OC below by @[email protected]
What called my attention is that assessments of AI are becoming polarized and somewhat a matter of belief.
Some people firmly believe LLMs are helpful. But programming is a logical task and LLMs can’t think - only generate statistically plausible patterns.
The author of the article explains that this creates the same psychological hazards like astrology or tarot cards, psychological traps that have been exploited by psychics for centuries - and even very intelligent people can fall prey to these.
Finally what should cause alarm is that on top that LLMs can’t think, but people behave as if they do, there is no objective scientifically sound examination whether AI models can create any working software faster. Given that there are multi-billion dollar investments, and there was more than enough time to carry through controlled experiments, this should raise loud alarm bells.
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:
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.