AI capability isn't humanness • Hacker News Board

Re: AI capability isn't humanness

#51

Post by dpark » Wed, Dec 17, 2025, 10:35 PM UTC

emp17344 wrote: post #50

dpark wrote: post #42

Earlier quoted context omitted.

I think you are trying to argue for a very abstract notion of intelligence that is divorced from any practical measurement. I don’t know how else to interpret your claim that inputs are divorced from intelligence (and that we don’t know if the brain in a jar is intelligent). This seems like a very philosophical standpoint, rather than practical. And I guess that’s fine, but I feel like the implication is that if an L…

Intelligence isn’t rigorously defined or measurable, so any conversation about the nature of intelligence will be inherently philosophical. Like it or not, intelligence just is an abstract concept. I’m trying to illustrate that the constraints that apply to LLMs don’t necessarily apply to humans. I don’t believe human intelligence is reliant upon sensory input.

It can’t be both. If intelligence is this abstract and philosophical then the claims about inputs not being relevant for human intelligence are meaningless. It’s equally meaningless to say that constraints on LLM intelligence don’t apply to human intelligence. In the absence of a meaningful definition of intelligence, these statements are not grounded in anything.

The term cannot mean something measurable or concrete when it’s convenient, but be vague and indefinable when it’s not.

Re: AI capability isn't humanness

#52

Post by jeisc » Thu, Dec 18, 2025, 8:40 AM UTC

The human condition is not ascertained through language; it is only expressed through language so truly understandable only to someone who also shares the human condition which certainly is not the case of any LLM.

Re: AI capability isn't humanness

#53

Post by ForceBru » Thu, Dec 18, 2025, 8:52 AM UTC

moffkalast wrote: post #15

ForceBru wrote: post #5

> Compared to humans, LLMs have effectively unbounded training data. They are trained on billions of text examples covering countless topics, styles, and domains. Their exposure is far broader and more uniform than any human's, and not filtered through lived experience or survival needs. I think it's the other way round: humans have effectively unbounded training data. We can count exactly how much text any given mod…

There's only so much information content you can get from a mug though. We get a lot of high quality data that's relatively the same. We run the same routines every day, doing more or less the same things, which makes us extremely reliable at what we do but not very worldly. LLMs get the opposite: sparse, relatively low quality, low modality data that's extremely varied, so they have a much wider breadth of knowledge…

Yep, LLMs have a greater breadth of knowledge, but it's shallow. Humans are able to achieve much greater depth because they have more data about the subject.

Re: AI capability isn't humanness

#54

Post by ForceBru » Thu, Dec 18, 2025, 9:14 AM UTC

mdahardy wrote: post #21

ForceBru wrote: post #5

> Compared to humans, LLMs have effectively unbounded training data. They are trained on billions of text examples covering countless topics, styles, and domains. Their exposure is far broader and more uniform than any human's, and not filtered through lived experience or survival needs. I think it's the other way round: humans have effectively unbounded training data. We can count exactly how much text any given mod…

This is a fair criticism we should've addressed. There's actually a nice study on this: Vong et al. ( https://www.science.org/doi/10.1126/science.adi1374 ) hooked up a camera to a baby's head so it would get all the input data a baby gets. A model trained on this data learned some things babies do (eg word-object mappings), but not everything. However, this model couldn't actively manipulate the world in the way that…

> LLMs are still trained on significantly more data pretty much no matter how you look at it ... 10-15 million words ... vs trillions for LLMs

I don't know how to count the amount of words a human encounters in their life, but it does seem plausible that LLMs deal with orders of magnitude more words. What I'm saying is that words aren't the whole picture.

Humans get continuous streams of video, audio, smell, location and other sensory data. Plus, you get data about your impact on the world and the world's impact on you: what happens when you move this thing? What happens when you touch some fire? LLMs don't have this yet, they only have abstract symbols (words, tokens).

So when I look at it from this "sensory" perspective, LLMs don't seem to be getting any data at all here.

Re: AI capability isn't humanness

#55

Post by aisdijoa » Sun, Dec 21, 2025, 7:32 PM UTC

mdahardy wrote: post #22

zkmon wrote: post #8

I think there might be a slight bias in this blog article in favor of their product/service. Their human verification service probably needs AI to have less humanness. But as we saw over the course of recent months or years, AI outputs are becoming more indistinguishable for human output.

Our main argument is that outputs will become increasingly indistinguishable, but the processes won't. E.g. in 5 years if you watch an AI book a flight it will do it in a very non-human way, even if it gets the same flight you yourself would book.

I was reading about your company and really liked your post about benchmarking bot detection systems (https://research.roundtable.ai/bot-benchmarking/).

I find myself wondering why Google isn't doing as good a job as you guys. In particular, I'm wondering if you think they've been kind of lazy about the problem because they don't see captcha detection as faring particularly poorly, and perhaps once AI agents really start taking off and becoming prevalent, then Google will buckle down, at which point they'll be able to hone their troves of data to build a newer captcha even better than yours. Or is there an additional secret sauce you guys have?

That kind of leads me to my other question-I assume your secret sauce is the cognitive science, stroop-esque approach to bot detection (which I think is brilliant in the abstract). But I'm curious how that scales. Like, do you go one-by-one for each website you have a partnership with and figure out how a human would likely use the site, or do you use general techniques (besides the obvious ones like typing speed and mouse movements, which almost certainly Google could implement too if it decided to buckle down). Like, can you scale some broad stroop task across websites?

By the way, asking all of this out of admiration. You guys are doing really clever work!