ML promises to be profoundly weird

Post by masfuerte » Wed, Apr 08, 2026, 4:38 PM UTC

perching_aix wrote: post #42

This is like all the usual anti-LLM talking points and sentiments fused together. Doesn't it get boring? I like using these models a lot more than I stand hearing people talk about them, pro or contra. Just slop about slop. And the discussions being artisanal slop really doesn't make them any better. Every time I hear some variation of bullshitting or plagiarizing machines, my eyes roll over. Do these people think th…

Post by nradov » Wed, Apr 08, 2026, 4:39 PM UTC

the_snooze wrote: post #39

bensyverson wrote: post #27

Earlier quoted context omitted.

> the technology in its current state still isn't fit for purpose. This is a broad statement that assumes we agree on the purpose. For my purpose, which is software development, the technology has reached a level that is entirely adequate. Meanwhile, sports trivia represents a stress test of the model's memorized world knowledge. It could work really well if you give the model a tool to look up factual information in…

There's nothing in these models that say its purpose is software development. Their design and affordances scream out "use me for anything." The marketing certainly matches that, so do the UIs, so do the behaviors. So I take them at their word, and I see that failure modes are shockingly common even under regular use. I'm not out to break these things at all. I'm being as charitable and empirical as I can reasonably…

Post by nothinkjustai » Wed, Apr 08, 2026, 4:40 PM UTC

ajross wrote: post #3

bensyverson wrote: post #2

I get the frustration, but it's reductive to just call LLMs "bullshit machines" as if the models are not improving. The current flagship models are not perfect, but if you use GPT-2 for a few minutes, it's incredible how much the industry has progressed in seven years. It's true that people don't have a good intuitive sense of what the models are good or bad at (see: counting the Rs in "strawberry"), but this is more…

> it's reductive to just call LLMs "bullshit machines" as if the models are not improving This is true, but I prefer to think of it as "It's delusional to pretend as if human beings are not bullshit machines too". Lies are all we have. Our internal monologue is almost 100% fantasy. Even in serious pursuits, that's how it works. We make shit up and lie to ourselves, and then only later apply our hard-earned[1] skill p…

Post by marssaxman » Wed, Apr 08, 2026, 4:41 PM UTC

knowaveragejoe wrote: post #51

Frieren wrote: post #47

Earlier quoted context omitted.

> Some people point at LLMs confabulating No. LLMs do not confabulate they bullshit. There is a big difference. AIs do not care, cannot care, have not capacity to care about the output. String tokens in, string tokes out. Even if they have all the data perfectly recorded they will still fail to use it for a coherent output. > Collapsing the dimensionality is going to be lossy, which means it will have gaps between wh…

> No. LLMs do not confabulate they bullshit. There is a big difference. AIs do not care, cannot care, have not capacity to care about the output. String tokens in, string tokes out. Even if they have all the data perfectly recorded they will still fail to use it for a coherent output. Isn't "caring" a necessary pre-requisite for bullshitting? One either bullshits because they care, or don't care, about the context.

Post by delusional » Wed, Apr 08, 2026, 4:42 PM UTC

_dwt wrote: post #58

I have a question for all the "humans make those mistakes too" people in this thread, and elsewhere: have you ever read, or at least skimmed a summary of, "The Origin of Consciousness in the Breakdown of the Bicameral Mind"? Did you say "yeah, that sounds right"? Do you feel that your consciousness is primarily a linguistic phenomenon? I am not trying to be snarky; I used to think that intelligence was intrinsically…