I know you are, but the argument that an LLM doesn’t understand context is incorrect. It’s not human level understanding, but it’s been demonstrated that they do have a level of understanding.
And to be clear, I’m not talking about consciousness or sapience.
I know you are, but the argument that an LLM doesn’t understand context is incorrect
Emphasis mine. I am talking about the textual output. I am not talking about context.
It’s not human level understanding
Additionally, your obnoxiously insistent comparison between LLMs and human beings boils down to a red herring.
Not wasting my time further with you.
[For others who might be reading this: sorry for the blatantly rude tone but I got little to no patience towards people who distort what others say, like the one above.]
I got little to no patience towards people who distort what others say,
My original reply was meant to be tongue-in-cheek, but I guess I forgot about Poe’s law. I’m not a layman, for the record. I’ve worked with AI for over a decade
A better mathematical system of storing words does not mean the LLM understands any of them. It just has a model that represents the relation between words that it uses.
If I put 10 minus 8 into my calculator I get 2. The calculator doesn’t actually understand what 2 means, or what subtracting represents, it just runs the commands that gives the appropriate output.
That’s a bad analogy, because the calculator wasn’t trained using an artificial neural network literally designed by studying biological brains (aka biological neutral networks).
And “understand” doesn’t equate to consciousness or sapience. For example, it is entirely and factually correct to state that an LLM is capable of reasoning. That’s not even up for debate. The accuracy of an LLM’s reasoning capability is one of the fundamental benchmarks used for evaluating its quality.
But that doesn’t mean it’s “thinking” in the way most people consider.
it is entirely and factually correct to state that an LLM is capable of reasoning
Citation needed.
If you’re going to tell me LLMs are modeled after biological brains and capable of reasoning then I call bullshit on your claims that you actually work in AI.
Imagine you put a man in an enclosed room. There is a slot in the wall where messages get passed through written in Chinese. The man does not speak Chinese or even recognize the written language, he just thinks they’re weird symbols.
First the man is shown examples of sequences of symbols to train him. Then he is shown incomplete sequences and asked which symbol comes next. If incorrect he is corrected, if correct he gets cookie. Eventually this man is able to carry on “conversations” with people in Chinese through continued practice.
This man still does not speak Chinese, he is not having reasoned, rational arguments with the people he is conversing with, and if you told him it was a language he’s look at you like your crazy. “There’s no language here, just if I have these symbols and I next put the one that looks like a man wearing a hat they give me a cookie.”
Thinking LLMs are capable of reasoning is the digital equivalent of putting eyes on a pencil then feeling bad when it gets broken in half.
In machine learning, a neural network (also artificial neural network or neural net, abbreviated ANN or NN) is a model inspired by the structure and function of biological neural networks in animal brains
Thinking LLMs are capable of reasoning is the digital equivalent of putting eyes on a pencil then feeling bad when it gets broken in half.
In this paper, we present Reasoning via Planning (RAP), a novel LLM reasoning framework that equips LLMs with an ability to reason akin to human-like strategic planning
Someone trying to sell their LLM to the general public, and therefore simplifying the language to convey a concept is not a source.
These nodes pass data to each other, just like how in a brain, neurons pass electrical impulses to each other.
By that definition my dimmer switch functions like a biological brain because it passes electrical impulses.
In this paper, we present Reasoning via Planning (RAP), a novel LLM reasoning framework that equips LLMs with an ability to reason akin to human-like strategic planning
This prevents LLMs from performing deliber-
ate planning akin to human brains,
So does not function like a brain does.
To overcome the limitations, we propose a new LLM reasoning framework
So it’s a proposal for a new framework to mimic it, not how LLMs currently function
Aaand I’m going to stop checking your sources now. If you’re just going to gish gallop every link from a search page you think agrees with you I’m not going to waste my time reading things you clearly didn’t bother to. It took 5 links to get to something that even looks like a source, and it doesn’t say what you think it does.
Read your sources and make sure they say what you think they do. If you present me with another pile of links and the first one is invalid I won’t bother looking at the 2nd.
What you just did is called “digging a deeper hole”.
Like I said, I’ve worked in the industry for over a decade. What I said isn’t even up for debate. If you had a shred of understanding you know how astoundingly wrong what you said is. In fact, if you had a shred of understanding you just flat out wouldn’t have said it.
