[sublinear]

Yeah wow fascinating! It's almost like LLM output quality was never the point from a business perspective.

Real people think in concepts and experiences instead of words. The words are not so important to get the idea across, but LLMs only model language.

The problem is fundamental. There's no workaround. Averaging out word usage might even make the problem worse.

[rpdillon]

> Real people think in concepts and experiences instead of words.

I learned about this opinion recently. It's interesting to me, because I very much think through words. I have an internal monologue that is running most of the time, and I often talk to myself, just start writing, or even record myself and transcribe to work through ideas, proposals, risks, etc. My understand is that some people don't have an internal monologue, and think purely in concept form. I was never like that.

[optimalquiet]

Agreed. I think in and visualize in words, generally not images. I see something akin to [Spreeder](https://www.spreeder.com/app.html) in my head most of the time, and I often can somatically feel punctuation.

[theowaway213456]

This sort of take is so tired and boring, and frankly has zero grounding in reality.

"LLMs will never <X>" is constantly being disproven every time they scale up to the next 10X and apply architectural improvements.

Their internal representations are so cryptic and complex that even the top AI researchers don't really know how they work or what their limits are. No one is going to take you seriously as a rando HN user if you're claiming to know better than them.

[BearOso]

> Their internal representations are so cryptic and complex that even the top AI researchers don't really know how they work or what their limits are. No one is going to take you seriously as a rando HN user if you're claiming to know better than them.

We know exactly how they work. When we say they're impossible to analyze, i.e. for particular traits like this, it means that the data model is so big that tracing it would be logistically impossible because of the scale involved and time constraints.

For comparison, suppose you tried to analyze all the nooks and crannies of the Amazon watershed to find out why a particular rock appears at the delta. You could follow it back to the exact tributary, but it'll take forever, and is it worth the effort when you're going to start from scratch with the next rock?

[rsoto2]

We know exactly how LLMs work. you don't understand how they work and so you think they are free of physical limits like scaling. There are several rudimentary articles on hackernews for you to peruse to understand weights and scaling. IMO the "magic" derived from LLMs comes from one of humanity's actual greatest inventions and constantly evolving tools: language.

[sublinear]

I'm not claiming to know better than researchers. They do know how they work, and so does everyone else, except you I guess.

The research goals were and still are clearly distinct from the business goals.

[Zambyte]

Understanding how transformers work does not mean understanding how they compose into the capabilities we observe. The former is concretely understood. The latter is an active area of research where no, we (in general, including you) do not understand how they work.

[rsoto2]

What capabilities? Regurgitating a collage of training data? Again it's pretty easy to understand why this happens. The "magic" you are perceiving is language itself not these models. Language is a constantly evolving tool and we constantly imbue it with our collective knowledge.

[sublinear]

The "capabilities you observe" are the actual psychological phenomena at hand here. There's zero chance that branch of research will meaningfully improve the output. That's simply not the point.

This isn't people merely annoyed with repetition. This is the majority of people realizing the limitations of LLMs. Why would researchers give a flying crap about the ignorance of the business world and the public?

[AlexandrB]

How can their internal representation represent "concepts" when the training data is all words? There's no possible experience of the world there. No input other than a bunch of imperfect labels we created for stuff.

[sebastiennight]

This is a wild argument.

If I use the word "semantic", do you have a concept of what it means?

If so, can you please share which of your senses have shaped the world experience that inform this concept? What have you smelled, tasted, caressed, that informed this concept outside of words?

If I make up the word "polysemantic", do you need to recall a personal experience of polyamory to understand it, or could you possibly use your concept of "poly" and your concept of "semantic" to figure out this new concept?

[rsoto2]

Yes. When someone is teaching you language as a baby you have eyes and ears and 100 million nerve endings and constant "training" to understand language. You cannot understand the word "semantics" as a human without this crucial "training" step. My god you people will pull out the most bs metaphors to justify being in awe(and debt) to a software program.

[sublinear]

Yes, but are you claiming that LLMs perform more specific acts of cognition beyond organizing information?

[sebastiennight]

I'm puzzled by this question.

Does the material universe perform any other acts than organizing information?

I feel like you're trying to make me argue a position I'm not defending here.

[robotresearcher]

What does 'organizing information' exclude?

[visarga]

> There's no possible experience of the world there. No input other than a bunch of imperfect labels we created for stuff.

The brain too sits locked inside a bone box and only gets a bundle of unlabeled nerves connecting it to the outside. How can the brain could possibly experience anything, it only sees patters and patterns of patterns never the real thing?

[sebastiennight]

> a bundle of unlabeled nerves connecting it to the outside

As a species, we do need to up our cable management skills. We're likely not getting augmented humans until we get there.

[rsoto2]

a bone box.. with eyes and 100 million nerve endings to experience the world...

[Applejinx]

No Man's Sky has such a range of possible outputs that in theory, nobody can possibly know how it works or what its limits are. That's the mathematical reality of how many combinations are on tap in that worldgen algorithm.

And yet, how quickly does it cease to surprise you?

Damn right we can tell what AI's limits are. It's palpable, hard to miss. Even the people I know who're all-in on the technology are pretty jaded by now.