aleph_minus_one

> One imagines maybe you can get to N^1.4 within that budget for whatever the brain is doing. Maybe. But that would be the limit.

Not for matrix multiplication, since the output, which has to be written, is already of size O(n^2).

> About ETH: Many people say now that ETH was simply stated in a too strong manner, and that the correct exponential time hypothesis is SH, the Satisfiability Hypothesis.

In 3 months: some AI frontier lab will disprove SH.

> It's completely standard for "galactic" algorithms and not relevant to big-O runtime.

This is true, but if doing brute-force search for all instances below some super-astronomic threshold is part of the algorithm, you typically want to understand

- where this constant comes from,

- how much this constant can be decreased (or why it can't)

- etc.

So, proving the correctness of an algorithm which is doing brute-force search for all instances below some super-astronomic threshold is typically just the first step towards getting an understanding of the complexity-theoretic phenomenon.

So: There is indeed nothing wrong with such aspects of galactic algorithms, but exactly understanding and improving the super-astronomic thresholds involved is the next step.

> How is first semester calculus a "weed-out" course when so many of these kids enter with transcripts indicating they've already taken calculus?

German universities have a simple solution: students who believe that they have already "learned" calculus in school (in a sense every pupil with an Abitur school diploma (the kind of school diploma that you need in Germany to study at a university) had to learn) should hold to this belief at their own peril. :-)

Hint: After one week, these kids will hopefully have realized that the level of calculus that they learned in school was very shallow. :-)

> Ignoring the stabbings and shootings, the children are not disciplined, properly supported, or permitted to excel. The speed of education moves at the slowest students and interrupted by the most disruptive.

"Smart" and "disruptive" are in my opinion at least uncorrelated, perhaps there even exists a non-trivial relationship:

In my observation often children who are either much less or more smart than the average are the more disruptive ones, though the children at the two the ends of this spectrum differ in the kinds of disruptions.

Those who are in power in Western countries only preach free markets if it serves to their advantage.

An interesting consideration, but don't functional languages have overhead, too?

> Trump got confused and said shithouse (which makes no sense) instead of shithole, his original term for basically any non-white country.

Is Norway really a non-white country? ;-)

> This is the problem with HN not doing humor. You are always the one who does not grok it...

Rather: many people who are not US citizens or don't live in the USA don't really care about the gossip around Donald Trump's most recent tantrum.

> Name one instance that approaches this level of immaturity.

Not a head of state, but I nominate:

Vladimir Volfovich Zhirinovsky (Владимир Вольфович Жириновский), "Russia's Trump"

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

> It is unfathomable to me how anyone can defend or relativize this despicable behavior.

From the perspective of a person who is neither a US citizen nor living in the USA: I (and many of my fellow countrymen/countrywomen) will relativize and defend a lot of Trump's tantrums since they give you so much material to laugh about.

:-)

> Ops is a specialized skillset completely orthog[o]nal to the business of building applications.

Exactly this was the idea: persons in a DevOps role have skills in both areas, i.e. are very wide skill set, so that one can assign them to very diverse tasks for more flexibility. Additionally, these persons can implement synergies to make things more efficient in areas that intersect both development and operation.

But in many countries (including Germany), you are not allowed to encrypt your transmissions via ham radio, e.g. using TLS with such IPv4 addresses is against the law.

If it is not rocket science, how does it work?

> Or just learn how to teach.

Most people don't want to learn (in particular not learn sufficiently hard to really improve).

> Regular people don’t even upgrade to Win 10/11 unless they are forced to.

In consideration how much spying functionality was added with Windows 10 (which worsened even more with Windows 11), and that Microsoft made it insanely hard to install Windows 11 without creating some Microsoft account, it is actually very sensible that people don't want to upgrade to Windows 10/11, despite the technological improvements that these versions provide.

> Microsoft went all in and have really not got much out of their efforts.

The problem was rather that Microsoft had no real plan what they wanted to get out of AI. If they had a plan, they could have laser-focused their all-in on AI.

Instead, Microsoft just AI-slopped a lot of their bread-and-butter products, making them much worse than before. If AI is as revolutionizing and beloved by users as Microsoft believes, Microsoft could easily have created an offering like "Windows AI Pack" or "Microsoft AI" that should sell like hot cakes.

On the other hand, if you have to force AI functionality onto the users, it should be considered as a strong sign that perhaps it is not something that the users want.