Amazon is not a source.
Someone trying to sell their LLM to the general public, and therefore simplifying the language to convey a concept is not a source.
Straight up genetic fallacy.
Wikipedia is not a source.
You’re right. It’s not a “source”. It’s a source aggregator. You know that list of little tiny text at the bottom of each page? Those are “references” from credible sources that are cited.
I’ll give you an example. The quote from Wikipedia I provided has a little “1” and a little “2” right at the end of the sentence. If you click on them it’ll take you to the cited source.
The little “1” will bring you to the following page:
Modeled loosely on the human brain, a neural net consists of thousands or even millions of simple processing nodes that are densely interconnected.
particular network layouts or rules for adjusting weights and thresholds have reproduced observed features of human neuroanatomy and cognition, an indication that they capture something about how the brain processes information.
It resembles the human brain in two respects: The knowledge is acquired by the network through a learning process, and interneuron connection strengths known as synaptic weights are used to store the knowledge.
They imitate somewhat the learning process of a human brain because they learn the relationship between the input parameters and the controlled and uncontrolled variables by studying previously recorded data.
ANN is a computational model that is based on a machine learning technique. It works like a human brain neuron system.
Directly linked to in the Science Direct page from Wikipedia:
Artificial neural networks (ANNs) are computational models that attempt to emulate the architecture and function of the human brain (Russell and Norvig, 1995).
So does not function like a brain does.
Now I know you’re either 14 or just not very smart. You directly quoted the source with This prevents LLMs from performing deliber-
ate planning akin to human brains,
It’s literally in the sentence, it said “deliberate planning akin to human brains”. It doesn’t say anywhere in that sentence that neural networks aren’t modelled after brains and it doesn’t say anything about reasoning (the two things you keep refuting).
Aaand I’m going to stop checking your sources now
Convenient for your “argument”.
Read your sources and make sure they say what you think they do
I have. You just can’t read, have reading comprehension issues, or simply can’t understand them.
If you present me with another pile of links and the first one is invalid I won’t bother looking at the 2nd.
I don’t care if you do. Anyone else who reads these comments will see you’re out of your depth.
I know you are, but the argument that an LLM doesn’t understand context is incorrect. It’s not human level understanding, but it’s been demonstrated that they do have a level of understanding.
And to be clear, I’m not talking about consciousness or sapience.
Emphasis mine. I am talking about the textual output. I am not talking about context.
Additionally, your obnoxiously insistent comparison between LLMs and human beings boils down to a red herring.
Not wasting my time further with you.
[For others who might be reading this: sorry for the blatantly rude tone but I got little to no patience towards people who distort what others say, like the one above.]
My original reply was meant to be tongue-in-cheek, but I guess I forgot about Poe’s law. I’m not a layman, for the record. I’ve worked with AI for over a decade
Ditto. Have a nice day.
Citation needed
Here you go
https://youtu.be/gQddtTdmG_8
A better mathematical system of storing words does not mean the LLM understands any of them. It just has a model that represents the relation between words that it uses.
If I put 10 minus 8 into my calculator I get 2. The calculator doesn’t actually understand what 2 means, or what subtracting represents, it just runs the commands that gives the appropriate output.
That’s a bad analogy, because the calculator wasn’t trained using an artificial neural network literally designed by studying biological brains (aka biological neutral networks).
And “understand” doesn’t equate to consciousness or sapience. For example, it is entirely and factually correct to state that an LLM is capable of reasoning. That’s not even up for debate. The accuracy of an LLM’s reasoning capability is one of the fundamental benchmarks used for evaluating its quality.
But that doesn’t mean it’s “thinking” in the way most people consider.
Citation needed.
If you’re going to tell me LLMs are modeled after biological brains and capable of reasoning then I call bullshit on your claims that you actually work in AI.
Imagine you put a man in an enclosed room. There is a slot in the wall where messages get passed through written in Chinese. The man does not speak Chinese or even recognize the written language, he just thinks they’re weird symbols.
First the man is shown examples of sequences of symbols to train him. Then he is shown incomplete sequences and asked which symbol comes next. If incorrect he is corrected, if correct he gets cookie. Eventually this man is able to carry on “conversations” with people in Chinese through continued practice.
