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What happens when people don't understand how AI works

theatlantic.com

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Re: What happens when people don't understand how AI works

#171

Post by kenjackson »

jhedwards wrote: post #156
AlecSchueler wrote: post #148

Earlier quoted context omitted.

The question is what's different in your own "thinking?"

Thinking in humans is prior to language. The language apparatus is embedded in a living organism which has a biological state that produces thoughts and feelings, goals and desires. Language is then used to communicate these underlying things, which themselves are not linguistic in nature (though of course the causality is so complex that the may be _influenced_ by language among other things).

This is really over indexing on language for LLMs. It’s about taking input and generating output. Humans use different types of senses as their input, LLMs use text.

What makes thinking an interesting form of output is that it processes the input in some non-trivial way to be able to do an assortment of different tasks. But that’s it. There may be other forms of intelligence that have other “senses” who deem our ability to only use physical senses as somehow making us incomplete beings.

Re: What happens when people don't understand how AI works

#172

Post by tim333 »

>Demis Hassabis, [] said the goal is to create “models that are able to understand the world around us.”

>These statements betray a conceptual error: Large language models do not, cannot, and will not “understand” anything at all.

This seems quite a common error in the criticism of AI. Take a reasonable statement about AI not mentioning LLMs and then say the speaker (nobel prize winning AI expert in this case) doesn't know what they are on about because current LLMs don't do that.

Deepmind already have project Astra, a model but not just language but also visual and probably some other stuff where you can point a phone at something and ask about it and it seems to understand what it is quite well. Example here https://youtu.be/JcDBFAm9PPI?t=40

Re: What happens when people don't understand how AI works

#173

Post by throwawaymaths »

i think this author doesnt fully understand how llms work either. Dismissing it as "a statistical model" is silly. hell, quantum mechanics is a statistical model too.

moreover, each layer of an llm imbues the model with the possibility of looking further back in the conversion and imbuing meaning and context through conceptual associations (thats the k-v part of the kv cache). I cant see how this doesn't describe, abstractly, human cognition. now, maybe llms are not fully capable of the breadth of human cognition or have a harder time training to certain deeper insight, but fundamentally the structure is there (clever training and/or architectural improvements may still be possible -- in the way that every CNN is a subgraph of a FCNN that would be nigh impossible for a FCNN to discover randomly through training)

to say llms are not smart in any way that is recognizable is just cherry-picking anecdotal data. if llms were not ever recognizably smart, people would not be using them the way they are.

Re: What happens when people don't understand how AI works

#174

Post by NoMoreNicksLeft »

tim333 wrote: post #172

>Demis Hassabis, [] said the goal is to create “models that are able to understand the world around us.” >These statements betray a conceptual error: Large language models do not, cannot, and will not “understand” anything at all. This seems quite a common error in the criticism of AI. Take a reasonable statement about AI not mentioning LLMs and then say the speaker (nobel prize winning AI expert in this case) doesn'…

>Deepmind already have project Astra, a model but not just language but also visual and probably some other stuff where you can point a phone at something and ask about it and it seems to understand what it is quite well.

Operative phrase "seems to understand". If you had some bizarre image unlike anything anyone's ever seen before and showed it to a clever human, the human might manage to figure out what it is after thinking about it for a time. The model could never figure out anything, because it does not think. It's just a gigantic filter that takes known-and-similar images as input, and spits out a description on the other side, quite mindlessly. The language models do the same thing, do they not? They take prompts as inputs, and shit output from their LLM anuses based on those prompts. They're even deterministic if you take the seeds into account.

We'll scale all those up, and they'll produce ever-more-impressive results, but none of these will ever "understand" anything.

Re: What happens when people don't understand how AI works

#175

Post by kenjackson »

tempodox wrote: post #125
nosianu wrote: post #70

Earlier quoted context omitted.

> So any and all human communication is divination in your book? Words from an AI are just words. Words in a human brain have more or less (depending on the individual's experiences) "stuff" attached to them: From direct sensory inputs to complex networks of experiences and though. Human thought is mainly not based on words. Language is an add-on. (People without language - never learned, or sometimes temporarily dis…

I can only agree with you. And I find it disturbing that every time someone points out what you just said, the counter argument is to reduce human experience and human consciousness to the shallowest possible interpretation so they can then say, “look, it's the same as what the machine does”.

