81–90 of 151 posts
What a clear and well-written article. I have only a basic understanding of LLM architecture and was able to follow along and gain intuition the whole time!
> I am sure that OpenAI’s GPT-6 Astra is top of mind for everyone right now.
and closed the tab.
Astra was insane until Monday but something happened on tuesday, now it feels like Sol. I grieve for the lost productivity but i hope they may give us the original Astra back.
Alternative theory - it always seems amazing when it first comes out then the novelty wears off and we’re just meh about it. New model is a model is a model. I bought a PS5 Pro and was genuinely blown away by it at first…few weeks later I’m just like…eh it looks pretty good I guess? It’s still the same, I’m just used to it now and the wow factor along a new thing is going. Kinda like that.
Or they are just compute constrained so they have to serve a shittier version. Who knows?
I hate how opaque these companies are. It feels deceptive and evil.
- Jakub Pachocki (OpenAI’s Chief Scientist)
I wonder how helpful this actually is for alignment? Didn't we already determine that they know when they're being evaluated, and they just say what they think you want to hear?
Earlier quoted context omitted.
For sure they quickly move to q8, the output quality difference to bf16 is small compared to the speed/capacity gain
Yeah q8 made so littler difference back when I was testing such things I'd be surprised if people could quickly notice that as a change. It's got to be either further quantized or some other type of optimization that kicks in when people notice the drop.
Anecdatum but I experienced looped cognition on a peculiar combination of substances. I was able to treat thoughts as solid objects and manipulate them iteratively. (Ordinarily they're more like "glimpses" or "flashes" that fade rapidly. So I guess it would be like the mental equivalent of tracers.) I was able to stack thoughts on top of each other, like planks. (I can do something similar or the narrowly but the pla…
That's almost always the problem of course. Wasn't there a quote about the "breakthrough" of "shoes go on feet"?
> manipulate them iteratively. (Ordinarily they're more like "glimpses" or "flashes" that fade rapidly.
This is intriguing. I would describe my normal thought process as iteratively working on a semi-persistent problem held in my mind. Is it different for other people?
Earlier quoted context omitted.
Do you have hard evidence of this assertion?
We can't have hard evidence. It's a SaaS and they own the code and the machine it runs on. So it may be a widespread hallucination. But there's no evidence of that either.
Astra was insane until Monday but something happened on tuesday, now it feels like Sol. I grieve for the lost productivity but i hope they may give us the original Astra back.
Earlier quoted context omitted.
It’s a little more complicated than that. While looped transformers can be unrolled a fixed number of times to save on memory, if loop depth is determined dynamically between tokens, a single transformer can compute any computable function between tokens. To analogize, current transformers run a fixed-length program per step. Any program can be factored into a top-level loop with a fixed-length branching body (an int…
Actually, removing CoT might make models safer, because we can analyze the entire landscape of their potential outputs, rather than a point-sample (we'll never know how close we were to "kill all humans"). By inspecting intermediate vector spaces, we can actually get certainty bounds on how safely the model is behaving (or even trending). Wrote about it here: https://substack.com/home/post/p-214402969
Astra was insane until Monday but something happened on tuesday, now it feels like Sol. I grieve for the lost productivity but i hope they may give us the original Astra back.
It can very well be Sol, no? What stops them from using cheaper model for some requests during "rush" hours or simply use cheaper model for every Nth request.