Some context: https://eu.36kr.com/en/p/4023452816134019
5,089 karma · joined February 14, 2023
I can only say that in Germany, where I live, in my gut feeling the situation is very different: politicians imposing various laws "for the common good" and many parts of the populations hate these laws because this implies even more red tape.
Not Flere-Imsaho:
I think if one made a serious effort, one could easily find a well-founded answer to this question that is based on a solid rational foundation.
The problem rather is: people (often in decision positions, but also employees who fear for their jobs) don't act rationally on AI:
- For example, managers firing good programmers because programmers are to be replaced by AI. By now you can find many reports of companies who try to convince their programmers that they fired "because of AI" to come back.
- Similarly, panicking employees who demand irrational restrictions on AI. EDIT: with this I mean for example "legal restrictions on AI with on a pretense of say 'AI is too dangerous for the public'".
These very non-rational factors and irrational actions are very hard to predict.
A lot of people that I know would strongly prefer to go to some brick and mortar shop. The problem is: most of items that I buy on the internet (e.g. on Amazon) are simply not easily available in a shop in my town (and I am not living in a small town).
For example:
- lots of obscure scientific books that are written in German or even English (I live in Germany)
- similarly: lots of rather niche belletristic books (think into the direction: some obscure novel recommendation on HN) often in various foreign languages
N.B. It is true that an important reason why Amazon got big among early computer enthusiasts in Germany in the 90s is that it was one of the few ways for easily getting computer science textbooks delivered from the USA - though with long delivery times.
- 3D printing supplies (why doesn't there exist a brick an mortar store for this?)
- very niche indie games (they are by now basically all sold on Steam, GOG, Epic Store or itch.io)
- very specific parts for Maker projects
- ...
So, the situation is not that people necessarily want to buy on the internet or specifically Amazon, but rather that there exists barely any way to get what they want in a brick and mortar store in even large cities.
This is exactly the hard part: a topic which many people in more applied scientific disciplines worry about. Welcome to the real word, Neo. :-)
Again, I don't have definite answer, but rough guidelines are:
- is a result too good to be true?
- is some result coherent to results that are much more established?
- why would you assume that the author is unbiased or biased? (biases not only have financial reasons)
- which agenda does the author have (yes, deep pursuit for scientific truth is also an agenda? Nobody is free of an agenda)
- does the author make an effort to explain how the findings could be explained in an alternative way that makes the result look much less impressive?
- could the results be reproduced in other labs?
- which is the minimum amount of facts that you must believe in (like axioms) such that the result holds?
- ...
For a lack of deep knowledge in this area, I don't think I have answers for this, but if one is interested in working on this problem, my approach would be to start with diving deeply into scientific literature about psychology and sociology to find out
- what convinces people to change their opinions,
- what causes people to take action
etc.
"Convincing the masses to send these politicians to hell" is thus nearly isomorphic to making the masses hate politicians who create such laws, which at least very likely implies that by convincing the masses to send these politicians to hell, a different mindset emerges in the masses.
I have no access to Astra, but with GPT 6.1 Sol, the results with respect to attempting to create STL, OBJ or even OpenSCAD files by using image references and a prompt were really bad.
Nevertheless, my counterpoint to
> If they actually had access to systems that could do "years of top professional work" across software, cyber, science, and math, they would not mostly be leaving to start more chatbot companies, agent frameworks, eval tools, and "AI for workflow" startups.
> They would be starting normal companies to disrupt the global economies of the world.
> Insurance companies. CAD companies. Compliance companies. Security auditing firms. Logistics software. Tax automation. ERP replacements. Drug discovery tooling. Industrial design. Legal ops. Accounting systems. Boring vertical SaaS with insane output per employee.
is:
Many people who work in such industries already know an insane amount of inefficiencies. Unluckily, they are not in positions and have no political power (with respect to organizational policy) in the company that they are capable of changing the situation.
Additionally, many of these sectors are heavily regulated, so it is very hard to make a difference in this sector as a startup founder, and even if there is an entrpreneur who founds a company to change the status quo, an insane amount of work in the company will be handling the big amount of red tape.
