81–90 of 117 posts
If this is true and easily computable, this might have big impact in AI safety, as it seems to be really lacking today.
"Vectors seem inadequate for capturing the structure of language, logic, and other cognitive domains, yet neural networks achieve impressive performance in these areas". Missing the forest for the trees? Aren't neural networks modeled after biological systems? Our brains are obviously able to contain symbolic structure despite not having a "symbol processing unit".
People really overstate the relationship between ANNs and the brain, they have very different mechanisms and only have a similarity if you squint at 100000 feet. ANNs don't have neurotransmitters or even action potentials.
That is, yes, ANNs are not brains. There are countless differences. But are there differences at the computational level? ANNs are meant to model brain computation, not brain biology.
(There is still a lot to debate there, I'm not saying "ANNs are perfect computational models for the brain")
The big questions I’m taking away are: (1) they are claiming to produce apparently bijective closed-form symbolic representations/approximations of, among other things, LLMs. Is evaluating these closed-form representations more computationally efficient? The implications of that are potentially huge. It would be essentially analytic distillation. Fable on a chip and not a data center would be important — and disrupti…
Their representation is a key-value store that they embed via a tensor product to reconstruct the vectors the model produces. The catch is that it works best if the key-value mapping is task-specific. So if you already know how to solve the task the model is performing and can transform the input into a data structure that makes it easy to just read off the answer, you can probably also recover the model output. That…
Well that's good to hear. Would have been rather exasperating to find out we could have somehow gotten Fable or Sol out of sufficiently advanced sparse-coding ages ago.
e.g. quickarxiv.org/abs/2608.29530
Reading stuff like this (as a layman), diminishing these things as 'Next token predictors' seems absurdly reductive. At some point we'll need to concede that 'selection' is a better term for this than prediction.
> diminishing these things as 'Next token predictors' seems absurdly reductive. This shows a deep misunderstanding of the paper's claims, which in no way challenge the established view that these bots are next-token predictors. Regardless, if all you want is a next-token selector , save your money and roll a die.
No, this shows an appreciation of the symbolic richness behind that token 'prediction' which the paper leads on.
> Regardless, if all you want is a next-token selector, save your money and roll a die.
Tell me, where is the emergent symbology guiding that dice?
For anyone like me who finds theory a little dense, you can prepend "quick" to an arxiv link to get a blogpost-style summary e.g. quickarxiv.org/abs/2608.29530
Earlier quoted context omitted.
Too shallow of a dismissal, and you don't determine what everyone else takes seriously. It's been several years now of LLMs only appeasing those with low expectations and inexperience. Unless the only goal was generating boilerplate or really sloppy proofs of concept, LLMs are a waste time for everyone else. This argument is so over already. We're all just hoping for a soft landing when the hangover really kicks in.
You are disconnected from reality. The whole industry is already completely dominated by LLMs generating code. Bury your head in the sand all you want. This is not about low expectations or inexperience at all. Your condescending tone doesn't make you look smarter, it makes you look like an Amish who expects the industrial revolution is temporary and soon people will come to their senses and stop using all this nonse…
"Amish do not view technology as evil, and individuals may petition for acceptance of a particular technology in the local community" - https://en.wikipedia.org/wiki/Amish_way_of_life#Use_of_moder...
See also https://thereader.mitpress.mit.edu/how-the-amish-let-technol... about some Amish use of cell phones with adapters to be more payphone/landline-like and https://news.ycombinator.com/item?id=21349989 was a discussion about the use of pneumatic machinery by the Amish.
Earlier quoted context omitted.
Yup and the industry is worse than ever. Maybe you forgot that important tidbit? People are using them because they're being shoved down their throats and they're complacent. Software quality, maintainability, exploitability, morale, competency are all at all-time lows and just worsening. It's really bad to defend this.
I spent the last 6 months reviewing all of the AI generated code primarily with gpt 5.3 codex but after I bought the subscription I also used gpt 5.5 and although I was constantly rejecting the bad code and I was mostly happy with the end result. Then they removed the approve everything manually mode and I thought, maybe I'm the one out of touch, I should try vibe coding. I gave it a big spec of things to implement a…
The big questions I’m taking away are: (1) they are claiming to produce apparently bijective closed-form symbolic representations/approximations of, among other things, LLMs. Is evaluating these closed-form representations more computationally efficient? The implications of that are potentially huge. It would be essentially analytic distillation. Fable on a chip and not a data center would be important — and disrupti…
Earlier quoted context omitted.
People really overstate the relationship between ANNs and the brain, they have very different mechanisms and only have a similarity if you squint at 100000 feet. ANNs don't have neurotransmitters or even action potentials.
But neurotransmitters and action potentials don't help in modeling symbolic structure. That is, yes, ANNs are not brains. There are countless differences. But are there differences at the computational level? ANNs are meant to model brain computation, not brain biology. (There is still a lot to debate there, I'm not saying "ANNs are perfect computational models for the brain")
This is exactly why Fodor argues that psychology should be explained on its on level with symbols rather than appealing to neurology. But if you're interested in modeling symbols, there's much better options than ANNs (see nearly any programming language ever).
>ANNs are meant to model brain computation
But we don't really know how that works! So if you know if you're not modelling the low-level behaviour right, you can't assume that there's a correspondence of the higher level computation when you don't really know what that higher level computations are.