- cross-posted to:
- technology@lemmy.zip
- cross-posted to:
- technology@lemmy.zip
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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.
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.
This is an absolutely profound take that I hadn’t seen before; thank you.
It prob came from a few of the fired from various ai places ai ethicists who actually worry about real world problems like the racism/bias from ai systems btw.
The article itself also mentions ideas like this a lot btw. This: “Fan describes how reinforcement learning through human feedback (RLHF), which uses human feedback to condition the outputs of AI models, might come into play. “It’s not too different from asking GPT-4 ‘are you self-conscious’ and it gives you a sophisticated answer,”” is the same idea with extra steps.
Someone is looking for investors…
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?”
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.
I’m also going from the other post which said that this is all simply 90’s era algorithms scaled up. But using that form of neural net stuff, wouldn’t we expect minor mistakes like this from time to time? Neural net does strange unexplained thing suddenly is an ancient tale.
it doesn’t even have to do the ‘are you paying attention’ thing (which shows so many levels of awareness it is weird (but I guess they are just saying it is copying the test idea back at us (which is parroting, not cognition but whatever))) because it is aware, it could just be an error.
Yup, it’s 100% repeating the kind of cliché that is appropriate to the situation. Which is what the machine is designed to do. This business is getting stupider and more desperate by the day.
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.
It’s not self aware, it’s just okay at faking it. Just because some people might believe it doesn’t make it so, people also don’t believe in global warming and think the earth is flat.
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.
who would be equipped to make a sound judgment on such a matter?
Philosophy majors.
Don’t even have to be majors, an introductory course in epistemology does wonders in breaking ones self-confidence, in a good way.
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?