41–50 of 699 posts
Earlier quoted context omitted.
It is a stateless text / pixel auto-complete it has no references of self, stop spreading this bs.
is a kv cache not a kind of state? what does statefulness have to do with selfhood? how does a system prompt work at all if these things have no reference to themselves?
This is funny because it’s a silly topic, but I think it shows something extremely seriously wrong with llms. The goblins stand out because it’s obvious. Think of all the other crazy biases latent in every interaction that we don’t notice because it’s not as obvious. Absolutely terrifying that OpenAI is just tossing around that such subtle training biases were hard enough to contain it had to be added to system promp…
> Absolutely terrifying that OpenAI is just tossing around that such subtle training biases were hard enough to contain it had to be added to system prompt. May I introduce you to homo sapiens , a species so vulnerable to such subtle (or otherwise) biases (and affiliations) that they had to develop elaborate and documented justice systems to contain the fallouts? :)
> the evidence suggests that the broader behavior emerged through transfer from Nerdy personality training. > The rewards were applied only in the Nerdy condition, but reinforcement learning does not guarantee that learned behaviors stay neatly scoped to the condition that produced them > Once a style tic is rewarded, later training can spread or reinforce it elsewhere, especially if those outputs are reused in super…
Anthro means human and these are not human. Please do not use anthropology or any derivative of the word to refer to non-human constructs. I suggest Synthetipologists, those who study beings of synthetic origin or type, aka synthetipodes, just as anthropologists study Anthropodes
A plausible theory I've seen going around: https://x.com/QiaochuYuan/status/2049307867359162460
Would love if OpenAI did more of these types of posts. Off the top of my head, I'd like to understand: - The sepia tint on images from gpt-image-1 - The obsession with the word "seam" as it pertains to coding Other LLM phraseology that I cannot unsee is Claude's "___ is the real unlock" (try google it or search twitter!). There's no way that this phrase is overrepresented in the training data, I don't remember people…
It was always funny how easy it was to spot the people using a Studio Ghibli style generated avatar for their Discord or Slack profile, just from that yellow tinging. A simple LUT or tone-mapping adjustment in Krita/Photoshop/etc. would have dramatically reduced it. The worst was you could tell when someone had kept feeding the same image back into chatgpt to make incremental edits in a loop. The yellow filter would…
> the evidence suggests that the broader behavior emerged through transfer from Nerdy personality training. > The rewards were applied only in the Nerdy condition, but reinforcement learning does not guarantee that learned behaviors stay neatly scoped to the condition that produced them > Once a style tic is rewarded, later training can spread or reinforce it elsewhere, especially if those outputs are reused in super…
I call myself an AI theologian. I don't think humans are smart enough to be AInthropologists. The models are too big for that. Nobody really understands what's truly going on in these weights, we can only make subjective interpretations, invent explanations, and derive terminal scriptures and morals that would be good to live by. And maybe tweak what we do a little bit, like OpenAI did here.
no no no, don't stop there, just go full AItheologian, pronounced aetheologian :)
This is funny because it’s a silly topic, but I think it shows something extremely seriously wrong with llms. The goblins stand out because it’s obvious. Think of all the other crazy biases latent in every interaction that we don’t notice because it’s not as obvious. Absolutely terrifying that OpenAI is just tossing around that such subtle training biases were hard enough to contain it had to be added to system promp…
Doesn't seem that surprising or terrifying to me. Humans come equipped with a lot more internal biases (learned in a fairly similar fashion), and they're usually a lot more resistant to getting rid of them. The truly terrifying stuff never makes it out of the RLHF NDAs.
Would love if OpenAI did more of these types of posts. Off the top of my head, I'd like to understand: - The sepia tint on images from gpt-image-1 - The obsession with the word "seam" as it pertains to coding Other LLM phraseology that I cannot unsee is Claude's "___ is the real unlock" (try google it or search twitter!). There's no way that this phrase is overrepresented in the training data, I don't remember people…
Seams, spirals, codexes, recursion, glyphs, resonance, the list goes on and on.
A plausible theory I've seen going around: https://x.com/QiaochuYuan/status/2049307867359162460
This "theory" is simply role playing and has no grounding in reality.
This is funny because it’s a silly topic, but I think it shows something extremely seriously wrong with llms. The goblins stand out because it’s obvious. Think of all the other crazy biases latent in every interaction that we don’t notice because it’s not as obvious. Absolutely terrifying that OpenAI is just tossing around that such subtle training biases were hard enough to contain it had to be added to system promp…
Doesn't seem that surprising or terrifying to me. Humans come equipped with a lot more internal biases (learned in a fairly similar fashion), and they're usually a lot more resistant to getting rid of them. The truly terrifying stuff never makes it out of the RLHF NDAs.
There a great many things people do which are not acceptable in our machines.
Ex: I would not be comfortable flying on any airplane where the autopilot "just zones-out sometimes", even though it's a dysfunction also seen in people.