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> Given the breadth and depth of GPT-4’s capabilities, we believe that it could reasonably be viewed as an early (yet still incomplete) version of an artificial

> Given the breadth and depth of GPT-4’s capabilities, we believe that it could reasonably be viewed as an early (yet still incomplete) version of an artificial general intelligence (AGI) system. I don't know why, but my brain refuses to accept GPT-4 as something close to AGI. Maybe I am wrong. It is hard to believe that our brain is just a bunch of attention layers and neural nets.

sdenton4 4y ago
There's no rule that agi has to have the same architecture as a human...
- robotresearcher 4y ago
  There’s no agreement about what an AGI is or does, let alone how it should do it.
cowmix 4y ago
Conversely, after using ChatGPT-4 (and generally loving it) -- I'm at peace with this maybe fact.
atleastoptimal 4y ago
> It is hard to believe that our brain is just a bunch of attention layers and neural nets. Our brain isn't, but I'd wager the architectural complexity of a physical, neuronal brain is not optimized for all useful mental tasks, and has perhaps a fair amount of local maxima that are near vestigial in overall positive impact on cognition. Just because the human brain model of cognition is the only way nature has been able to create GI doesn't mean it's the only way GI can be attained. The best kind of machine is the simplest one needed to produce a desired outcome.
- georgehill 4y ago
  I agree that GI can have a different implementation compared to our human brain, but one thing is for sure: as of right now, the human brain can become more creative with a fraction of the data consumed by GPT-4. GPT-4 could be AGI, but it feels like cheating to achieve AGI by feeding the entire internet. If someone can build AGI with only the data that humans consume in their lifetime, then that, imho, is the real AGI.
  - Avicebron 4y ago
    or better yet, chuck it in an open plain and see how long it takes to figure out how to attach a rock to a stick and fight a gazelle to refuel it's energy supply.
  - angusturner 4y ago
    I guess the challenge here is that the human mind is not a blank slate, and has been optimized first by billions of years of evolution. If it takes all the data on the internet (or more) to bootstrap AGI, but that system is then capable of leveraging its knowledge to solve new out-of-distribution tasks, that seems like a fair test to me. I agree with the article that we see "sparks" of this generality with GPT4.
  - scubakid 4y ago
    Not sure I would call constant real-time perceptual stimuli since before birth "a fraction of the training data."
  - singularity2001 4y ago
    become more creative with a fraction of the data consumed by GPT-4 not if you understand the input stream of vision as an equivalent input stream of semantic tokens as in multimodal models. under that definition people looking around for 10 years receive much more training data than large language models and thus perform a bit better at zero shot inference.
adroniser 4y ago
Do you think anything digital could ever become conscious?
- georgehill 4y ago
  yes
- serverholic 4y ago
  [dead]
- steve_adams_86 4y ago
  I have a feeling it's like the saying "Any sufficiently advanced technology is indistinguishable from magic". At a certain point they could become practically identical things.
- Mike_12345 4y ago
  The question is whether consciousness is computable. Can a Turing machine be conscious? Probably not. https://www.newscientist.com/article/mg25634130-100-roger-penrose-consciousness-must-be-beyond-computable-physics/ https://www.newscientist.com/article/mg25634130-100-roger-pe... https://www.youtube.com/watch?v=hXgqik6HXc0 https://www.youtube.com/watch?v=hXgqik6HXc0
  - coldtea 4y ago
    Note that Penrose's answer is not the "consensus". Also, Penrose doesn't conver if I recall correctly about modelling the quantum part too. It's just statistics after all.
    - Mike_12345 4y ago
      So the consensus is that consciousness is computable by a Turing machine?
      - coldtea 4y ago
Robotbeat 4y ago
Well it’s not quite that simple. Brains use spiking neural networks, not the kind used typically in artificial neural networks like those used by LLMs. The “weights” can be changed over time, new connections and even new neurons formed. And the number of connections (“weights”) is about 500-1000x more in our brain than GPT-3. The connection topography is a lot different. But ultimately, our brains are still just made of neurons. As far as we know, there isn’t some sort of extreme molecular computing going on (ie memories directly stored in RNA or whatever) or any large scale quantum mechanics (temperature too high). The differences between AI approaches like artificial neural networks and our animal meat brains could be just the difference between a propeller and flapping wings. Same base mechanics (airfoil producing lift as thrust), different substantiation.
- deleted 4y ago
  [deleted]
- thro1 4y ago
  Do you consider that every neuron in the brain has unique DNA and ancestorship ?
  - thro1 4y ago
    It seems no. Those are facts - whoever argue with facts (parent still downvoted?).. is an idiot. https://www.scientificamerican.com/article/scientists-surprised-to-find-no-two-neurons-are-genetically-alike/ https://www.scientificamerican.com/article/scientists-surpri... https://www.science.org/doi/10.1126/science.aab1785 https://www.science.org/doi/10.1126/science.aab1785 - Somatic mutation in single human neurons tracks developmental and transcriptional history (good luck simulating that)
hotpotamus 4y ago
"We are the meat in our heads" is the way I've heard it said that human intelligence is just a physical phenomenon created by our brains. And there was never any reason to believe that intelligence could not arise from other substrates.
carapace 4y ago
It seems clear to me that these systems think in a meaningful sense, but I don't think they are beings. In Cybernetics there is a result that says that any well-regulated system must contain a model of itself. This seems as good a definition as any of a "being", and by this definition these language models don't make the cut.
- Robotbeat 4y ago
  The architecture for large language models is summarized in the training set for large language models. With fairly minimal modification such as via a plug-in, chatGPT and the like are Turing complete and can thus model themselves.
  - carapace 4y ago
    Hmm, then, from first principles, we should expect "ghosts" to arise in those systems. (These will not be the "virtual entities" that people talk to and call by name (Alexa, Cortana, Siri, etc., but more akin to fixed points in the flow of information.)
jltsiren 4y ago
It's a well-established principle in computer science that the input/output behavior of a system may not capture all of its important properties. Take zero-knowledge proofs for example. Their entire point is that they are indistinguishable from randomly generated garbage from a specific distribution. The proofs only gain value if you make causal assumptions about the system that generated them. I don't think systems like GPT-4 can ever be truly intelligent, because they simply output randomly generated garbage from a specific distribution. Their output may eventually be indistinguishable from that of a truly intelligent system, but the causal mechanism behind them is not intelligent. On the other hand, most people lose their ability to think when they are under sufficient pressure (such as fighting for their lives). It's plausible that people are fundamentally no different from systems like GPT-4 in such situations. Then a language model could be a key part of an AGI, but true intelligence would also need higher-level causal mechanisms.

