Wondering if Modern LLMs like GPT4, Claude Sonnet and llama 3 are closer to human intelligence or next word predictor. Also not sure if this graph is right way to visualize it.
the entire thing is an illusion. what is someone supposed to do with this graph
They’re still word predictors. That is literally how the technology works
Yeah, the only question is whether human brains are also just that.
no, they are not. try showing an ai a huge number of pictures of cars from the front. Then show them one car from the side, and ask them what it is.
Show a human one picture of a car from the front, then the one from the side and ask them what it is.
What if the human had never seen or heard of anything similar to cars?
I bet it’d be confused as much as the llm.
That’s why you show him one, before asking what that same car viewed from a different angle is.
I had never seen a recumbent bike before. I only needed to see one to know and recognize one whenever I see one. Even one with a different color or make and model. The human brain definitely works differently.
You know what bicycle are though. And you’re heard of recumbent bikes or things similar to it.
If you had never heard of anything similar at all to bikes, and saw a picture of a recumbent bike from the front only, you’d probably think “ I have no fucking idea what that is”.
Idk man, weird for you to think humans can kinda learn fully about something without all the required context.
you keep missing the fact that I don’t know out of nowhere. You would have just shown me one and told me what it was. Yes of course I’d be able to tell you what it was. You just taught me. With one example.
To understand a recumbent bicycle you have to understand bicycles. To understand bicycles you have to understand wheels. You have to understand humans, and human transportation. What IS transportation. What are roads. What is a pedal. What is steering. How physics works for objects in motion. Etc etc etc etc.
You truly underestimate the amount of context and previous knowledge you need to understand even the simplest things.
A remarkable paper has just come out on this topic.
I’m going to say x=7, y=10. The sum x+y is not 10, because choosing the next word accurately in a complex passage is hard. The x is 7, just based on my gut guess about how smart they are - by different empirical measures it could be 2 or 40.
Modern LLMs are basically really fancy Markov chains.
Human intelligence is a next word predictor.
Change my mind.
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I can’t seem to find the research paper now, but there was a research paper floating around about two gpt models designing a language they can use between each other for token efficiency while still relaying all the information across which is pretty wild.
Not sure if it was peer reviewed though.
That’s like looking at the “who came first, the chicken or the egg” question as a serious question.
Eggs existed long before chickens evolved.
I think you point out the main issue here. Wtf is intelligence as defined by this axis? IQ? Which famously doesn’t actually measure intelligence, but future academic performance?
It could be.
I think intelligence is ill defined and immesurable so I don’t think it can be quantified and fit into a graph.
Your face is a next word predictor.
What about people who don’t speak any language? (Raised by wolves, etc.)
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Elrik.
good god… autophagy… it’s terrible
Hell no. Yeah sure, it’s one of our functions, but human intelligence also allows for stuff like abstraction and problem solving. There are things that you can do in your head without using words.
The way I would classify it is if you could somehow extract the “creative writing center” from a human brain, you’d have something comparable to to a LLM. But they lack all the other bits, and reason and learning and memory, or badly imitate them.
If you were to combine multiple AI algorithms similar in power to LLM but designed to do math, logic and reason, and then add some kind of memory, you probably get much further towards AGI. I do not believe we’re as far from this as people want to believe, and think that sentience is on a scale.
But it would still not be anchored to reality without some control over a camera and the ability to see and experience reality for itself. Even then it wouldn’t understand empathy as anything but an abstract concept.
My guess is that eventually we’ll create a kind of “AGI compiler” with a prompt to describe what kind of mind you want to create, and the AI compiler generates it. A kind of “nursing AI”. Hopefully it’s not about profit, but a prompt about it learning to be friends with humans and genuinely enjoy their company and love us.
That’s literally how llma work, they quite literally are just next word predictors. There is zero intelligence to them.
It’s literally a while token is not “stop”, predict next token.
It’s just that they are pretty good at predicting the next token so it feels like intelligence.
