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jms4607 t1_j0ckrj0 wrote

Reply to comment by ReginaldIII in [R] Talking About Large Language Models - Murray Shanahan 2022 by Singularian2501

Ur only able to sample something from the manifold you have been trained on.

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ReginaldIII t1_j0cl6lg wrote

That's not really true because because both under- and over-fitting can happen.

And it doesn't reinforce your assertion that ChatGPT has awareness or intent.

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jms4607 t1_j0cqu0a wrote

I’d argue that if ChatGPT was fine tuned in RL based off of the responses of a human, for example, if it’s goal as a debater ai was to make humans less confident of their belief by responding in contrary in a conversation, than it arguably has awareness of intent. Is this not possible in the training scheme of ChatGPT? I looked into how they use RL right now, and I agree it is just fine-tuning human-like responses, but I think a different reward function could illicit awareness of intent.

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ReginaldIII t1_j0cuujj wrote

It mimics statistical trends from the training data. It uses embeddings that make related semantics and concepts near to one another, and unrelated ones far from one another. Therefore, when it regurgitates structures and logical templates that were observed in the training data it is able to project other similar concepts and semantics into those structures, making them look convincingly like entirely novel and intentional responses.

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jms4607 t1_j0cva57 wrote

I don’t think we know enough about the human brain to say we aren’t doing something very similar ourselves. 90% at least of human brain development has been to optimize E[agents with my dna in future]. Our brains are basically embedding our sensory input into a compressed latent internal state, then sampling actions to optimize some objective.

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ReginaldIII t1_j0cxciw wrote

That we have the ability to project concepts into the scaffold of other concepts? Imagine a puppy wearing a sailor hat. Yup we definitely can do that.

f(x) = 2x

I can put x=1 in, I can put x=2 but if I don't put anything in then it just exists as a mathematical construct and it doesn't sit their pondering its own existence or the nature of what x even is. "I mean, why 2x ?!"

If I write an equation c(Φ,ω) =（Φ ω Φ）do you zoomorphise it because it looks like a cat?

What about this function which plots out Simba. Is it aware of how cute it is?

x(t) = ((-1/12 sin(3/2 - 49 t) - 1/4 sin(19/13 - 44 t) - 1/7 sin(37/25 - 39 t) - 3/10 sin(20/13 - 32 t) - 5/16 sin(23/15 - 27 t) - 1/7 sin(11/7 - 25 t) - 7/4 sin(14/9 - 18 t) - 5/3 sin(14/9 - 6 t) - 31/10 sin(11/7 - 3 t) - 39/4 sin(11/7 - t) + 6/5 sin(2 t + 47/10) + 34/11 sin(4 t + 19/12) + 83/10 sin(5 t + 19/12) + 13/3 sin(7 t + 19/12) + 94/13 sin(8 t + 8/5) + 19/8 sin(9 t + 19/12) + 9/10 sin(10 t + 61/13) + 13/6 sin(11 t + 13/8) + 23/9 sin(12 t + 33/7) + 2/9 sin(13 t + 37/8) + 4/9 sin(14 t + 19/11) + 37/16 sin(15 t + 8/5) + 7/9 sin(16 t + 5/3) + 2/11 sin(17 t + 47/10) + 3/4 sin(19 t + 5/3) + 1/20 sin(20 t + 24/11) + 11/10 sin(21 t + 21/13) + 1/5 sin(22 t + 22/13) + 2/11 sin(23 t + 11/7) + 3/11 sin(24 t + 22/13) + 1/9 sin(26 t + 17/9) + 1/63 sin(28 t + 43/13) + 3/10 sin(29 t + 23/14) + 1/45 sin(30 t + 45/23) + 1/7 sin(31 t + 5/3) + 3/7 sin(33 t + 5/3) + 1/23 sin(34 t + 9/2) + 1/6 sin(35 t + 8/5) + 1/7 sin(36 t + 7/4) + 1/10 sin(37 t + 8/5) + 1/6 sin(38 t + 16/9) + 1/28 sin(40 t + 4) + 1/41 sin(41 t + 31/7) + 1/37 sin(42 t + 25/6) + 3/14 sin(43 t + 12/7) + 2/7 sin(45 t + 22/13) + 1/9 sin(46 t + 17/10) + 1/26 sin(47 t + 12/7) + 1/23 sin(48 t + 58/13) - 55/4) θ(111 π - t) θ(t - 107 π) + (-1/5 sin(25/17 - 43 t) - 1/42 sin(1/38 - 41 t) - 1/9 sin(17/11 - 37 t) - 1/5 sin(4/3 - 25 t) - 10/9 sin(17/11 - 19 t) - 1/6 sin(20/19 - 17 t) - 161/17 sin(14/9 - 2 t) + 34/9 sin(t + 11/7) + 78/7 sin(3 t + 8/5) + 494/11 sin(4 t + 33/7) + 15/4 sin(5 t + 51/11) + 9/4 sin(6 t + 47/10) + 123/19 sin(7 t + 33/7) + 49/24 sin(8 t + 8/5) + 32/19 sin(9 t + 17/11) + 55/18 sin(10 t + 17/11) + 16/5 sin(11 t + 29/19) + 4 sin(12 t + 14/9) + 77/19 sin(13 t + 61/13) + 29/12 sin(14 t + 14/3) + 13/7 sin(15 t + 29/19) + 13/4 sin(16 t + 23/15) ...

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jms4607 t1_j0d65c3 wrote

  1. Projecting can be interpolation, which these models are capable of. There are a handful of image/text models that can imagine/project an image of a puppy wearing a sailor hat.

  2. All you need to do is have continuous sensory input in your RL environment/include cost or delay of thought in actions, which is something that has been implemented in research to resolve your f(x) = 2x issue.

  3. The Cat example is only ridiculous because it obviously isn’t a cat. If we can’t reasonably prove that it is or isn’t a cat, then asking whether it is a cat or not is not a question worth considering. Similar idea goes for the question “is ChatGPT capturing some aspect of human cognition”. If we can’t prove that our brains work in a functionally different way that can’t be approximated to arbitrary degree by a ML model, then it isn’t something worth arguing ab. I don’t think we know enough ab neuroscience to state we aren’t just doing latent interpolation to optimize some objective.

  4. The simba is only cute because you think it is cute. If we trained an accompanying text model for the simba function, where it was given the training data “you are cute” in different forms, it would probably respond yes if asked if it was cute. GPT-3 or ChatGPT can refer and make statements ab itself.

At least agree that evolution on earth and human actions are nothing but a MARL POMDP environment.

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