6 ms·

Awareness is just continuous propagation of the neural network, be that artificial or biological. The reason thoughts just "appear" is because the brain is cont

by luisml77 11mo ago

Awareness is just continuous propagation of the neural network, be that artificial or biological. The reason thoughts just "appear" is because the brain is continuously propagating signal through the neural network. LLMs also do this during their decoding phase, where they reason continuously with every token that they generate. There is no difference here. Then you say "we don't think most of the times using language exclusively" , but neither do LLMs. What most people fail to realise is that in between each token being generated, black magic is happening in between the transformer layers. The same type of magic you describe. High dimensional. Based on complex concepts. Merging of ideas. Fusion of vectors to form a combined concept. Smart compression. Application of abstract rules. An LLM does all of these things, and more, and you can prove this by how complex their output is. Or, you can read studies by Anthropic on interpretability, and how LLMs do math underneath the transformer layers. How they manipulate information. AGI is not here with LLMs, but its not because they lack reasoning ability. It's due to something different. Here is what I think is truly missing: continuous learning, long term memory, and infinite and efficient context/operation. All of these are tied together deeply, and thus I believe we are but a simple breakthrough away from AGI.

10weirdfishes 11mo ago
There are very significant differences between biological and artificial neural networks. Artificial neural networks are mathematical attempts to replicating how the brain’s neurons work. They are not and were never meant to be 1 to 1 replications. There is the difference in scale, where the “parameters” of human neural networks absolutely dwarf the current LLMs we have today. There is also the fact that they are materially different. The underlying biology and cell structure affects biological neural networks in ways that artificial neural networks just simply dont have access to. The idea of awareness being propagations through the NN is an interesting concept though. I wonder if this idea be proven through monitoring the electrical signals within the brain.
- luisml77 11mo ago
  People like to focus on the differences between the brain and artificial neural networks. I myself believe the only thing that truly matters is that you can form complex functions with the common neuron element. This is achieved via linking lots them together, and by each having a property known as non-linearity. These two things ensure that with neurons you can just about approximate any linear or non-linear function or behaviour. This means you can simulate inside your network pretty much any reality within this universe, its causation and the effects. The deeper your network the more complex the reality you can "understand". Understand just means simulate and run inputs to get outputs in a way that matches the real phenomenon. When someone is said to be "smart", it means they possess a set of rules and functions that can very accurately predict a reality. You mention scale, and while its true the number of neuron elements the brain has is larger than any LLM, its also true the brain is more sparse, meaning much less of the neurons are active at the same time. For a more fair comparison, you can also remove the motor cortex from the discussion, and talk just about the networks that reason. I believe the scale is comparable. In essence, I think it doesn't matter that the brain has a whole bunch of chemistry added into it that artificial neural networks don't. The underlying deep non-linear function mapping capability is the same, and I believe this depth is, in both cases, comparable.
  - tuyiown 11mo ago
    While thinking that current mathematical model replicate accurately a fondamental aspect of biological neural network might be right, it doesn't mean that nothing is missing to achieve the stated goal of true intelligence. Maybe we've just reach the ability the replicate the function of an artificially powered dead brain that would be randomly stimulated and nothing more. Is this really a path to intelligence ?
    - luisml77 11mo ago
      Isn't the brain randomly stimulated already? Even not being dead? Don't you think the complex reasoning is a cause of the neurons themselves and not the stimulation? Animals are alive and are not nearly as smart. Its because their neural networks are not as deep. Its not for the lack of proper chemistry or stimulation.
- laterium 11mo ago
  Why would it have to be a 1 to 1 replication? Isn't that a strawman argument? NNs can basically store the collective of knowledge of humanity in that miniscule amount of neurons. NNs also run at much much higher frequency than human brains. Does that make human brains inferior and not worthy of being called aware by the same line of argumentation? Why do these differences even matter? I can imagine a vastly different form of awareness than humans just fine. They can both be aware and not that similar.
emptysongglass 11mo ago
> Awareness is just continuous propagation of the neural network, be that artificial or biological. The reason thoughts just "appear" is because the brain is continuously propagating signal through the neural network. This is just a claim you are making, without evidence. The way you understand awareness is not through "this is like that" comparisons. These comparisons fall over almost immediately as soon as you turn your attention to the mind itself, by observing it for any length of time. Try it. Go observe your mind in silence for months. You will observe for yourself it is not what you've declared it to be. > An LLM does all of these things, and more, and you can prove this by how complex their output is. Complex output does not prove anything. You are again just making claims. It is astoundingly easy to push an LLM over to collapse into ungrounded nonsense. Humans don't function this way because the two modes of reasoning are not alike. It's up to those making extraordinary claims to prove otherwise. As it is, the evidence does not exist that they behave comparably.
- antonvs 11mo ago
  > This is just a claim you are making, without evidence. Wait, you mean this HN comment didn't casually solve the hard problem of consciousness?
  - emptysongglass 11mo ago
    Haha, well, I would appreciate if comments included more substantive evidence when they make claims like they did. I see a lot of "AGI boosters/doomers" comfortable making big claims without providing research to back what, when challenged, prove to be just their model or feeling of how things function.
    - luisml77 11mo ago
      Feeling how things function is the art of Deep Learning
    - antonvs 11mo ago
      Oh I agree with you, I was just underscoring that. It seems to be a case of people looking at a problem they have little knowledge or understanding of and thinking "how hard can it be"? In this case, the answer is "so hard that philosophers have dubbed it 'the hard problem'".
ozgung 11mo ago
> What most people fail to realise is that in between each token being generated, black magic is happening in between the transformer layers. Thank you by saying that. I think most people have an incomplete mental model for how LLMs work. And it's very misleading for understanding what they really do and can achieve. "Next token prediction" is done only at the output layer. It's not what really happens internally. The secret sauce is at the hidden layers of a very deep neural network. There are no words or tokens inside the network. A transformer is not the simple token estimator that most people imagine.
- luisml77 11mo ago
  Yes, exactly! Finally someone who understands this.