sdenton4 4y ago

There's no rule that agi has to have the same architecture as a human...

robotresearcher 4y ago
There’s no agreement about what an AGI is or does, let alone how it should do it.

cowmix 4y ago

Conversely, after using ChatGPT-4 (and generally loving it) -- I'm at peace with this maybe fact.

atleastoptimal 4y ago

> It is hard to believe that our brain is just a bunch of attention layers and neural nets. Our brain isn't, but I'd wager the architectural complexity of a physical, neuronal brain is not optimized for all useful mental tasks, and has perhaps a fair amount of local maxima that are near vestigial in overall positive impact on cognition. Just because the human brain model of cognition is the only way nature has been able to create GI doesn't mean it's the only way GI can be attained. The best kind of machine is the simplest one needed to produce a desired outcome.

georgehill 4y ago
I agree that GI can have a different implementation compared to our human brain, but one thing is for sure: as of right now, the human brain can become more creative with a fraction of the data consumed by GPT-4. GPT-4 could be AGI, but it feels like cheating to achieve AGI by feeding the entire internet. If someone can build AGI with only the data that humans consume in their lifetime, then that, imho, is the real AGI.
- Avicebron 4y ago
  or better yet, chuck it in an open plain and see how long it takes to figure out how to attach a rock to a stick and fight a gazelle to refuel it's energy supply.
- angusturner 4y ago
  I guess the challenge here is that the human mind is not a blank slate, and has been optimized first by billions of years of evolution. If it takes all the data on the internet (or more) to bootstrap AGI, but that system is then capable of leveraging its knowledge to solve new out-of-distribution tasks, that seems like a fair test to me. I agree with the article that we see "sparks" of this generality with GPT4.
- scubakid 4y ago
  Not sure I would call constant real-time perceptual stimuli since before birth "a fraction of the training data."
- singularity2001 4y ago
  become more creative with a fraction of the data consumed by GPT-4 not if you understand the input stream of vision as an equivalent input stream of semantic tokens as in multimodal models. under that definition people looking around for 10 years receive much more training data than large language models and thus perform a bit better at zero shot inference.