This man still does not speak Chinese, he is not having reasoned, rational arguments with the people he is conversing with, and if you told him it was a language he’s look at you like your crazy. “There’s no language here, just if I have these symbols and I next put the one that looks like a man wearing a hat they give me a cookie.”
Thinking LLMs are capable of reasoning is the digital equivalent of putting eyes on a pencil then feeling bad when it gets broken in half.
Certainly!
In machine learning, a neural network (also artificial neural network or neural net, abbreviated ANN or NN) is a model inspired by the structure and function of biological neural networks in animal brains
Source
A neural network is a method in artificial intelligence that teaches computers to process data in a way that is inspired by the human brain.
Source
A neural network is a machine learning program, or model, that makes decisions in a manner similar to the human brain
Source
*A neural network, or artificial neural network, is a type of computing architecture that is based on a model of how a human brain functions *
Source
Would you like some more citations?
In this paper, we present Reasoning via Planning (RAP), a novel LLM reasoning framework that equips LLMs with an ability to reason akin to human-like strategic planning
Source - Reasoning with Language Model is Planning with World Model
Motivated by the observation that adding more concise CoT examples in the prompt can improve LLM reasoning performance
Source - Microsoft Research
LegalBench - a tool to evaluate the reasoning performance of an LLM in the legal domain.
A paper on benchmarking an LLMs temporal reasoning.
Shall I provide some more?
Wikipedia is not a source.
Amazon is not a source.
Someone trying to sell their LLM to the general public, and therefore simplifying the language to convey a concept is not a source.
By that definition my dimmer switch functions like a biological brain because it passes electrical impulses.
So does not function like a brain does.
So it’s a proposal for a new framework to mimic it, not how LLMs currently function
Aaand I’m going to stop checking your sources now. If you’re just going to gish gallop every link from a search page you think agrees with you I’m not going to waste my time reading things you clearly didn’t bother to. It took 5 links to get to something that even looks like a source, and it doesn’t say what you think it does.
Read your sources and make sure they say what you think they do. If you present me with another pile of links and the first one is invalid I won’t bother looking at the 2nd.
My god you’re thick.
What you just did is called “digging a deeper hole”.
Like I said, I’ve worked in the industry for over a decade. What I said isn’t even up for debate. If you had a shred of understanding you know how astoundingly wrong what you said is. In fact, if you had a shred of understanding you just flat out wouldn’t have said it.
Straight up genetic fallacy.
You’re right. It’s not a “source”. It’s a source aggregator. You know that list of little tiny text at the bottom of each page? Those are “references” from credible sources that are cited.
I’ll give you an example. The quote from Wikipedia I provided has a little “1” and a little “2” right at the end of the sentence. If you click on them it’ll take you to the cited source.
The little “1” will bring you to the following page:
https://news.mit.edu/2017/explained-neural-networks-deep-learning-0414
Here are some excerpts:
Modeled loosely on the human brain, a neural net consists of thousands or even millions of simple processing nodes that are densely interconnected.
particular network layouts or rules for adjusting weights and thresholds have reproduced observed features of human neuroanatomy and cognition, an indication that they capture something about how the brain processes information.
https://www.sciencedirect.com/topics/neuroscience/artificial-neural-network
It resembles the human brain in two respects: The knowledge is acquired by the network through a learning process, and interneuron connection strengths known as synaptic weights are used to store the knowledge.
They imitate somewhat the learning process of a human brain because they learn the relationship between the input parameters and the controlled and uncontrolled variables by studying previously recorded data.
ANN is a computational model that is based on a machine learning technique. It works like a human brain neuron system.
Directly linked to in the Science Direct page from Wikipedia:
https://www.sciencedirect.com/science/article/abs/pii/B9780444528551500118
Artificial neural networks (ANNs) are computational models that attempt to emulate the architecture and function of the human brain (Russell and Norvig, 1995).
Now I know you’re either 14 or just not very smart. You directly quoted the source with This prevents LLMs from performing deliber- ate planning akin to human brains,
It’s literally in the sentence, it said “deliberate planning akin to human brains”. It doesn’t say anywhere in that sentence that neural networks aren’t modelled after brains and it doesn’t say anything about reasoning (the two things you keep refuting).
Convenient for your “argument”.
I have. You just can’t read, have reading comprehension issues, or simply can’t understand them.
I don’t care if you do. Anyone else who reads these comments will see you’re out of your depth.