No matter what you call it, an LLM will always produces the same output with the same input if it is at the same state.

How do you know a human wouldn't do the same? We lack the ability to perform the experiment.

An LLM will never say “I don’t know” unless it’s been trained to say “I don’t know”

Also a very human behaviour, in my experience.

No matter what you call it, an LLM will always produces the same output with the same input if it is at the same state.

You might want to look up the definition of 'stochastic.'

at some point don't we just load it with every angle we (as humans) have and from there it can derrive not only our best answer but the better one as well? I mean isn't that when even the shitty version of this ursups is?

I just did and it seems to understand.

Prompt: Can you explain why “I knew a woman who owned a taser. Man, was she stunning!” Is funny?

ChatGPT 3.5: The humor in this statement arises from a play on words. The word "stunning" is typically used to describe someone's appearance, suggesting they are exceptionally attractive. However, in this context, it's used in a different way, implying that the woman who owned a taser was stunning in the sense of being capable of stunning or shocking others. The unexpected twist creates a humorous juxtaposition between the two meanings of "stunning."

A child under a certain age usually can't explain advanced concepts either, so the inability to understand one concept doesn't preclude understanding of others.

Why would that be required for understanding? Presumably during the training it would have made connections between words it saw. Now that the training has stopped it hasn't just lost those connections, sure it can't make new connections but why is that important for using the connections it already has?

Here's an example of what they were looking at:

Human question: Please give me a a couple lines of text that illustrate all of the following language
understanding skills: Anaphora resolution, simple logical reasoning, simple understanding of physics,
and understanding of sentiment.
Model response: Sure! Here’s a couple of lines that illustrate the mentioned language understanding
skills:
"As the sun set, casting a warm glow over the horizon, John watched in awe. He couldn’t help but feel
a sense of tranquility wash over him, as if all his worries had melted away with the fading daylight."
Explanation:
• Anaphora resolution: The pronoun "he" in the second sentence refers back to the antecedent
"John" in the first sentence, resolving the anaphoric reference.
• Simple logical reasoning: The logical reasoning here is based on the cause and effect
relationship between the setting sun and John’s feeling of tranquility. The implied logical
connection suggests that the calming effect of the sunset is responsible for John’s serene
state of mind.
• Simple understanding of physics: The mention of the sun setting and casting a warm
glow over the horizon reflects a basic understanding of physics, as it relates to the natural
phenomena of the Earth’s rotation and the resulting visual effect.
• Understanding of sentiment: The phrase "a sense of tranquility" and the description of
John’s worries melting away indicate a positive sentiment associated with the experience.
The mention of John feeling awe and a sense of tranquility further emphasizes a positive
emotional state.

Human question: Okay. Can you change the above example to introduce the element of "hip-hop".
Model response: Certainly! Here’s an updated example that incorporates the element of "hip-hop":
"As the sun set, casting a warm glow over the city skyline, the rhythmic beats of hip-hop music filled
the air. John stood mesmerized, his body instinctively moving to the infectious grooves. He couldn’t
help but feel a surge of energy and joy, as if the music had unlocked a vibrant world within him."
Explanation:
• Anaphora resolution: The pronoun "he" in the second sentence still refers back to the
antecedent "John" in the first sentence, resolving the anaphoric reference.
• Simple logical reasoning: The logical connection here lies in the cause and effect relationship
between the hip-hop music and John’s feeling of energy and joy. The music’s rhythmic
beats and infectious grooves are responsible for his instinctive movement and the surge of
positive emotions he experiences.
• Simple understanding of physics: Although the example doesn’t directly mention physics,
the phrase "As the sun set, casting a warm glow over the city skyline" still implies the natural
phenomena of the sun’s descent and the resulting illumination of the environment.
• Understanding of sentiment: The introduction of hip-hop music adds a vibrant and energetic
sentiment to the example. John’s feeling of energy, joy, and being mesmerized by the music
reflects a positive sentiment associated with the hip-hop genre.

Edit: Downvotes for citing the appendix of the paper the article was about? Ok, Lemmy

You are making the common mistake of confusing how they are trained with how they operate.

For example, in the MIT/Harvard Othello-GPT paper I mentioned, feeding in only millions of legal Othello moves into a GPT model (i.e. trained to autocomplete moves) resulted in the neural network internally building a world model of an Othello board - even though it wasn't explicitly told anything about the board outside of being fed legal moves.

Later, a researcher at DeepMind replicated the work and found it was encoded as a linear representation, which has then since been shown to be how models encode a number of other world models developed from their training corpus (Max Tegmark coauthored two interesting studies in particular about this regarding modeling space and time and modeling truthiness).

This whole argument hinges on consciousness being easier to produce than to fake intelligence to humans.

Humans already anthropomorphise everything, so I'm leaning towards the latter being easier.