10weirdfishes 11mo ago

There are very significant differences between biological and artificial neural networks. Artificial neural networks are mathematical attempts to replicating how the brain’s neurons work. They are not and were never meant to be 1 to 1 replications. There is the difference in scale, where the “parameters” of human neural networks absolutely dwarf the current LLMs we have today. There is also the fact that they are materially different. The underlying biology and cell structure affects biological neural networks in ways that artificial neural networks just simply dont have access to. The idea of awareness being propagations through the NN is an interesting concept though. I wonder if this idea be proven through monitoring the electrical signals within the brain.

luisml77 11mo ago
People like to focus on the differences between the brain and artificial neural networks. I myself believe the only thing that truly matters is that you can form complex functions with the common neuron element. This is achieved via linking lots them together, and by each having a property known as non-linearity. These two things ensure that with neurons you can just about approximate any linear or non-linear function or behaviour. This means you can simulate inside your network pretty much any reality within this universe, its causation and the effects. The deeper your network the more complex the reality you can "understand". Understand just means simulate and run inputs to get outputs in a way that matches the real phenomenon. When someone is said to be "smart", it means they possess a set of rules and functions that can very accurately predict a reality. You mention scale, and while its true the number of neuron elements the brain has is larger than any LLM, its also true the brain is more sparse, meaning much less of the neurons are active at the same time. For a more fair comparison, you can also remove the motor cortex from the discussion, and talk just about the networks that reason. I believe the scale is comparable. In essence, I think it doesn't matter that the brain has a whole bunch of chemistry added into it that artificial neural networks don't. The underlying deep non-linear function mapping capability is the same, and I believe this depth is, in both cases, comparable.
- tuyiown 11mo ago
  While thinking that current mathematical model replicate accurately a fondamental aspect of biological neural network might be right, it doesn't mean that nothing is missing to achieve the stated goal of true intelligence. Maybe we've just reach the ability the replicate the function of an artificially powered dead brain that would be randomly stimulated and nothing more. Is this really a path to intelligence ?
  - luisml77 11mo ago
    Isn't the brain randomly stimulated already? Even not being dead? Don't you think the complex reasoning is a cause of the neurons themselves and not the stimulation? Animals are alive and are not nearly as smart. Its because their neural networks are not as deep. Its not for the lack of proper chemistry or stimulation.
laterium 11mo ago
Why would it have to be a 1 to 1 replication? Isn't that a strawman argument? NNs can basically store the collective of knowledge of humanity in that miniscule amount of neurons. NNs also run at much much higher frequency than human brains. Does that make human brains inferior and not worthy of being called aware by the same line of argumentation? Why do these differences even matter? I can imagine a vastly different form of awareness than humans just fine. They can both be aware and not that similar.

emptysongglass 11mo ago

> Awareness is just continuous propagation of the neural network, be that artificial or biological. The reason thoughts just "appear" is because the brain is continuously propagating signal through the neural network. This is just a claim you are making, without evidence. The way you understand awareness is not through "this is like that" comparisons. These comparisons fall over almost immediately as soon as you turn your attention to the mind itself, by observing it for any length of time. Try it. Go observe your mind in silence for months. You will observe for yourself it is not what you've declared it to be. > An LLM does all of these things, and more, and you can prove this by how complex their output is. Complex output does not prove anything. You are again just making claims. It is astoundingly easy to push an LLM over to collapse into ungrounded nonsense. Humans don't function this way because the two modes of reasoning are not alike. It's up to those making extraordinary claims to prove otherwise. As it is, the evidence does not exist that they behave comparably.

antonvs 11mo ago
> This is just a claim you are making, without evidence. Wait, you mean this HN comment didn't casually solve the hard problem of consciousness?
- emptysongglass 11mo ago
  Haha, well, I would appreciate if comments included more substantive evidence when they make claims like they did. I see a lot of "AGI boosters/doomers" comfortable making big claims without providing research to back what, when challenged, prove to be just their model or feeling of how things function.
  - luisml77 11mo ago
    Feeling how things function is the art of Deep Learning
  - antonvs 11mo ago
    Oh I agree with you, I was just underscoring that. It seems to be a case of people looking at a problem they have little knowledge or understanding of and thinking "how hard can it be"? In this case, the answer is "so hard that philosophers have dubbed it 'the hard problem'".

ozgung 11mo ago

> What most people fail to realise is that in between each token being generated, black magic is happening in between the transformer layers. Thank you by saying that. I think most people have an incomplete mental model for how LLMs work. And it's very misleading for understanding what they really do and can achieve. "Next token prediction" is done only at the output layer. It's not what really happens internally. The secret sauce is at the hidden layers of a very deep neural network. There are no words or tokens inside the network. A transformer is not the simple token estimator that most people imagine.

luisml77 11mo ago
Yes, exactly! Finally someone who understands this.