>As Weizenbaum later wrote, "I had not realized ... that extremely short exposures to a relatively simple computer program could induce powerful delusional thinking in quite normal people."...

That pretty much explain the AI Hysteria that we observe today.

ACCount37 4 hours ago | parent | next [-]

https://en.wikipedia.org/wiki/AI_effect

>It's part of the history of the field of artificial intelligence that every time somebody figured out how to make a computer do something—play good checkers, solve simple but relatively informal problems—there was a chorus of critics to say, 'that's not thinking'.

That pretty much explains the "it's not real AI" hysteria that we observe today.

And what is "AI effect", really? It's a coping mechanism. A way for silly humans to keep pretending like they are unique and special - the only thing in the whole world that can be truly intelligent. Rejecting an ever-growing pile of evidence pointing otherwise.

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qsera 4 hours ago | parent [-]

>there was a chorus of critics to say, 'that's not thinking'.

And they were always right...and the other guys..always wrong..

See, the questions is not if something is the "real ai". The questions is, what can this thing realistically achieve.

The "AI is here" crowd is always wrong because they assign a much, or should I say a "delusionaly" optimistic answer to that question. I think this happens because they don't care to understand how it works, and just go by its behavior (which is often cherry-pickly optimized and hyped to the limit to rake in maximum investments).

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ACCount37 4 hours ago | parent [-]

Anyone who says "I understand how it works" is completely full of shit.

Modern production grade LLMs are entangled messes of neural connectivity, produced by inhuman optimization pressures more than intelligent design. Understanding the general shape of the transformer architecture does NOT automatically allow one to understand a modern 1T LLM built on the top of it.

We can't predict the capabilities of an AI just by looking at the architecture and the weights - scaling laws only go so far. That's why we use evals. "Just go by behavior" is the industry standard of AI evaluation, and for a good damn reason. Mechanistic interpretability is in the gutters, and every little glimpse of insight we get from it we have to fight for uphill. We don't understand AI. We can only observe it.

"What can this thing realistically achieve?" Beat an average human on a good 90% of all tasks that were once thought to "require intelligence". Including tasks like NLP/NLU, tasks that were once nigh impossible for a machine because "they require context and understanding". Surely it was the other 10% that actually required "real intelligence", surely.

The gaps that remain are: online learning, spatial reasoning and manipulation, long horizon tasks and agentic behavior.

The fact that everything listed has mitigations (i.e. long context + in-context learning + agentic context management = dollar store online learning) or training improvements (multimodal training improves spatial reasoning, RLVR improves agentic behavior), and the performance on every metric rises release to release? That sure doesn't favor "those are fundamental limitations".

Doesn't guarantee that those be solved in LLMs, no, but goes to show that it's a possibility that cannot be dismissed. So far, the evidence looks more like "the limitations of LLMs are not fundamental" than "the current mainstream AI paradigm is fundamentally flawed and will run into a hard capability wall".

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qsera 3 hours ago | parent | next [-]

Do yourself a favor and watch this video podcast shared by the following comment very carefully..

https://news.ycombinator.com/item?id=47421522

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ACCount37 2 hours ago | parent [-]

Frankly, I don't buy that LeCun has that much of use to say about modern AI. Certainly not enough to justify an hour long podcast.

Don't get me wrong, he has some banger prior work, and the recent SIGReg did go into my toolbox of dirty ML tricks. But JEPA line is rather disappointing overall, and his distaste of LLMs seems to be a product of his personal aesthetic preference on research direction rather than any fundamental limitations of transformers. There's a reason why he got booted out of Meta - and it's his failure to demonstrate results.

That talk of "true understanding" (define true) that he's so fond of seems to be a flimsy cover for "I don't like the LLM direction and that's all everyone wants to do those days". He kind of has to say "LLMs are fundamentally broken", because if they aren't, if better training is all it takes to fix them, then, why the fuck would anyone invest money into his pet non-LLM research projects?

It is an uncharitable read, I admit. But I have very little charity left for anyone who says "LLMs are useless" in year 2026. Come on. Look outside. Get a reality check.

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qsera an hour ago | parent [-]

My opinions on the matter does not come from any experts and is coming from my own reason. I didn't see that video before I came across that comment.

>"LLMs are useless" in year 2026

Literally no one is saying this. It is just that those words are put into the mouths of the people that does not share the delusional wishful thinking of the "true believers" of LLM AI.

	▲	ACCount37 a minute ago \| parent [-]
		To be honest, I would prefer "I over-index on experts who were top of the line in the past but didn't stay that way" over "my bad takes are entirely my own and I am proud of it". The former has so much more room for improvement. >Literally no one is saying this. Did you not just advise me to go watch a podcast full of "LLMs are literally incapable of inventing new things" and "LLMs are literally incapable of solving new problems"? I did skim the transcript. There are some very bold claims made there - especially when LLMs out there roll novel math and come up with novel optimizations. No, not reliably. But the bar we hold human intelligence to isn't that high either.

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qsera 3 hours ago | parent | prev [-]

Mm..You seem to be consider this to be some mystical entity and I think that kind of delusional idea might be a good indication that you are having the ELIZA effect...

>We don't understand AI. We can only observe it.

Lol what? Height of delusion!

> Beat an average human on a good 90% of all tasks that were once thought to "require intelligence".

This is done by mapping those tasks to some representation that an non-intelligent automation can process. That is essentially what part of unsupervised learning does.

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reverius42 8 hours ago | parent | prev [-]

ELIZA couldn't write working code from an English-language prompt though.

I think the "AI Hysteria" comes more from current LLMs being actually good at replacing a lot of activity that coders are used to doing regularly. I wonder what Weizenbaum would think of Claude or ChatGPT.

	▲	qsera 7 hours ago \| parent [-]
		>ELIZA couldn't write working code from an English-language prompt though. Yea, that is kind of the point. Even such a system could trick people into delusional thinking. > actually good at replacing a lot of activity that coders are used to... I think even that is unrealistic. But that is not what I was thinking. I was thinking when people say that current LLMs will go on improving and reach some kind of real human like intelligence. And ELIZA effect provides a prefect explanation for this. It is very curious that this effect is the perfect thing for scamming investors who are typically bought into such claims, but under ELIZA effect with this, they will do 10x or 100x investment....