13 ms·

This is super cool. I share Francois' intuition that the presently data-hungry learning paradigm is not only not generalizable but unsustainable: humans do not

by salamo 2y ago

This is super cool. I share Francois' intuition that the presently data-hungry learning paradigm is not only not generalizable but unsustainable: humans do not need 10,000 examples to tell the difference between cats and dogs, and the main reason computers can today is because we have millions of examples. As a result, it may be hard to transfer knowledge to more esoteric domains where data is expensive, rare, and hard to synthesize. If I can make one criticism/observation of the tests, it seems that most of them reason about perfect information in a game-theoretic sense. However, many if not most of the more challenging problems we encounter involve hidden information. Poker and negotiations are examples of problem solving in imperfect information scenarios. Smoothly navigating social situations also requires a related problem of working with hidden information. One of the really interesting things we humans are able to do is to take the rules of a game and generate strategies. While we do have some algorithms which can "teach themselves" e.g. to play go or chess, those same self-play algorithms don't work on hidden information games. One of the really interesting capabilities of any generally-intelligent system would be synthesizing a general problem solver for those kinds of situations as well.

goertzen 2y ago
I don’t know enough of biology or genetics or evolution, but surely the millions of years of training that is hardcoded into our genes and expressed in our biology had much larger “training” runs.
jules 2y ago
Do computers need 10,000 examples to distinguish dogs from cats when pretrained on other tasks?
- curious_cat_163 2y ago
  No.
VirusNewbie 2y ago
>: humans do not need 10,000 examples to tell the difference between cats and dogs well, maybe. We view things in three dimensions at high fidelity: viewing a single dog or cat actually ends up being thousands of training samples, no?
- amelius 2y ago
  Yes, but we do not call a couch in a leopard print a leopard. Because we understand that the print is secondary to the function.
  - VirusNewbie 2y ago
    I'm not sure it's as simple as you say. The first time my very young son saw a horse, he made the ASL sign for 'dog'. He had only ever seen cats and dogs in his life previous to that.
    - clipsy 2y ago
      Did he require 9,999 more examples of horses before learning the difference?
      - VirusNewbie 2y ago
        In another comment I replied that 3D high fidelity images do end up being thousands of training samples, so the answer is yes.
        clipsy 2y ago
        I'm deeply skeptical that training AI on (effectively) thousands of images of one horse will perform very well at training to recognize horses in general.
        jpc0 2y ago
        I'll double down with you on this. Then train the AI using a binaural video of a thoroughbred and see if it can distinguish a draft horse and a quarter horse as horse...
        _flux 2y ago
        Are you suggesting that if a group of kids were given a book of zoo animals before going to the zoo, they would have difficulties identifing any new animals, because they only have seen one picture of each?
pants2 2y ago
Humans, I would bet, could distinguish between two animals they've never seen based only on a loose or tangential description. I.e. "A dog hunts animals by tracking and chasing them long enough to exhaust their energy, but a cat is opportunistic and strikes using stealth and agility." A human that has never seen a dog or a cat could probably determine which is which based on looking at the two animals and their adaptations. This would be an interesting test for AIs, but I'm not quite sure how one would formulate a eval for this.
- ryankrage77 2y ago
  A possible way to this idea would be to draw two aliens with different hunting strategies and do a poll of which is which. I'd try it but my drawing skills are terrible and I'm averse to using generated images.
- taneq 2y ago
  Only after being exposed to (at least pictures and descriptions of) dozens if not hundreds of different types of animal and their different attributes. Literal decades of training time and carefully curated curriculum learning are required for a human to perform at what we consider ‘human level’.
- tigerlily 2y ago
  Seems analogous to bouba/kiki effect: https://en.m.wikipedia.org/wiki/Bouba/kiki_effect https://en.m.wikipedia.org/wiki/Bouba/kiki_effect
com2kid 2y ago
> humans do not need 10,000 examples to tell the difference between cats and dogs, I swear, not enough people have kids. Now, is it 10k examples? No, but I think it was on the order of hundreds, if not thousands. One thing kids do is they'll ask for confirmation of their guess. You'll be reading a book you've read 50 times before and the kid will stop you, point at a dog in the book, and ask "dog?" And there is a development phase where this happens a lot. Also kids can get mad if they are told an object doesn't match up to the expected label, e.g. my son gets really mad if someone calls something by the wrong color. Another thing toddlers like to do is play silly labeling games, which is different than calling something the wrong name on accident, instead this is done on purpose for fun. e.g. you point to a