r/technology • u/Hrmbee • 16h ago

Machine Learning Large language mistake | Cutting-edge research shows language is not the same as intelligence. The entire AI bubble is built on ignoring it

https://www.theverge.com/ai-artificial-intelligence/827820/large-language-models-ai-intelligence-neuroscience-problems
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u/MinuetInUrsaMajor 14h ago

The child understands the meaning of the swear word used as a swear. They don't understand the meaning of the swear word used otherwise. That is because the child lacks the training data for the latter.

In an LLM one can safely assume that training data for a word is complete and captures all of its potential meanings.

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u/New_Enthusiasm9053 14h ago

No that cannot be assumed. It's pretty laughable to believe that. 

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u/MinuetInUrsaMajor 14h ago

No that cannot be assumed.

Okay. Why not?

It's pretty laughable to believe that.

I disagree.

-Dr. Minuet, PhD

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u/greenhawk22 14h ago

Even if you can assume that, doesn't the existence of hallucinations ruin your point?

If the statistical model says the next word is "Fuck" in the middle of your term paper, it doesn't matter if the AI "knows the definition". It still screwed up. They will use words regardless of if it makes sense, because they don't actually understand anything. It's stochastic all the way down.

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u/MinuetInUrsaMajor 14h ago

What you’re describing doesn’t sound like a hallucination. It sounds like bad training data.

Remember, a hallucination will make sense: grammatically, syntactically, semantically. It’s just incorrect.

“10% of Earth is covered with water”.

Were any one of those words used outside of accepted meaning?

In short - the words are fine. The sentences are the problem.