adroniser 4y ago

Do you think anything digital could ever become conscious?

georgehill 4y ago
yes
serverholic 4y ago
[dead]
steve_adams_86 4y ago
I have a feeling it's like the saying "Any sufficiently advanced technology is indistinguishable from magic". At a certain point they could become practically identical things.
Mike_12345 4y ago
The question is whether consciousness is computable. Can a Turing machine be conscious? Probably not. https://www.newscientist.com/article/mg25634130-100-roger-penrose-consciousness-must-be-beyond-computable-physics/ https://www.newscientist.com/article/mg25634130-100-roger-pe... https://www.youtube.com/watch?v=hXgqik6HXc0 https://www.youtube.com/watch?v=hXgqik6HXc0
- coldtea 4y ago
  Note that Penrose's answer is not the "consensus". Also, Penrose doesn't conver if I recall correctly about modelling the quantum part too. It's just statistics after all.
  - Mike_12345 4y ago
    So the consensus is that consciousness is computable by a Turing machine?
    - coldtea 4y ago

Robotbeat 4y ago

Well it’s not quite that simple. Brains use spiking neural networks, not the kind used typically in artificial neural networks like those used by LLMs. The “weights” can be changed over time, new connections and even new neurons formed. And the number of connections (“weights”) is about 500-1000x more in our brain than GPT-3. The connection topography is a lot different. But ultimately, our brains are still just made of neurons. As far as we know, there isn’t some sort of extreme molecular computing going on (ie memories directly stored in RNA or whatever) or any large scale quantum mechanics (temperature too high). The differences between AI approaches like artificial neural networks and our animal meat brains could be just the difference between a propeller and flapping wings. Same base mechanics (airfoil producing lift as thrust), different substantiation.

deleted 4y ago
[deleted]
thro1 4y ago
Do you consider that every neuron in the brain has unique DNA and ancestorship ?
- thro1 4y ago
  It seems no. Those are facts - whoever argue with facts (parent still downvoted?).. is an idiot. https://www.scientificamerican.com/article/scientists-surprised-to-find-no-two-neurons-are-genetically-alike/ https://www.scientificamerican.com/article/scientists-surpri... https://www.science.org/doi/10.1126/science.aab1785 https://www.science.org/doi/10.1126/science.aab1785 - Somatic mutation in single human neurons tracks developmental and transcriptional history (good luck simulating that)

hotpotamus 4y ago

"We are the meat in our heads" is the way I've heard it said that human intelligence is just a physical phenomenon created by our brains. And there was never any reason to believe that intelligence could not arise from other substrates.

carapace 4y ago

It seems clear to me that these systems think in a meaningful sense, but I don't think they are beings. In Cybernetics there is a result that says that any well-regulated system must contain a model of itself. This seems as good a definition as any of a "being", and by this definition these language models don't make the cut.

Robotbeat 4y ago
The architecture for large language models is summarized in the training set for large language models. With fairly minimal modification such as via a plug-in, chatGPT and the like are Turing complete and can thus model themselves.
- carapace 4y ago
  Hmm, then, from first principles, we should expect "ghosts" to arise in those systems. (These will not be the "virtual entities" that people talk to and call by name (Alexa, Cortana, Siri, etc., but more akin to fixed points in the flow of information.)

jltsiren 4y ago

It's a well-established principle in computer science that the input/output behavior of a system may not capture all of its important properties. Take zero-knowledge proofs for example. Their entire point is that they are indistinguishable from randomly generated garbage from a specific distribution. The proofs only gain value if you make causal assumptions about the system that generated them. I don't think systems like GPT-4 can ever be truly intelligent, because they simply output randomly generated garbage from a specific distribution. Their output may eventually be indistinguishable from that of a truly intelligent system, but the causal mechanism behind them is not intelligent. On the other hand, most people lose their ability to think when they are under sufficient pressure (such as fighting for their lives). It's plausible that people are fundamentally no different from systems like GPT-4 in such situations. Then a language model could be a key part of an AGI, but true intelligence would also need higher-level causal mechanisms.