Many very smart people who I know are quite skeptical of LLMs and the hype around them. In my observation/echo chamber, the people who are very into LLMs are rather slick, career-minded people who love to present themselves as trendsetters for the "next fancy thing".
Rather: these problems are not solved because there are not enough geniuses who are capable of convincing the masses to send the responsible politicians to hell.
I don't think this explanation is sufficient:
For example, many nerds care about 3D printing. On the other hand, my experiments (and the experiments of many nerds who I know) to let LLMs create files for 3D printing lead to horrendously lacking results.
Or many nerds care about linguistics or puns. Whenever a new LLM comes out to which I have easy access, I do the test, and let it explain some specific German jokes to me that are based on convoluted puns in the German grammar. Until now, no LLM that I had access to could give satisfying explanations of the puns on which these jokes are based.
Or even for coding (many nerds do care about elegant, sophisticated code): the LLMs that I could test were already overchallenged with the following task: I had written some code that is a very "artisanal", "clever" improvement of an algorithm over the version that one would find in a textbook. The task for the LLM was simply to write some code comments/documentation about the mathematical ideas upon which my improvement over the textbook version of the algorithm is based. It wasn't capable to do this. On the other hand, for a junior programmer, I would in such a situation expect that he goes through every single line and thinks through the algorithmic ideas so that he can learn from them.
---
Thus: even for "nerdy" topics, it is very easy to find tasks where LLMs still suck. So, my hypothesis about the nerds that you mention in your post is that these nerds are rather people who want to believe (with religious fervor) that the current LLMs are exceptionally good instead of just looking into a slightly different direction than where the tech billionaires want the users of LLMs to look at.
> one cannot help to suspect that this specific kind of academic malpractice does in fact have a point which is to undermine the technology as a whole out of fear, to keep the academic "consensus" in favor of tenured academics
Serious studies often take a lot of time to do. Also, models outdate very fast. So, of course nearly every serious study on such a topic will be based on models that are considered "outdated" by LLM aficionados.
So, no need to invent conspiracy theories that such studies are made to keep the academic "consensus" in favor of tenured academics.
My experience slightly differs: yes, LLMs are not the best entities to discuss innovative scientific ideas that one has in mind, but they are still often much more competent discussion partners on such topics than the people you are typically surrounded with (e.g. work colleagues).
(no, this is not a template for a Reddit /r/iamverysmart/ post :-) , but just my experience).
Often people who are critical of whether AI can lead to research breakthroughs are experts in the respective area, who nevertheless are afraid of their future career prospects in academia (getting a permanent position in academia is hard and it is deeply political who gets such a position).
This people are thus not scared by AI per se (it's basically their daily job to devise innovations that advance their field), but their fears are that
- because of the hype around AI the research into which they invested years, often decades, will be considered "unimportant",
- incompotent people in decision-making positions will think researchers can be replaced by AI.
This depends on the country:
- In Germany, many people are very suspicious about such privacy invasions.
- In Singapore, on the other hand, people seem to very accepting of public surveillance if it serves public safety.
- In China, of course, public surveillance is also huge (at least in the big cities). I don't know how Chinese citizens think about that.
> Tech worker / Software engineer:"The only piece of technology in my house is a printer from 2004, and I keep a loaded gun next to it in case it makes a noise I don't recognize."
You forgot an additional well-known punchline (source: https://old.reddit.com/r/NonPoliticalTwitter/comments/1e8do2...):
> I wouldn't keep the gun next to the printer; it may be able to use it against you
This is already the situation that we have: because of the fierce competition for temporary academic positions, and very little hope for permanent positions, large quantities of really good mathematicians leave academia and work in a job that has basically nothing with mathematics (many mathematicians consider these jobs as bullshit jobs, but they pay the bill).
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.).
SETH: Strong Exponential Time Hypothesis
See https://en.wikipedia.org/w/index.php?title=Exponential_time_...
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.
- 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
--
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 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.
The German tax system is one of the most complicated one in the world.
If you take "arbitrary" seriously, we are still very far away from it.
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 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. :-)
"Intelligence" is a term that is defined very precisely in psychology (psychometrics):