fish and say "isn't that a lovely llama!" at which point the kid will fall down giggling at how silly you are being. The human brain develops really slowly[1], and a sense of linear time encoding doesn't really exist for quite awhile. (Even at 3, everything is either yesterday, today, or tomorrow) so who the hell knows how things are being processed, but what we do know is that kids gather information through a bunch of senses, that are operating at an absurd data collection rate 12-14 hours a day, with another 10-12 hours of downtime to process the information. [1] Watch a baby discover they have a right foot. Then a few days later figure out they also have a left foot. Watch kids who are learning to stand develop a sense of "up above me" after they bonk their heads a few time on a table bottom. Kids only learn "fast" in the sense that they have nothing else to do for years on end.
- 9cb14c1ec0 2y ago
  > not enough people have kids. Second that. I think I've learned as much as my children have. > Watch a baby discover they have a right foot. Then a few days later figure out they also have a left foot. Watching a baby's awareness grow from pretty much nothing to a fully developed ability to understand the world around is one of the most fascinating parts of being a parent.
- 1024core 2y ago
  > I swear, not enough people have kids. My friends toddler, who grew up with a cat in the house, would initially call all dogs "cat". :-D
AIorNot 2y ago
There’s a great episode from Darkwish Patels podcast discussing this today https://youtu.be/UakqL6Pj9xo?si=iDH6iSNyz1Net8j7 https://youtu.be/UakqL6Pj9xo?si=iDH6iSNyz1Net8j7
- nphard85 2y ago
  Dwarkesh*
theptip 2y ago
> humans do not need 10,000 examples to tell the difference between cats and dogs The optimization process that trained the human brain is called evolution, and it took a lot more than 10,000 examples to produce a system that can differentiate cats vs dogs. Put differently, an LLM is pre-trained with very light priors, starting almost from scratch, whereas a human brain is pre-loaded with extremely strong priors.
- PaulDavisThe1st 2y ago
  > The optimization process that trained the human brain is called evolution, and it took a lot more than 10,000 examples to produce a system that can differentiate cats vs dogs. Asserted without evidence. We have essentially no idea at what point living systems were capable of differentiating cats from dogs (we don't even know for sure which living systems can do this).
  - choeger 2y ago
    We know for a fact that cats, dogs, and humans do.
    - ben_w 2y ago
      As adults, not (as per this thread) genetically.
    - PaulDavisThe1st 2y ago
      Sure, but can earthworms? Butterflies? Oak trees? Slime mould? At what point in the history of life did sufficient discrimination to differentiate e.g. a cat and a dog actually arise? Are the mechanisms used for this universal? Are some better than others? etc.
- deleted 2y ago
  [deleted]
- llm_trw 2y ago
  >The optimization process that trained the human brain is called evolution A human brain that doesn't get visual stimulus at the critical age between 0 and 3 years old will never be able to tell the difference between a cat and a dog because it will be forevermore blind.
allanrbo 2y ago
If a human eye works at say 10 fps, then 8 minutes with a cat is about 10k images :-D
- captaincaveman 2y ago
  I'd say that was more like a single instance, one interaction with a thing.
  - lxgr 2y ago
    But in that single interaction, you might have seen the cat from all kinds of different angles, in various poses, doing various things, some of which are particularly not-dog-like. I vaguely remember hearing that there's even ways to expand training data like that for neural networks, i.e. by presenting the same source image slightly rotated, partially obscured etc.
  - naasking 2y ago
    One interaction that captures a multidimensional, multisensory set of perceptions. In an ML training set, say for visual recognition, this would consist at least of hundreds of images from many angles, in different poses and varied lighting.
    - captaincaveman 2y ago
      I don't think its analogous, I don't think we see a cat and our brain have it frame by frame adjust our synaptic weights (or whatever brains do). The whole premise of natural brains being able to learn by static images or disjointed modalities is a very clunky reductionist engineered approach we have taken.
      - naasking 2y ago
        > I don't think we see a cat and our brain have it frame by frame adjust our synaptic weights (or whatever brains do) I think that "whatever we do" is doing a lot of heavy lifting here. Some of those "whatevers" will be isomorphic to a frame-level analysis that pulls out structural commonalities, or close enough that it's not a clunky reductionist analogy.
nextaccountic 2y ago
> humans do not need 10,000 examples to tell the difference between cats and dogs Humans learn through a lifetime. Or are we talking about newborn infants?
deleted 2y ago
[deleted]
fennecbutt 2y ago
Humans don't need those examples because our brains are very pretrained. Natural fear of snakes and snakelike things, etc etc. ML models are starting from absolute zero, single celled organism level.
woadwarrior01 2y ago
> humans do not need 10,000 examples to tell the difference between cats and dogs Neither do machines. Lookup few-shot learning with things like CLIP.

