That's a mischaracterization. Latent space is simply a (multidimensionally) sorted collection, it's only a piece of the pie. A massive amount of structure is held in the unembedding layer. Generative AI models are a very specific ordering, LLMs a very specific subset of that, and they're hardly the only users of the concept.
I get what the author is going for, and they're on the right track. There is something interesting going on with embedding spaces: When used as the substrate for a neural network, you can effectively treat them as a kind of continuous form of computation. That is, given two functions, you can trivially derive a function which sits exactly between those two, and do so ad infinitum, for any arbitrary program (in theory. Obviously everything materially accessible is finite.) This is only one such manipulation. You can deform a function in an unenumerable amount of ways. Think like a bezier curve path tool in something like Krita or Photoshop, but for a function. You can keep adding points and twist it to your heart's content.
It's wrong to focus on LLMs specifically, as well. This is a much, much broader topic than you realize. Most of the interesting stuff has nothing to do with language models at all. I get a huge chunk of the industry is currently having a stroke over LLMs being able to brute-force problem solving, but if we're to talk philosophy, theory, and so on, we have to get past the surface level misuse of Machine Translation's holy grail. That's like having a conversation about the potential of computation itself, but all you talk about is web browsers, using them interchangeably with "computer".
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invictati
Dear Kevin: AI models don't contain all of human knowledge. They don't even contain, for example, the complete curricula of the least comprehensive K-12 program.
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jschveibinz
Probably the most important thing I've read this month. The key concepts are valuable.
umm4gemm4
Some math related to training on latents, not tokens:
In future, to provide guard rails to models, we will build token flow pipes in mathematical sense. Sort of like Mathematical Engineering.
hmokiguess
This post made me want to watch Everything Everywhere All at Once again
lardosaurusrex
This article is written like someone sat around and wrote out as many potential buzzwords as possible and then came up with definitions after the fact.
inigyou
Infinite Craft is a web game based on combining two things using LLMs, but it's not clear how it works, whether latent space or something else.
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dannyw
This is nonsensical AI slop with so many technical mistakes.
That's a mischaracterization. Latent space is simply a (multidimensionally) sorted collection, it's only a piece of the pie. A massive amount of structure is held in the unembedding layer. Generative AI models are a very specific ordering, LLMs a very specific subset of that, and they're hardly the only users of the concept.
I get what the author is going for, and they're on the right track. There is something interesting going on with embedding spaces: When used as the substrate for a neural network, you can effectively treat them as a kind of continuous form of computation. That is, given two functions, you can trivially derive a function which sits exactly between those two, and do so ad infinitum, for any arbitrary program (in theory. Obviously everything materially accessible is finite.) This is only one such manipulation. You can deform a function in an unenumerable amount of ways. Think like a bezier curve path tool in something like Krita or Photoshop, but for a function. You can keep adding points and twist it to your heart's content.
It's wrong to focus on LLMs specifically, as well. This is a much, much broader topic than you realize. Most of the interesting stuff has nothing to do with language models at all. I get a huge chunk of the industry is currently having a stroke over LLMs being able to brute-force problem solving, but if we're to talk philosophy, theory, and so on, we have to get past the surface level misuse of Machine Translation's holy grail. That's like having a conversation about the potential of computation itself, but all you talk about is web browsers, using them interchangeably with "computer".
Dear Kevin: AI models don't contain all of human knowledge. They don't even contain, for example, the complete curricula of the least comprehensive K-12 program.
Probably the most important thing I've read this month. The key concepts are valuable.
Some math related to training on latents, not tokens:
https://arxiv.org/abs/2605.27734
In future, to provide guard rails to models, we will build token flow pipes in mathematical sense. Sort of like Mathematical Engineering.
This post made me want to watch Everything Everywhere All at Once again
This article is written like someone sat around and wrote out as many potential buzzwords as possible and then came up with definitions after the fact.
Infinite Craft is a web game based on combining two things using LLMs, but it's not clear how it works, whether latent space or something else.
This is nonsensical AI slop with so many technical mistakes.