If you have to use AI - maybe your work insists on it - always demand it cite its sources, hope they are relevant, and go read those instead.
this post was submitted on 10 Jun 2025
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What's the difference between copying a function from stack overflow and copying a function from a llm that has copied it from SO?
LLM are sort of a search engine with advanced language substitution features nothing more nothing less.
But people just love their drama, and others feed on dooming prophecies.
As for the lack of ""scientifically proof of faster software using llm""... What a statement! Give me the scientifically proof of why using neovim is faster or using a lsp is faster, or anything a developer uses while building software is """"scientifically faster"""
Because it's not a plain copy but an Interpretation of SO.
With llm you just have one more layer between you and the information that can distort that information.
And?
The issue is that you should not blindly trust code. Being originally written by a human being is not, by any means, a quality certification.
You asked what's the difference and I just told you.
Are you stupid or something?
Block and reported.
You should not insult people.
Another similar article that's really good:
I fear this is a problem that may never be solved. I mean that people of any intelligence fall for the mind's biases.
There's just too little to be gained feelings-wise. Yeah, you make better decisions, but you're also sacrificing "going with the flow", acting like our nature wants us to act. Going against your own nature is hard and sometimes painful.
Making wrong decisions is objectively worse, leading to worse outcomes, but if it doesn't feel worse (because you're not attributing the effects of the wrong decisions to the right cause, i.e. acting irrationally), then why should a person do it. If you follow the mind's bias towards attributing your problems away from irrationality, it's basically a self-fulfilling prophecy.
Great article.
LLMs can’t think - only generate statistically plausible patterns
Ah still rolling out the old "stochastic parrot" nonsense I see.
Anyway on to the actual article... I was hoping it wouldn't make these basic mistakes:
[Typescript] looks more like an “enterprise” programming language for large institutions, but we honestly don’t have any evidence that it’s genuinely more suitable for those circumstances than the regular JavaScript.
Yes we do. Frankly if you've used it it's so obviously better than regular JavaScript you probably don't need more evidence (it's like looking for "evidence" that film stars are more attractive than average people). But anyway we do have great papers like this one.
Anyway that's slightly beside the point. I think the article is right that smart people are not invulnerable to manipulation or falling for "obviously" stupid ideas. I know plenty of very smart religious people for example.
However I think using this to dismiss LLMs is dumb, in the same way that his dismissal of Typescript is. LLMs aren't homeopathy or religion.
I have used LLMs to get some work done and... guess what, it did the work! Do I trust it to do everything? Obviously not. But sometimes I don't need perfect code. For example recently I asked it to create an example SystemVerilog file for me utilising as many syntax features as possible (testing an auto-formatter). It did a pretty good job. Saved some time. What psychological hazard have I fallen for exactly?
Overall, B-. Interesting ideas but flawed logic.
LLMs can’t think - only generate statistically plausible patterns
Ah still rolling out the old “stochastic parrot” nonsense I see.
Ah still rolling out the old "computers think" pseudo-science.
I have used LLMs to get some work done and… guess what, it did the work!
Ah yes the old pointless vague anecdote.
What psychological hazard have I fallen for exactly?
Promoting pseudo-science.
Overall D. Neither interesting nor new nor useful.
What called my attention is that assessments of AI are becoming polarized and somewhat a matter of belief.
Proceed to write a belief as a statement in the following paragraph
If you think LLMs doesnt think (I won't argue that they arent extremely dumb), please define what is thinking, before continuing, and if your definition of thinking doesn't apply to humans, we won't be able to agree.
I don't think the current common implementation of AI systems are "thinking" and I'll base my argument on Oxford's definitions of words. Thinking is defined as "the process of using one's mind to consider or reason about something". I'll ignore the word "mind" and focus on the word "reason". I don't think what AIs are doing counts as reasoning as defined by Oxford. Let's go to that definition: "the power of the mind to think, understand, and form judgments by a process of logic". I take issue with the assertion that they form judgments. For completeness, but I don't think it's definition is particularly relevant here, a judgment is: "the ability to make considered decisions or come to sensible conclusions".
I think when you ask an LLM how many 'r's there are in Strawberry and questions along this line you can see they can't form judgments. These basic but obscure questions are where you see that the ability to form judgements isn't there. I would also add that if you "form judgments" you probably don't need to be reminded you formed a judgment immediately after forming one. Like if I ask an LLM a question, and it provides an answer, I can convince it that it was wrong whether or not I'm making junk up or not. I can tell it it made a mistake and it will blindly change it's answer whether it made a mistake or not. That also doesn't feel like it's able to reason or make judgments.
This is where all the hype falls flat for me. It feels like sometimes it looks like a concrete wall, but occasionally that concrete wall is made of wet paper. You can see how impressive the tool is and how paper thin it is at the same time. It's cool, it's useful, it's fake, and that's ok. Just be aware of what the tool is.
The burden of proof is on those who say that LLMs do think.
I asked for your definition, I cannot prove something if we do not agree on a definition first.
You also missread what I said, I did not said AI were thinking.
The burden of proof is on the one who made an affirmation.
I'm not the one who made an affirmation which field experts doesn't know the answer.
But depending of your definition of thinking, some can be answered.
I don't think y'all are disagreeing but maybe this sentence is somewhat confusing:
If you think LLMs doesnt think (I won’t argue that they arent extremely dumb), please define what is thinking,
Maybe the "doesnt" shouldn't be there.
No it is here because that's what they claim.
Nobody yet know how it work, we don't know how LLMs process information.
Anyone who claim it really think, or it isn't thinking, is believing, this is not something the current ML field know.
Well, the neural network is given a prefix (series of tokens) and a token, and it spits out how likely is it that the token follows the prefix. Text is generated by calculating this probability for all known tokens, then picking one random, weighted based on the calculated probabilities.
And the brain is made out of neurons that sends electric signals between them and operate muscles.
That doesnt explain how the brain think.
It allows us to conclude that an LLM doesn't "think" about what it is saying. Based on the mechanics, the LLM doesn't even know it's a participant in the conversation.