by salamo 2y ago

goertzen 2y ago

I don’t know enough of biology or genetics or evolution, but surely the millions of years of training that is hardcoded into our genes and expressed in our biology had much larger “training” runs.

jules 2y ago

Do computers need 10,000 examples to distinguish dogs from cats when pretrained on other tasks?

curious_cat_163 2y ago
No.

VirusNewbie 2y ago

>: humans do not need 10,000 examples to tell the difference between cats and dogs well, maybe. We view things in three dimensions at high fidelity: viewing a single dog or cat actually ends up being thousands of training samples, no?

amelius 2y ago
Yes, but we do not call a couch in a leopard print a leopard. Because we understand that the print is secondary to the function.
- VirusNewbie 2y ago
  I'm not sure it's as simple as you say. The first time my very young son saw a horse, he made the ASL sign for 'dog'. He had only ever seen cats and dogs in his life previous to that.
  - clipsy 2y ago
    Did he require 9,999 more examples of horses before learning the difference?
    - VirusNewbie 2y ago
      In another comment I replied that 3D high fidelity images do end up being thousands of training samples, so the answer is yes.
      - clipsy 2y ago
        I'm deeply skeptical that training AI on (effectively) thousands of images of one horse will perform very well at training to recognize horses in general.
        jpc0 2y ago
        I'll double down with you on this. Then train the AI using a binaural video of a thoroughbred and see if it can distinguish a draft horse and a quarter horse as horse...
      - _flux 2y ago
        Are you suggesting that if a group of kids were given a book of zoo animals before going to the zoo, they would have difficulties identifing any new animals, because they only have seen one picture of each?

pants2 2y ago

Humans, I would bet, could distinguish between two animals they've never seen based only on a loose or tangential description. I.e. "A dog hunts animals by tracking and chasing them long enough to exhaust their energy, but a cat is opportunistic and strikes using stealth and agility." A human that has never seen a dog or a cat could probably determine which is which based on looking at the two animals and their adaptations. This would be an interesting test for AIs, but I'm not quite sure how one would formulate a eval for this.

ryankrage77 2y ago
A possible way to this idea would be to draw two aliens with different hunting strategies and do a poll of which is which. I'd try it but my drawing skills are terrible and I'm averse to using generated images.
taneq 2y ago
Only after being exposed to (at least pictures and descriptions of) dozens if not hundreds of different types of animal and their different attributes. Literal decades of training time and carefully curated curriculum learning are required for a human to perform at what we consider ‘human level’.
tigerlily 2y ago
Seems analogous to bouba/kiki effect: https://en.m.wikipedia.org/wiki/Bouba/kiki_effect https://en.m.wikipedia.org/wiki/Bouba/kiki_effect

com2kid 2y ago

> humans do not need 10,000 examples to tell the difference between cats and dogs, I swear, not enough people have kids. Now, is it 10k examples? No, but I think it was on the order of hundreds, if not thousands. One thing kids do is they'll ask for confirmation of their guess. You'll be reading a book you've read 50 times before and the kid will stop you, point at a dog in the book, and ask "dog?" And there is a development phase where this happens a lot. Also kids can get mad if they are told an object doesn't match up to the expected label, e.g. my son gets really mad if someone calls something by the wrong color. Another thing toddlers like to do is play silly labeling games, which is different than calling something the wrong name on accident, instead this is done on purpose for fun. e.g. you point to a fish and say "isn't that a lovely llama!" at which point the kid will fall down giggling at how silly you are being. The human brain develops really slowly[1], and a sense of linear time encoding doesn't really exist for quite awhile. (Even at 3, everything is either yesterday, today, or tomorrow) so who the hell knows how things are being processed, but what we do know is that kids gather information through a bunch of senses, that are operating at an absurd data collection rate 12-14 hours a day, with another 10-12 hours of downtime to process the information. [1] Watch a baby discover they have a right foot. Then a few days later figure out they also have a left foot. Watch kids who are learning to stand develop a sense of "up above me" after they bonk their heads a few time on a table bottom. Kids only learn "fast" in the sense that they have nothing else to do for years on end.