So on your graph, it would be a vertical line at 0.
What is intelligence though? Maybe I’m getting through life just by being pretty good at predicting what to say or do next…
yeah yeah I’ve heard this argument before. “What is learning if not like training.” I’m not going to define it here. It doesn’t “think”. It doesn’t have nuance. It is simply a prediction engine. A very good prediction engine, but that’s all it is. I spent several months of unemployment teaching myself the ins and outs, developing against llms, training a few of my own. I’m very aware that it is not intelligence. It is a very clever trick it pulls off, and easy to fool people that it is intelligence - but it’s not.
But how do you know that the human brain is not just a super sophisticated next-thing predictor that by being super sophisticated manages to incorporate nuance and all that stuff to actually be intelligent? Not saying it is but still.
Because we have reason, understanding. Take something as simple as the XY problem. Humans understand that there are nuances to prompts and questions. I like the XY because a human knows to step back and ask “what are you really trying to do?”. AI doesn’t have that capability, it doesn’t have reasoning to say “maybe your approach is wrong”.
So, I’m not the one to define what it is or on what scale. But I can say that it’s not human intelligence.
This is true if you describe a pure llm, like gpt3
However systems like claude, gpt4o and 1o are far from just a single llm, they are a blend of llm’s other machine learning (like image recognition) some old fashioned code.
Op does ask “modern llm” so technically you are right but i believed they did mean the more advanced “products”
No, unfortunately you are wrong.
Gpt4 is a better version of gpt3.
The brand new one that is allegedly “unhackable” just has a role hierarchy providing rules and that hasn’t been fulled tested in the wild yet.
That is just next word prediction with extra steps.
Now that is fair.
None of which are intelligence, and all of which are catered towards predicting the next token.
All the models have a total reliance on data and structure for inference and prediction. They appear intelligent but they are not.
How is good old fashioned code comparing outputs to a database of factual knowledge “predicting the next token” to you. Or reinforcement relearning and token rewards baked into models.
I can tell you have not actually tried to work with professional ai or looked at the research papers.
Yes none of it is “intelligent” but i would counter that with neither are human beings, we dont even know how to define intelligence.
Agreed
They’re not incompatible, although I think it unlikely AGI will be an LLM. They are all next word predictors, incredibly complex ones, but that doesn’t mean they’re not intelligent. Just as your brain is just a bunch of neurons sending signals to each other, but it’s still (presumably) intelligent.
Intelligence is a measure of reasoning ability. LLMs do not reason at all, and therefore cannot be categorized in terms of intelligence at all.
LLMs have been engineered such that they can generally produce content that bears a resemblance to products of reason, but the process by which that’s accomplished is a purely statistical one with zero awareness of the ideas communicated by the words they generate and therefore is not and cannot be reason. Reason is and will remain impossible at least until an AI possesses an understanding of the ideas represented by the words it generates.
Sure, they ‘know’ the context of a conversation but only by which words are most likely to come next in order to complete the conversation. That’s all they’re trained to do. Fancy vocabulary and always choosing the ‘best’ word makes them really good at appearing intelligent. Exactly like a Sales Rep who’s never used a product but knows all the buzzwords.
This should just be a 1D spectrum line.
</dataviz>
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Allanoi is going to be the name of a 0 INT Warforged character I’ll create ^^
The “i” in LLM stands for “intelligence”
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Are you interested in this from a philosophical perspective or from a practical perspective?
From a philosophical perspective:
It depends on what you mean by “intelligent”. People have been thinking about this for millennia and have come up with different answers. Pick your preference.
From a practical perspective:
This is where it gets interesting. I don’t think we’ll have a moment where we say “ok now the machine is intelligent”. Instead, it will just slowly and slowly take over more and more jobs, by being good at more and more tasks. And just so, in the end, it will take over a lot of human jobs. I think people don’t like to hear it due to the fear of unemployedness and such, but I think that’s a realistic outcome.
