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ninjadude93 t1_jc1w26o wrote

Congrats you've regurgitated a slightly more technical description of what I said, statistics based word generation. An important piece you missed is the temperature parameter which injects a bit of randomness into the selection of each word from the distribution.

As to your second text block of course we know what happens you just explained it in your first text block. Input is transformed by node weights and passed along between layers getting sequentially transformed by the next weights. It's not magic guy its just mathematics. But according to you this means its fully aware AGI right? Lol jesus you are so far up your own ass

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Surur t1_jc1xcxw wrote

> Input is transformed by node weights and passed along between layers getting sequentially transformed by the next weights.

Think, Forrest, think. Isn't that how the human nervous system works? Or are you one of the magic microtubule guys?

> But according to you this means its fully aware AGI right?

I never said that lol. What I am saying is that this is the most complex machine humans have ever made. You don't appear to appreciate this. You are like an idiot who thinks a car works by turning the ignition and then the wheels roll.

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ninjadude93 t1_jc1zkcj wrote

Sure, thats why its called a neural net because its modeled after human neurons dummy lol but humans don't rely solely on statistical data processing. We have specialized portions of the brain that do things other than simple statistical inference. Maybe pick up some books on the subject?

Ok and? Just because something is complex doesn't automatically imbue it with self awareness or intelligence. Also its not all that complex, the output from training a NN is just a mathematical model. Chatgpt happens to be a model with billions of parameters but its just a bunch of terms combined together. Humans didnt even need to intervene in the creation of the model in this case. Maybe thats a bit too much for you to wrap your brain around though

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Surur t1_jc20j8z wrote

> We have specialized portions of the brain that do things other than simple statistical inference

So just because you cant physically see the layout of the neural network you don't think it has a specialist structure? Studies in simpler models have shown that LLMs build physical representations of their world model in their layers, but according to you that is just "a bunch of terms combined together"

> Also its not all that complex, the output from training a NN is just a mathematical model.

Again, if you think LLMs only do "simple statistical inference" then replicate the system without using NNs.

Else just admit your ignorance and move on.

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ninjadude93 t1_jc23myl wrote

No you absolute idiot how are you this bad at parsing the point lol. Humans do things other than just statistical inference which is the only mode of operation of NNs. Humans are able to logically reason by deduction rather than inference. Your entire first paragraph has nothing to do with what I said try to stay on topic man.

NNs utility comes from the ability to generate a model in an automated fashion. Again, there's no magic here just math and computational power. If you were able to plot all the input data in a high dimensional space and draw a hyperplane through it would get the exact same model output you get through regular training, people just cant visualize more than 3 dimensions so we use NNs to do this instead.

You clearly lack the basic mathematical background to understand how ML works. I suggest starting with some statistics and calculus and going from there so you can intelligently contribute in the future

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Surur t1_jc244ph wrote

> Humans are able to logically reason by deduction rather than inference.

This is mostly not true lol. For example, I detect a distinct lack of reasoning and logic on your part lol.

So clearly that is not the case, because if you were actually thinking you would see the resemblance and equivalence between how the human brain works and the NN in LLMs.

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ninjadude93 t1_jc26dum wrote

Says the moron who thinks humans lack the ability to reason deductively lol

Maybe if I explain it more simply for you. A NN will never be able to logically reason by way of deduction. This is due to the very nature of its design which is simply a device that takes input data and generates an output mathematical equation. The only way to get a good model is by viewing lots and lots of data. This is statistical inference since you don't seem to know what that is. There's no inner monologue happening within the computer. No intelligence is required at all to simply take data input and run it through a model. NNs take a small important slice of what the human brain is doing but clearly don't capture the whole picture otherwise we'd already have AGI based on NNs and we dont.

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Surur t1_jc2940h wrote

> A NN will never be able to logically reason by way of deduction.

See, what you don't appear to understand, being somewhat below average intelligence, is that deductive reasoning is not native to humans and has to be taught.

Using simple Chain of Thought prompting deductive reasoning is much improved in LLMs.

I hate to break it to you, little ninja, but you are not that much better than ChatGPT.

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ninjadude93 t1_jc2a8j9 wrote

Interesting paper but you still miss the point. The LLM needed to be prompted pretty specifically in the correct direction. It's not reasoning on its own merits and its still generating text based on a statistical distribution of next likely characters rather than examining the problem and formulating an answer then producing the response. A slight difference above your ability to comprehend, but one day you'll get there champ.

Hate to break it to you lil guy but just reposting articles on futurology doesn't make you intelligent

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Surur t1_jc2aoxo wrote

> The LLM needed to be prompted pretty specifically in the correct direction.

And children have to be taught. ChatGPT5 will have this natively built in.

> It's not reasoning on its own merits and its still generating text based on a statistical distribution of next likely characters rather than examining the problem and formulating an answer then producing the response.

Look here little man, do I have to demonstrate again you have no idea what is actually going on inside the black-box of the 96 layers of chatGPT? I guess if you are slow I might have to.

> rather than examining the problem and formulating an answer then producing the response

Again, you are obviously not examining the problem before you are formulating your response. Why don't you try it a bit and see where you get. Take that as a challenge.

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ninjadude93 t1_jc2awkk wrote

Aw you're getting all worked up lol just go back and read the previous responses a little slower again maybe at some point you'll pick up the point again

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Surur t1_jc2cgvn wrote

Lol. Have you run out of things to say? Why don't you employ your logic and reasoning for once.

Lets see:

Humans, when presented with a prompt, produce a response using their neural network, based on training they have received.

LLMs, when presented with a prompt, produce a response using their neural network, based on training they have received.

We do not know in detail how the brain works, though we know how neurons work.

We do not know in detail how the LLMs works, though we know how the GPUs work.

Fact: In most cases it is difficult to differentiate between the output of an average human vs a LLM, and in many cases the output from humans are worse, which is why they find great utility in LLMs like ChatGPT.

LLMs, similar to children, still have deficits in symbolic computation, but developers are making progress in that area.

Conclusion: Little Ninja is no different to a pile of silicon.

BTW I tested ChatGPT's deductive skills:

> Children do not believe LLMs can reason. Little Ninja is a child. What conclusion can we draw? Please lay out your thoughts step by step.

ChatGPT:

> The premise states that "Children do not believe LLMs can reason."

> Little Ninja is a child.

> Therefore, based on the given information, we can conclude that Little Ninja may not believe that LLMs can reason.

Or how about an example not including little ninja.

Q: South Africa is at the southern tip of Africa. Chile is at the southern tip of South America. Both countries are far away from the equator. The further you get from the equator, the colder you are. What can you conclude about the climate of South Africa and Chile.

A: Based on the given information, we can conclude that both South Africa and Chile are located far away from the equator, and the statement "the further you get from the equator, the colder you are" suggests that these countries are likely to have colder climates compared to countries located closer to the equator. However, we cannot make any specific conclusions about the climates of South Africa and Chile beyond this generalization, as climate is influenced by a wide range of factors such as altitude, ocean currents, and prevailing winds, which can vary from region to region within a country. Therefore, further information about specific regions within South Africa and Chile would be needed to make more detailed conclusions about their climates.

Or:

Q: South Africa is at the southern tip of Africa. Brazil is in South America and closer to the equator. The further you get from the equator, the colder you are. Which country is warmer and which is colder.

A: Based on the given information and the known relationship between distance from the equator and temperature, we can conclude that Brazil is likely to be warmer than South Africa. This is because Brazil is located closer to the equator than South Africa, meaning that the angle of incidence of the sun's rays is more direct and the sunlight is more concentrated, resulting in more heat energy reaching the surface.

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