So, even with concrete examples, model haters are still wrong.

You also imply the claim that making the distribution of words as the possible next one visible, somehow makes the whole system not intelligent. I would say the exact opposite is true.

By using the embedding vectors, models are aware of precise placement and relative position of words in this hugely dimensional space. No human is capable of such precision. This enables party tricks of "king plus woman minus man" kind. But this also give us a precise point between any two words, no matter how different. What is on the midpoint between volcano and music, for example. No human can precisely answer that, but an embedding can. And we can see which words are closest to this 700 dimensional point.

You see this menu of words as a weakness, and I say it is in fact a sign of super intelligence. And this is all before any reasoning or attention mechanism is even run.

Yes, models posses intelligence, but it is not a true one.

Then you claim that models do not posses world-building capabilities. But this is simply not true. Even ignoring the whole subgenre of scientific papers on exactly that subject, it is not that hard to build some hypothetical scenarios, big or small, and then witness the ease with which models do navigate those worlds.

This is because you goal is to state how models are not intelligent, but you couldn't attack the generated text itself, so you created a little rider, attached it to the model, and then you attacked the raider.

But, even in that you failed. You compared the source of human randomness in text generation, and called it 'profound' and implied that it is exactly the source of true intelligence. But, then, the temperature, the similar thing in model was "just a randomness slider". Double standard.

A logical fallacy free attack on LLMs would be to show a prompt, and then the response generated by this prompt, where it would be shown that only an entity with no intelligence would generate such a response. Yet, attacks like this are not written here anymore.

I wonder why.

If models can spot 13 years old critical bugs, I think they can also produce fresh code without those bugs. The skillset is the same.

How in the world does the halting problem enters into the picture if my program is bug free or not?

Police, 1980

But he didn't mention that training any model from a set of texts and books is much cheaper than writing those books in the first place.

In other words, it's ok when Anthropic learns from others, but it is not ok when others learn from Anthropic.

You got a perfectly reasonable response, clear, short. Yet, you chose to ignore it and attack the guy by claiming that the fact that LLMs give a reasonable response are his "beliefs", and "unsupported" at that. LoL.

Is you claim that LLMs don't give a reasonable answers? Did you try to ask them some complex questions in the last 12 months?

Or is your line of reasoning more in the line of "they heard all the questions before, and just memorized the answers?"

Or, do you not agree with a statement that giving reasonable answers is reasoning?

In this case it is the "how we dare not trusting all the experts at spaceX."

But even the fallacy itself is applied incorrectly, as we hear zero from anyone else other than the cult leader himself.