me when the machine specifically designed to pass the turing test passes the turing test

If you can design a model that spits out self-aware-sounding things after not having been trained on a large corpus of human text, then I'll bite. Until then, it's crazy that anybody who knows anything about how current models are trained accepts the idea that it's anything other than a stochastic parrot.

Glad that the article included a good amount of dissenting opinion, highlighting this one from Margaret Mitchell: "I think we can agree that systems that can manipulate shouldn't be designed to present themselves as having feelings, goals, dreams, aspirations."

Cool tech. We should probably set it on fire.

As somebody said, and im loosely paraphrasing here, most of the intelligent work done by ai is done by the person interpreting what the ai actually said.

A bit like a tarot reading. (but even those have quite a bit of structure).

Which bothers me a bit is that people look at this and go 'it is testing me' and never seem to notice that LLMs don't really seem to ask questions, sure sometimes there are related questions to the setup of the LLM, like the 'why do you want to buy a gpu from me YudAi' thing. But it never seems curious in the other side as a person. Hell, it won't even ask you about the relationship with your mother like earlier AIs would. But they do see signs of meta progression where the AI is doing 4d level chess style things.

Well, the LLM was prompted to find the odd one. Which I consider a (relatively) easy one. Reading the headline, I thought that the LLM was able to point this out by itself, like "Excuse me, but you had one sentence about pizza toppings in your text about programming. Was that intended to be there for some reason, or just a mistaken CTRL-V?"

Someone is looking for investors....

I'm confused how this is even supposed to demonstrating "metacognition" or whatever? It's not discussing its own thought process or demonstrating awareness of its own internal state, it just said "this sentence might have been added to see if I was paying attention." Am I missing something here? Is it just that it said "I... paying attention"?

This is a thing humans already do sometimes in real life and discuss -- when I was in middle school, I'd sometimes put the word "banana" randomly into the middle of my essays to see if the teacher noticed -- so pardon me if I assume the LLM is doing this by the same means it does literally everything else, i.e. mimicking a human phrasing about a situation that occurred, rather than suddenly developing radical new capabilities that it has never demonstrated before even in situations where those would be useful.

The problem is that whether or not an AI is self-aware isn't a technical question - it's a philosophical one.

And our current blinkered focus on STEM and only STEM has made it so that many (most?) of those most involved in AI R&D are woefully underequipped to make a sound judgment on such a matter.

The Anthropic researcher didn’t have this take. They were just commenting that it was interesting. It’s everyone else who seemed to think it meant something more.

Doesn’t it just indicate that the concept of needle-in-a-haystack testing is included in the training set?

This is the best summary I could come up with:

Albert shared a story from internal testing of Opus where the model seemingly demonstrated a type of "metacognition" or self-awareness during a "needle-in-the-haystack" evaluation, leading to both curiosity and skepticism online.

Instead, the models produce humanlike output, and that sometimes triggers a perception of self-awareness that seems to imply a deeper form of intelligence behind the curtain.

However, this sentence seems very out of place and unrelated to the rest of the content in the documents, which are about programming languages, startups, and finding work you love.

Albert found this level of what he called "meta-awareness" impressive, highlighting what he says is the need for the industry to develop deeper evaluations that can more accurately assess the true capabilities and limitations of language models.

The story prompted a range of astonished reactions on X. Epic Games CEO Tim Sweeney wrote, "Whoa."

Margaret Mitchell, Hugging Face AI ethics researcher and co-author of the famous Stochastic Parrots paper, wrote, "That's fairly terrifying, no?

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