9cb14c1ec0 2y ago
> not enough people have kids. Second that. I think I've learned as much as my children have. > Watch a baby discover they have a right foot. Then a few days later figure out they also have a left foot. Watching a baby's awareness grow from pretty much nothing to a fully developed ability to understand the world around is one of the most fascinating parts of being a parent.
1024core 2y ago
> I swear, not enough people have kids. My friends toddler, who grew up with a cat in the house, would initially call all dogs "cat". :-D

AIorNot 2y ago

There’s a great episode from Darkwish Patels podcast discussing this today https://youtu.be/UakqL6Pj9xo?si=iDH6iSNyz1Net8j7 https://youtu.be/UakqL6Pj9xo?si=iDH6iSNyz1Net8j7

nphard85 2y ago
Dwarkesh*

theptip 2y ago

> humans do not need 10,000 examples to tell the difference between cats and dogs The optimization process that trained the human brain is called evolution, and it took a lot more than 10,000 examples to produce a system that can differentiate cats vs dogs. Put differently, an LLM is pre-trained with very light priors, starting almost from scratch, whereas a human brain is pre-loaded with extremely strong priors.

PaulDavisThe1st 2y ago
> The optimization process that trained the human brain is called evolution, and it took a lot more than 10,000 examples to produce a system that can differentiate cats vs dogs. Asserted without evidence. We have essentially no idea at what point living systems were capable of differentiating cats from dogs (we don't even know for sure which living systems can do this).
- choeger 2y ago
  We know for a fact that cats, dogs, and humans do.
  - ben_w 2y ago
    As adults, not (as per this thread) genetically.
  - PaulDavisThe1st 2y ago
    Sure, but can earthworms? Butterflies? Oak trees? Slime mould? At what point in the history of life did sufficient discrimination to differentiate e.g. a cat and a dog actually arise? Are the mechanisms used for this universal? Are some better than others? etc.
deleted 2y ago
[deleted]
llm_trw 2y ago
>The optimization process that trained the human brain is called evolution A human brain that doesn't get visual stimulus at the critical age between 0 and 3 years old will never be able to tell the difference between a cat and a dog because it will be forevermore blind.

allanrbo 2y ago

If a human eye works at say 10 fps, then 8 minutes with a cat is about 10k images :-D

captaincaveman 2y ago
I'd say that was more like a single instance, one interaction with a thing.
- lxgr 2y ago
  But in that single interaction, you might have seen the cat from all kinds of different angles, in various poses, doing various things, some of which are particularly not-dog-like. I vaguely remember hearing that there's even ways to expand training data like that for neural networks, i.e. by presenting the same source image slightly rotated, partially obscured etc.
- naasking 2y ago
  One interaction that captures a multidimensional, multisensory set of perceptions. In an ML training set, say for visual recognition, this would consist at least of hundreds of images from many angles, in different poses and varied lighting.
  - captaincaveman 2y ago
    I don't think its analogous, I don't think we see a cat and our brain have it frame by frame adjust our synaptic weights (or whatever brains do). The whole premise of natural brains being able to learn by static images or disjointed modalities is a very clunky reductionist engineered approach we have taken.
    - naasking 2y ago
      > I don't think we see a cat and our brain have it frame by frame adjust our synaptic weights (or whatever brains do) I think that "whatever we do" is doing a lot of heavy lifting here. Some of those "whatevers" will be isomorphic to a frame-level analysis that pulls out structural commonalities, or close enough that it's not a clunky reductionist analogy.

nextaccountic 2y ago

> humans do not need 10,000 examples to tell the difference between cats and dogs Humans learn through a lifetime. Or are we talking about newborn infants?

deleted 2y ago

[deleted]

fennecbutt 2y ago

Humans don't need those examples because our brains are very pretrained. Natural fear of snakes and snakelike things, etc etc. ML models are starting from absolute zero, single celled organism level.

woadwarrior01 2y ago

> humans do not need 10,000 examples to tell the difference between cats and dogs Neither do machines. Lookup few-shot learning with things like CLIP.