> The Aaron Swartz case is not an analog of these claims.

Indeed: the prosecution of Aaron Swartz drove him to suicide, while Anthropic's CEO Dario Amodei is still alive.

> N.B. JSTOR explicitly settled with Swartz, suffered no financial harm, and begged the federal government to drop the case

... and the course of action of Carmen Ortiz', the responsible Attorney General, drove Aaron Swartz into suicide.

> Funny how "maybe they work in different domain" doesn't come up here as well.

Good point. :-)

> Otherwise, the person building the bridge is not an engineer.

One is likely not an engineer if one does not notice the risk. But in practice, managers commonly desire docile subordinates, so the only thing an engineer can do in such a situation is to ensure that a paper trail gets generated that will be capable of breaking the manager's neck once the disaster has occurred. :-(

> To properly understand what you are going to build, it's not enough to read specifications from some manager as gospel. You need to ask questions, and challenge the requirements sometimes, to make them your own.

Many managers don't like being challenged. :-(

With this answer, you rather have revealed which style of programming you are strongly biased to.

> I’ll claim the ones in the end that will have that responsibility [to figure out if you're building the right thing] will be engineers.

One can have this stance. But in practice, programmers who have strong opinions on this topic that is not aligned to the management wishes will commonly become personae non gratae in the company, and are thus commonly on the brink of getting fired.

So, in the end, the incentives that exist in most companies are strongly biased towards the position that figuring out if you're building the right thing is the job of the managers and product owners. :-(

> I have a harder job convincing a team member who spent several days manually coding something that they’ve headed in the wrong direction compared to one who built it with AI. The person doesn’t have a personal attachment to the AI written code. Of course that also means they don’t understand every line like they would if they wrote it manually, but the lack of attachment is certainly a benefit.

If the situation that you have to convince a programmer to stop working on something is something that happens more often than very rarely is in my opinion a strong sign of bad leadership. These are people who are really in love with what they are doing and are thus so attached to it, and you want to cast out this love for working?

So, the moral that I can only get from your post is:

- AI can be used as a mitigation for bad leadership.

- Programmers should care much less about the work that they do.

> Some not so good ones have even stopped using AI at all, arguing it 'just got confused'. Good ones on the other hand are embracing it

The behaviour of the good programmers is in my experience very "spread": some embrace strongly embrace LLMs for programming, some strongly reject LLMs for programming, with everything in-between.

The explanatory variables that I rather think are good predictors whether a good programmer will embrace or reject LLMs for coding are rather the following ones:

1. Is the programmer biased towards the "artisan" side of programming, or does he see the code as a means to an end?

2. Is the programmer either

- in love,

- interested in, or

- does the programmer have to work with

more obscure programming languages and/or the abstractions and mental models that these programming languages are based on? If this is the case, using an AI is often more of a hindrance than help because there exists much less training data, and/or the programmer will much more often be confronted with the observation that the AI model simply does not "get" what he wants, and will very often get annoyed by bad AI code hallucinations.

Just in case someone from some frontier lab is reading this:

One problem where that mathematicians would love to see resolved is the smooth Poincaré Conjecture (in dimension 4): https://en.wikipedia.org/wiki/Generalized_Poincar%C3%A9_conj...

This is a problem where people really have no idea whether it holds or not (and different mathematicians have strong opinions here).

Additionally, "by mere coincidence" :-) (which makes this problem very fitting for the drama around the recent AI proof drops), the smooth Poincaré conjecture is a problem where Selman Akbulut, who made a lot of progress on it, posted strong claims of how his results were "stolen" by other famous mathematicians in the past:

https://selmanakbulut.com/plagiarism.pdf

There exist lots of non-wetting liquids in which humans cannot breathe.

> This is such a short sighted take. Number theory was considered beautifully useless for centuries, and now it’s the backbone of the cryptography that secures every bank transaction

If you refer to RSA or Diffie-Hellman: the number theory that it is based on is from 17th to at most 19th century, i.e. it precedes modern number theory.

I do consider modern number theory to be fascinating and do claim that many results from it could have huge applications in society, but the argument that parts of modern asymmetric cryptography is based on number theory is rather an argument that we don't need any number theory research anymore because these insanely old results that are used in cryptography have already been known for centuries - so no new research is necessary. :-(