5 ms·

The confabulation to justify picking out related images that the left brain never observed (chicken and snow shovel in the article) reminds me profoundly of the

The confabulation to justify picking out related images that the left brain never observed (chicken and snow shovel in the article) reminds me profoundly of the confident slop produced by LLMs. Make you wonder if llms might be one half of the "brain" of a true AGI

HeatrayEnjoyer 2y ago
More then half! Human experience is more confabulation than not. The optic nerve's digital-equivalent bandwidth is an estimated 10Mbps, predominantly dedicated to a narrow radius around the center of vision. Everything around the outside of your vision is a few fuzzy pixels that are in-filled with plausible data. Same goes for the blind spot created by the optic disc, which is actually fully fabricated as it has no cones or rods at all!
- BriggyDwiggs42 2y ago
  You’d like blindsight, if you haven’t read it
jjtheblunt 2y ago
along those lines, maybe dreaming is piecing together new adventures imagined from snippets of reality.
- encipriano 2y ago
  Those videos about ai making up a game after having watched countless hours of streaming is fucked up. It looks completely how dreams do
  - jmesmith 2y ago
    Do you have a link?
    - triMichael 2y ago
      Here's one: "AI Minecraft Is Beautifully Bizarre" https://www.youtube.com/watch?v=KHJ9jJh0udc https://www.youtube.com/watch?v=KHJ9jJh0udc
MathMonkeyMan 2y ago
That's a theme in the novel "Neuromancer".
danielmarkbruce 2y ago
confident slop.
- Lerc 2y ago
  The confidence seems to be an artifact of fine tuning. The first instruction trained models were given data sets with answers to questions but generally omitted non answers to things the model didn't know. Later research showed that models know that they don't know certain pieces of information, but the fine tuning constraint of providing answers did not give them the ability to express that they didn't know. Asking the model questions against known information can produce a correct/incorrect map detailing a sample of facts that the model knows and does not know. Fine tuning a model to say "I don't know" in response to the those questions where it was incorrect can allow it to generalise the concept to its internal concept of unknown. It is good to keep in mind that the models we have been playing with are just the first ones to appear. GPT 3.5 is like the Atari 2600. You can get it provide a limited experience for what you want and its cool that you can do it at all, but it is fundamentally limited and far from an ideal solution. I see the current proliferation of models to be like the Cambrian explosion of early 8 bit home computers. Exciting and interesting technology which can be used for real world purposes, but you still have to operate with the knowledge of the limitations forefront in your mind and tailor tasks to allow them to perform the bits they are good at. I have no-idea of the timeframe, but there is plenty more to come. There have been a lot of advances revealed in papers. A huge number of those advances have not yet coalesced into shipping models. When models cost millions to train you want to be using a set of enhancements that play nicely together. Some features will be mutually exclusive. By the time you have analysed the options to find an optimal combination, a whole lot of new papers will be suggesting more options. We have not yet got the thing for AI that Unix was for computers. We are just now exposing people to the problems that drives the need to create such a thing.
  - danielmarkbruce 2y ago
    My comment was snark and basically saying "humans are full of confident slop".
- 2y ago
codr7 2y ago
It certainly looks like what LLMs are doing is one aspect of what a brain is doing.
- ggm 2y ago
  Key point here is "looks like" I suggest if you want to argue this further to invest the time asking Brain Scientists what they think. Not AI scientists but people who actually work in cognition. (Not a brain scientist btw)
  - yesco 2y ago
    Only if you think computers need to copy the precise neurological "hardware" systems of the brain. However if you think of conciousness as software then I think overlap is highly likely considering both are emergent. That said, this topic is more philosophical than scientific at the end of the day.
    - codr7 2y ago
      It looks to me like the deeper you dig into any scientific subject, the more philosophical it gets.

HeatrayEnjoyer 2y ago

More then half! Human experience is more confabulation than not. The optic nerve's digital-equivalent bandwidth is an estimated 10Mbps, predominantly dedicated to a narrow radius around the center of vision. Everything around the outside of your vision is a few fuzzy pixels that are in-filled with plausible data. Same goes for the blind spot created by the optic disc, which is actually fully fabricated as it has no cones or rods at all!

BriggyDwiggs42 2y ago
You’d like blindsight, if you haven’t read it

jjtheblunt 2y ago

along those lines, maybe dreaming is piecing together new adventures imagined from snippets of reality.

encipriano 2y ago
Those videos about ai making up a game after having watched countless hours of streaming is fucked up. It looks completely how dreams do
- jmesmith 2y ago
  Do you have a link?
  - triMichael 2y ago
    Here's one: "AI Minecraft Is Beautifully Bizarre" https://www.youtube.com/watch?v=KHJ9jJh0udc https://www.youtube.com/watch?v=KHJ9jJh0udc

MathMonkeyMan 2y ago

That's a theme in the novel "Neuromancer".

danielmarkbruce 2y ago

confident slop.

Lerc 2y ago
The confidence seems to be an artifact of fine tuning. The first instruction trained models were given data sets with answers to questions but generally omitted non answers to things the model didn't know. Later research showed that models know that they don't know certain pieces of information, but the fine tuning constraint of providing answers did not give them the ability to express that they didn't know. Asking the model questions against known information can produce a correct/incorrect map detailing a sample of facts that the model knows and does not know. Fine tuning a model to say "I don't know" in response to the those questions where it was incorrect can allow it to generalise the concept to its internal concept of unknown. It is good to keep in mind that the models we have been playing with are just the first ones to appear. GPT 3.5 is like the Atari 2600. You can get it provide a limited experience for what you want and its cool that you can do it at all, but it is fundamentally limited and far from an ideal solution. I see the current proliferation of models to be like the Cambrian explosion of early 8 bit home computers. Exciting and interesting technology which can be used for real world purposes, but you still have to operate with the knowledge of the limitations forefront in your mind and tailor tasks to allow them to perform the bits they are good at. I have no-idea of the timeframe, but there is plenty more to come. There have been a lot of advances revealed in papers. A huge number of those advances have not yet coalesced into shipping models. When models cost millions to train you want to be using a set of enhancements that play nicely together. Some features will be mutually exclusive. By the time you have analysed the options to find an optimal combination, a whole lot of new papers will be suggesting more options. We have not yet got the thing for AI that Unix was for computers. We are just now exposing people to the problems that drives the need to create such a thing.
- danielmarkbruce 2y ago
  My comment was snark and basically saying "humans are full of confident slop".
2y ago

codr7 2y ago

It certainly looks like what LLMs are doing is one aspect of what a brain is doing.

ggm 2y ago
Key point here is "looks like" I suggest if you want to argue this further to invest the time asking Brain Scientists what they think. Not AI scientists but people who actually work in cognition. (Not a brain scientist btw)
- yesco 2y ago
  Only if you think computers need to copy the precise neurological "hardware" systems of the brain. However if you think of conciousness as software then I think overlap is highly likely considering both are emergent. That said, this topic is more philosophical than scientific at the end of the day.
  - codr7 2y ago
    It looks to me like the deeper you dig into any scientific subject, the more philosophical it gets.