I will believe this theory if someone shows me that the ratio of scientists to engineers of leading teams of the leading companies deploying AI products is bigger than 1.
layer8 · 3m ago
I don’t think the dichotomy between scientists and engineers that’s being established here is making much sense in the first place. Applied science is applied science.
therobots927 · 29m ago
This is pure sophistry and the use of formal mathematical notation just adds insult to injury here:
“Think about it: we’ve built a special kind of function F' that for all we know can now accept anything — compose poetry, translate messages, even debug code! — and we expect it to always reply with something reasonable.”
This forms the axiom from which the rest of this article builds its case. At each step further fuzzy reasoning is used. Take this for example:
“Can we solve hallucination? Well, we could train perfect systems to always try to reply correctly, but some questions simply don't have "correct" answers. What even is the "correct" when the question is "should I leave him?".”
Yes of course relationship questions don’t have a “correct” answer. But physics questions do. Code vulnerability questions do. Math questions do. I mean seriously?
The most disturbing part of my tech career has been witnessing the ability that many highly intelligent and accomplished people have to apparently fool themselves with faulty yet complex reasoning. The fact that this article is written in defense of chatbots that ALSO have complex and flawed reasoning just drives home my point. We’re throwing away determinism just like that? I’m not saying future computing won’t be probabilistic but to say that LLMs are probabilistic, so they are the future of computing can only be said by someone with an incredibly strong prior on LLMs.
I’d recommend Baudrillards work on hyperreality. This AI conversation could not be a better example of the loss of meaning. I hope this dark age doesn’t last as long as the last one. I mean just read this conclusion:
“It's ontologically different. We're moving away from deterministic mechanicism, a world of perfect information and perfect knowledge, and walking into one made of emergent unknown behaviors, where instead of planning and engineering we observe and hypothesize.”
I don’t actually think the above paragraph makes any sense, does anyone disagree with me? “Instead of planning we observe and hypothesize”?
That’s called the scientific method. Which is a PRECURSOR to planning and engineering. That’s how we built the technology we have today. I’ll stop now because I need to keep my blood pressure low.
aredox · 19m ago
Again there is a match between programs and the structure that creates it (a.k.a. Conway's law). This society not only tolerates but embraces bullshit, it has elected a complete con man, and now it is sinking billions of dollars building universal bullshit machines.
therobots927 · 5m ago
Exactly right. LLMs are a natural product of our post truth society. I’ve given up hope that things get better but maybe they will once the decline becomes more tangible. I just hope it involves less famine than previous systemic collapses.
falcor84 · 20m ago
> Yes of course relationship questions don’t have a “correct” answer. But physics questions do. Code vulnerability questions do. Math questions do. I mean seriously?
But as per Gödel's incompleteness theorem and the Halting Problem, math questions (and consequently physics and CS questions) don't always have an answer.
layer8 · 8m ago
There is a truth of the matter regarding whether a program will eventually halt or not, even when there is no computable proof for either case. Similar for the incompleteness theorems. The correct response in such cases is “I don’t know”.
therobots927 · 4m ago
You know something I don’t hear a lot from chatGPT? “I don’t know”
therobots927 · 14m ago
Providing examples of questions without correct answers does not prove that no questions have correct answers. Or that it’s hallucinations aren’t problematic when they provide explicitly incorrect answers. The author is just avoiding addressing the hallucination problem at all by saying “well sometimes there is no correct answer”
mentalgear · 49m ago
> After decades of technical innovation, the world has (rightfully) developed some anti-bodies to tech hype. Mainstream audiences have become naturally skeptical of big claims of “the world is changing”.
Well, it took about 3 years of non-stop AI hype from the industry and press (and constant ignoring of actual experts) until finally the perception seems to have shifted in recognising it as another bubble. So I wouldn't say any lessons were learned. Get ready for the next bubble when the crypto grifters that moved to "AI" will soon move on the to the NEXT-BIG-THING!
lacy_tinpot · 36m ago
Is it really "hype" if like 100s of millions of people are using llms on a daily basis?
pmg101 · 29m ago
The dot-com bubble burst but I'm betting you visited at least one of those "websites" they were hyping today.
AIorNot · 1h ago
From the article:
“We have a class of products with deterministic cost and stochastic outputs: a built-in unresolved tension. Users insert the coin with certainty, but will be uncertain of whether they'll get back what they expect. This fundamental mismatch between deterministic mental models and probabilistic reality produces frustration — a gap the industry hasn't yet learned to bridge.”
