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AI is a floor raiser, not a ceiling raiser

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51–60 of 218 posts

Re: AI is a floor raiser, not a ceiling raiser

#51

There are some things that you still can't do with LLMs. For example, if you tried to learn chess by having the LLM play against you, you'd quickly find that it isn't able to track a series of moves for very long (usually 5-10 turns; the longest I've seen it last was 18) before it starts making illegal choices. It also generally accepts invalid moves from your side, so you'll never be corrected if you're wrong about…

> people aren't aware of how wrong they can be, and the errors take effort and knowledge to notice. I have friends who are highly educated professionals (PhDs, MDs) who just assume that AI\LLMs make no mistakes. They were shocked that it's possible for hallucinations to occur. I wonder if there's a halo effect where the perfect grammar, structure, and confidence of LLM output causes some users to assume expertise?

Computers are always touted as deterministic machines. You can't argue with a compiler, or Excel's formula editor.

AI, in all its glory, is seen as an extension of that. A deterministic thing which is meticulously crafted to provide an undisputed truth, and it can't make mistakes because computers are deterministic machines.

The idea of LLMs being networks with weights plus some randomness is both a vague and too complicated abstraction for most people. Also, companies tend to say this part very quietly, so when people read the fine print, they get shocked.

Re: AI is a floor raiser, not a ceiling raiser

#52
post #50

The blog post has a bunch of charts, which gives it a veneer of objectivity and rigor, but in reality it's just all vibes and conjecture. Meanwhile recent empirical studies actually point in the opposite direction, showing that AI use increases inequality, not decrease it. https://www.economist.com/content-assets/images/20250215_FNC... https://www.economist.com/finance-and-economics/2025/02/13/h...

The graphic has four studies that show increased inequality and six that show reduced inequality.

Re: AI is a floor raiser, not a ceiling raiser

#53

There are some things that you still can't do with LLMs. For example, if you tried to learn chess by having the LLM play against you, you'd quickly find that it isn't able to track a series of moves for very long (usually 5-10 turns; the longest I've seen it last was 18) before it starts making illegal choices. It also generally accepts invalid moves from your side, so you'll never be corrected if you're wrong about…

> people aren't aware of how wrong they can be, and the errors take effort and knowledge to notice. I have friends who are highly educated professionals (PhDs, MDs) who just assume that AI\LLMs make no mistakes. They were shocked that it's possible for hallucinations to occur. I wonder if there's a halo effect where the perfect grammar, structure, and confidence of LLM output causes some users to assume expertise?

Have they never used it? Majority of the responses that I can verify are wrong. Sometimes outright nonse, sometimes believable. Be it general knowledge or something where deeper expertise is required.

Re: AI is a floor raiser, not a ceiling raiser

#54
post #50

The blog post has a bunch of charts, which gives it a veneer of objectivity and rigor, but in reality it's just all vibes and conjecture. Meanwhile recent empirical studies actually point in the opposite direction, showing that AI use increases inequality, not decrease it. https://www.economist.com/content-assets/images/20250215_FNC... https://www.economist.com/finance-and-economics/2025/02/13/h...

Thanks for the links. That should be obvious to anyone who believes that $70 billion datacenters (Meta) are needed and the investment will be amortized by subscriptions (in the case of Meta also by enhanced user surveillance).

The means of production are in a small oligopoly, the rest will be redundant or exploitable sharecroppers.

(All this under the assumption that "AI" works, which its proponents affirm in public at least.)

Re: AI is a floor raiser, not a ceiling raiser

#55

Earlier quoted context omitted.

Hogwash. If you can't figure out how to do something with project Y from npm try checking it out from Github with WebStorm and asking Junie how to do it -- often you get a good answer right away. If not you can ask questions that can help you understand the code base. Don't understand some data structure which is a maze of Map (s) it will scan how it is used and give you draft documentation. Sure you can't point it t…

> Sure you can't point it to a Jira ticket and get a PR You absolutely can. This is exactly what SWE-Bench[0] measures, and I've been amazed at how quickly AIs have been climbing those ladders. I personally have been using Warp [1] a lot recently and in quite a lot of low-medium difficulty cases it can one-shot a decent PR. For most of my work I still find that I need to pair with it to get sufficiently good results…

How does Warp compare to others you have tried?

Re: AI is a floor raiser, not a ceiling raiser

#56
post #3

AI is an interpolator, not an extrapolator.

I read this as interloper. What's an extraloper?

An interloper being someone who intrudes or meddles in a situation (inter "between or amid) + loper "to leap or run" - https://en.wiktionary.org/wiki/loper ), an extraloper would be someone who dances or leaps around the outside of a subject or meeting with similar annoyances.

Re: AI is a floor raiser, not a ceiling raiser

#57

There are some things that you still can't do with LLMs. For example, if you tried to learn chess by having the LLM play against you, you'd quickly find that it isn't able to track a series of moves for very long (usually 5-10 turns; the longest I've seen it last was 18) before it starts making illegal choices. It also generally accepts invalid moves from your side, so you'll never be corrected if you're wrong about…

> people aren't aware of how wrong they can be, and the errors take effort and knowledge to notice. I have friends who are highly educated professionals (PhDs, MDs) who just assume that AI\LLMs make no mistakes. They were shocked that it's possible for hallucinations to occur. I wonder if there's a halo effect where the perfect grammar, structure, and confidence of LLM output causes some users to assume expertise?

> I wonder if there's a halo effect where the perfect grammar, structure, and confidence of LLM output causes some users to assume expertise?

I think it's just that LLMs are modeling generative probability distributions of sequences of tokens so well that what they actually are nearly infallible at is producing convincing results. Often times the correct result is the most convincing, but other times what seems most convincing to an LLM just happens to also be most convincing to a human regardless of correctness.

Re: AI is a floor raiser, not a ceiling raiser

#58

Earlier quoted context omitted.

Boxen? (Oxen)

AFAIK, Boxen is a permutation of Boxes, not Oxen.

There seems to be a pattern of humorous plurals in English where by analogy with ox ~ oxen you get -x ~ -xen: boxen, Unixen, VAXen.

Before you call this pattern silly, consider that the fairly normal plural “Unices” is by analogy with Latin plurals in -x = -c|s ~ -c|ēs, where I’ve expanded -x into -cs to make it clear that the Latin singular comprises a noun stem ending in -c- and a (nominative) singular ending -s, which does exist in Latin but is otherwise completely nonexistent in English. (This is extra funny for Unix < Unics < Multics.) Analogies are the order of the day in this language.

Re: AI is a floor raiser, not a ceiling raiser

#60

There are some things that you still can't do with LLMs. For example, if you tried to learn chess by having the LLM play against you, you'd quickly find that it isn't able to track a series of moves for very long (usually 5-10 turns; the longest I've seen it last was 18) before it starts making illegal choices. It also generally accepts invalid moves from your side, so you'll never be corrected if you're wrong about…

> people aren't aware of how wrong they can be, and the errors take effort and knowledge to notice. I have friends who are highly educated professionals (PhDs, MDs) who just assume that AI\LLMs make no mistakes. They were shocked that it's possible for hallucinations to occur. I wonder if there's a halo effect where the perfect grammar, structure, and confidence of LLM output causes some users to assume expertise?

I worry that the way the models "Speak" to users, will cause users to drop their 'filters' about what to trust and not trust.

We are barely talking modern media literacy, and now we have machines that talk like 'trusted' face to face humans, and can be "tuned" to suggest specific products or use any specific tone the owner/operator of the system wants.

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