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Comment by sdesol | Hacker News Reader

> Most people recognize that LLM's are not currently super intelligent,

I think calling it intelligent is being extremely generous. Take a look at the following example which is a spelling and grammar checker that I wrote:

https://app.gitsense.com/?doc=f7419bfb27c89&temperature=0.50...

When the temperature is 0.5, both Claude 3.5 and GPT-4o can't properly recognize that GitHub is capitalized. You can see the responses by clicking in the sentence. Each model was asked to validate the sentence 5 times.

If the temperature is set to 0.0, most models will get it right (most of the time), but Claude 3.5 still can't see the sentence in front of it.

https://app.gitsense.com/?doc=f7419bfb27c89&temperature=0.00...

Right now, LLM is an insanely useful and powerful next word predictor, but I wouldn't call it intelligent.

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> I think calling it intelligent is being extremely generous ... can't properly recognize that GitHub is capitalized.

Wouldn't this make chimpanzees and ravens and dolphins unintelligent too? You're asking it to do a task that's (mostly) easy for humans. It's not a human though. It's an alien intelligence which "thinks" in our language, but not in the same way we do.

If they could, specialized AI might think we're unintelligent based on how often we fail, even with advanced tools, pattern matching tasks that are trivial for them. Would you say they're right to feel that way?

Animals are capable of learning. LLMs can not. LLM uses weights that are defined during the training process to decide what to do next. LLM cannot self evaluate based on what it has said. You have to create a new message for it to create a new probability path.

Animals have the ability to learn and grow by themselves. LLMs are not intelligent and I don't see how they can be since they just follow the most likely path with randomness (temperature) sprinkled in.

Ok so just to be clear, that's an entirely different and unrelated argument from the one I responded to.

Second, it's wrong. LLMs can learn within their context window. The main issue now is the limited size of their context window; animals have a lifetime of compressed context and LLMs only have approximately one conversation.

> Ok so just to be clear, that's an entirely different and unrelated argument from the one I responded to.

It honestly made no sense what you were saying so I didn't respond to that directly as I assumed it would be clear from my explanation as to why animals can be intelligent and LLM are not.

> LLMs can learn within their context window.

They don't learn from the context window as much as they use what is in the context window to define a probabilistic path. If you put something in the context window that it was never trained on, it would spit out BS or say it doesn't know.

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