And all the news today around AI being a bubble -
We’re still learning what we can do with these models and how to evaluate them but industry and capitalism forces our hand into building sellable products rapidly
CGMthrowaway · 16m ago
It's like putting money into a (potentially) rigged slot machine
failiaf · 1h ago
(unrelated) what's the font used for the cursive in the article? the heading is ibm plex serif and the content dm mono, but the cursive font is simply labeled as dm mono which isn't accurate
oh! i mistook 'dm' to be 'dm mono', but this appears to be correct
leutersp · 1h ago
Chrome Dev console shows that the italics font is indeed named "dm" just like the rest of the content. It is not really a cursive, only a few letters are stylized ("f", "s" and "l").
It is possible (and often desirable) to use different WOFF fonts for italics, and they can look quite different from the standard font.
hodgehog11 · 1h ago
This seems like an expression of The Bitter Lesson:
Author advocates for building general purpose systems that can accomplish goals within some causal boundary given relevant constraints, versus highly deterministic logical flows that are created from priors like intuition or user research.
Parallel with the bitter lesson being that general purpose algorithms that use search and learning leveraged by increasing computational capacity tend to beat out specialized methods that exploit intuition about how cognitive processes work.
“Think about it: we’ve built a special kind of function F' that for all we know can now accept anything — compose poetry, translate messages, even debug code! — and we expect it to always reply with something reasonable.”
This forms the axiom from which the rest of this article builds its case. At each step further fuzzy reasoning is used. Take this for example:
“Can we solve hallucination? Well, we could train perfect systems to always try to reply correctly, but some questions simply don't have "correct" answers. What even is the "correct" when the question is "should I leave him?".”
Yes of course relationship questions don’t have a “correct” answer. But physics questions do. Code vulnerability questions do. Math questions do. I mean seriously?
The most disturbing part of my tech career has been witnessing the ability that many highly intelligent and accomplished people have to apparently fool themselves with faulty yet complex reasoning. The fact that this article is written in defense of chatbots that ALSO have complex and flawed reasoning just drives home my point. We’re throwing away determinism just like that? I’m not saying future computing won’t be probabilistic but to say that LLMs are probabilistic, so they are the future of computing can only be said by someone with an incredibly strong prior on LLMs.
I’d recommend Baudrillards work on hyperreality. This AI conversation could not be a better example of the loss of meaning. I hope this dark age doesn’t last as long as the last one. I mean just read this conclusion:
“It's ontologically different. We're moving away from deterministic mechanicism, a world of perfect information and perfect knowledge, and walking into one made of emergent unknown behaviors, where instead of planning and engineering we observe and hypothesize.”
I don’t actually think the above paragraph makes any sense, does anyone disagree with me? “Instead of planning we observe and hypothesize”?
That’s called the scientific method. Which is a PRECURSOR to planning and engineering. That’s how we built the technology we have today. I’ll stop now because I need to keep my blood pressure low.
But as per Gödel's incompleteness theorem and the Halting Problem, math questions (and consequently physics and CS questions) don't always have an answer.
Well, it took about 3 years of non-stop AI hype from the industry and press (and constant ignoring of actual experts) until finally the perception seems to have shifted in recognising it as another bubble. So I wouldn't say any lessons were learned. Get ready for the next bubble when the crypto grifters that moved to "AI" will soon move on the to the NEXT-BIG-THING!
“We have a class of products with deterministic cost and stochastic outputs: a built-in unresolved tension. Users insert the coin with certainty, but will be uncertain of whether they'll get back what they expect. This fundamental mismatch between deterministic mental models and probabilistic reality produces frustration — a gap the industry hasn't yet learned to bridge.”
And all the news today around AI being a bubble -
We’re still learning what we can do with these models and how to evaluate them but industry and capitalism forces our hand into building sellable products rapidly
It is possible (and often desirable) to use different WOFF fonts for italics, and they can look quite different from the standard font.
https://www.cs.utexas.edu/~eunsol/courses/data/bitter_lesson...
https://news.ycombinator.com/item?id=19393432
Parallel with the bitter lesson being that general purpose algorithms that use search and learning leveraged by increasing computational capacity tend to beat out specialized methods that exploit intuition about how cognitive processes work.