I think it’s because the brain is simply a set of chemical and electrical interactions. I think some believe when we understand how the brain works it won’t be some “soulful” other worldly explanation. It will be some science based explanation that will seem very unsatisfying to some that think of us as more than complex machines. The human brain is different than LLMs, but I think we will eventually say “hey we can make a machine very similar”.

Re: What happens when people don't understand how AI works

#176

Post by mmsc »

This can be generalized to "what happens when people don't understand how something works". In the computing world, that could be "undefined behavior" (of which itself is .. defined as undefined) in the C programming language, or anything as simple as "functionality people didn't know because they didn't read the documentation"

Re: What happens when people don't understand how AI works

#177

Post by chasil »

AlecSchueler wrote: post #148
duxup wrote: post #141

Earlier quoted context omitted.

The terminology is so confusing in AI right now. I use LLMs, I enjoy them, I'm more productive with them. Then I go read a blog from some AI devs and they use terms like "thinking" or similar terms. I always have to ask "We're still s stringing words together with math right? Not really thinking right?" The answer is always yes ... but then they go back to using their wonky terms.

The question is what's different in your own "thinking?"

The platform that we each hold is the most powerful abstract analysis machine known to exist.

It may be, by the end of my life, that this will no longer be true. That would be poignant.

Re: What happens when people don't understand how AI works

#178

Post by EMM_386 »

fer wrote: post #115
EMM_386 wrote: post #88

> These statements betray a conceptual error: Large language models do not, cannot, and will not "understand" anything at all. They are not emotionally intelligent or smart in any meaningful or recognizably human sense of the word. This is terrible write-up, simply because it's the "Reddit Expert" phenomena but in print. They "understand" things. It depends on how your defining that. It doesn't have to be in its trai…

> More means more You could have used "loool" vs "loooooool", "xDD" vs "xDDDDDDDDD", using flags doesn't change a whole lot.

Did I say it did!?

These are the type of responses that REALLY will drive me nuts.

I never said the flag emojis were special.

I've been a software engineers for almost 30 years.

I know what Unicode code pages are.

This is not helpful. How is my example missing your definition of understanding?

Replace the flags with yours if it helps ... same thing.

It's not the flags it's the understanding of what they are. They can be pirate ships or cats.

In my example they are surrender flags, because that is logical given the conversation.

It will "understand" that too. But the article says it can't do that. And the article, sorry, is wrong.

Re: What happens when people don't understand how AI works

#179

Post by AlecSchueler »

jsdalton wrote: post #159
jhedwards wrote: post #156

Earlier quoted context omitted.

Thinking in humans is prior to language. The language apparatus is embedded in a living organism which has a biological state that produces thoughts and feelings, goals and desires. Language is then used to communicate these underlying things, which themselves are not linguistic in nature (though of course the causality is so complex that the may be _influenced_ by language among other things).

Agreed. Many animals without language show evidence of thinking (e.g. complex problem solving skills and tool use). Language is clearly an enabler of complex thought in humans but not the entire basis of our intelligence, as it is with LLMs.

But having language as the basis doesn't mean it isn't intelligence, right? At least I see no argument for that in what's being said. Stability can come from a basis of steel but it can also have a basis of wood.

Re: What happens when people don't understand how AI works

#180

Post by intended »

lordnacho wrote: post #112
intended wrote: post #87

Earlier quoted context omitted.

This isn’t that hard, to be honest. And I’m not just saying this. One school of thought is - the output is indistinguishable from what a human would produce given these questions. Another school of thought is - the underlying process is not thinking in the sense that humans do it Both are true. For the lay person, calling it thinking leads to confusions. It creates intuitions that do not actually predict the behavior…

This is maybe the best response thus far. We can say that there's no real modelling capability inside these LLMs, and that thinking is the ability to build these models and generate predictions from them, reject wrong models, and so on. But then we must come up with something other than opening up the LLM to look for the "model generating structure" or whatever you want to call it. There must be some sort of experime…

Heh, this phrasing has resulted in 2 “best response” type comments in the 2 times I’ve used it.

I think maybe it makes sense for people who already have the building blocks in place and just require seeing it assembled.

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