismissive of the product they're selling themselves.

I believe that considering that AI is much cheaper than their service offering, and thus customers of Dymocks Tutoring and Talent 100 often ask them how much more they are actually offering for the much more expensive price has put this company under a lot of price pressure from customers.

So, I bet that Dymocks Tutoring and Talent 100 wants to change their main service offering to target parents from rich families instead who aren't so stingy.

Perhaps tell the AI that it should rather "praise" you as much for the progress that you make as a Chinese parent.

:-)

(to make it clear: this was a joke, even though I'd actually be interested whether this works)

> But I also have a soft spot for Myst.

Riven is even better. :-)

Because there exist so many schools of programming and so many deep philosophical considerations what makes software good vs not good.

Basically, software created by programmers who are more on the artisan side often deeply encodes what they value in life and what they don't.

So, finding a "good" programmer for a company means finding someone who is skilled in programming, and who has very compatible deep opinions about life and everything.

Also, many exceptional programmers are not good, obedient workers in a "software factory"; this is another consideration that you have to keep in mind.

> I'm shocked in general at the lack of open source Rapid Application Development software.

They exist:

- In particular in the 90s and 00s, Tcl/Tk was really magic for creating user interfaces for small applications under GNU/Linux.

- Lazarus attempts to be an open-source analogue to Delphi

- LibreOffice Base attempts to fill the same niche as Microsoft Access

- Historically, in the time of Gtk+ 1.x and 2.x Glade [1] was an editor for clicking together user interfaces. Well, development ceased, and under GNU/Linux there is no attitude of retaining backwards compatibility with applications/libraries that are not maintained anymore (but which might be business-critical).

- ...

But of course Rapid Application Development is much more popular in the business world which is (at least in many European countries) a rather Microsoft-centric environment. Additionally, the typical developer that uses Rapid Application Development is often a subject-matter expert in some department who also knows a little bit about programming (i.e. is not in deep love with programming), and not a programming expert who also knows about some other specialized topics that are important for the business.

On the other hand, the open source environment typically rather attracts people who really like programming.

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[1] https://en.wikipedia.org/wiki/Glade_Interface_Designer