5 ms·

I think that most human learning comes from years of sensory input. Why should we expect a machine to generalize well without any background?

Krasnol 2y ago
I'd guess it's because we don't want to have another human. We want something better. Therefore, the expectations on the learning process are way beyond what humans do. I guess some are expecting some magic word (formula) which would be like a seed with unlimited potential. So like humans after all but faster. I guess it's just hard to write a book about the way you write that book.
andoando 2y ago
It does but it also generalizes extremely well
- tripplyons 2y ago
  I haven't seen a convincing argument that it is more sample efficient than a neural network that has seen an equivalent amount of lifetime information. Yann LeCun gave an interesting explanation of how even in the first few years of a child's life, they have seen much more information than the largest pretrained models have.
aithrowawaycomm 2y ago
Newborns (and certainly toddlers) seem to understand the underlying concepts for these things when it comes to visual/hepatic object identification and "folk physics": A short list of abilities that cannot be performed by CompressARC includes: Assigning two colors to each other (see puzzle 0d3d703e) Repeating an operation in series many times (see puzzle 0a938d79) Counting/numbers (see puzzle ce9e57f2) Translation, rotation, reflections, rescaling, image duplication (see puzzles 0e206a2e, 5ad4f10b, and 2bcee788) Detecting topological properties such as connectivity (see puzzle 7b6016b9) Note: I am not saying newborns can solve the corresponding ARC problems! The point is there is a lot of evidence that many of the concepts ARC-AGI is (allegedly) measuring are innate in humans, and maybe most animals; e.g. cockroaches can quickly identify connected/disconnected components when it comes to pathfinding. Again, not saying cockroaches can solve ARC :) OTOH even if orcas were smarter than humans they would struggle with ARC - it would be way too baffling and obtuse if your culture doesn't have the concept of written standardized tests. (I was solving state-mandated ARCish problems since elementary school.) This also applies to hunter-gatherers, and note the converse: if you plopped me down among the Khoisan in the Kalahari, they would think I was an ignorant moron. But it makes as much sense scientifically to say "human-level intelligence" entails "human-level hunter-gathering" instead of "human-level IQ problems."
- Ukv 2y ago
  > there is a lot of evidence that many of the concepts ARC-AGI is (allegedly) measuring are innate in humans I'd argue that "innate" here still includes a brain structure/nervous system that evolved on 3.5 billion years worth of data. Extensive pre-training of one kind or another currently seems the best way to achieve generality.
  - onemoresoop 2y ago
    Sure and LLMs ain’t nothing of this sort. While they’re an incredible feat in technology, they’re just a building block for intelligence, an important building block I’d say.
  - SiempreViernes 2y ago
    So all billons spent finding tricks and architectures that perfom well haven't resulted in any durable structures in contemporary LLMs? Each new training from scratch is a perfect blank slate and the only thing ensuring words come out is the size of the corpus?
    - Ukv 2y ago
      > Each new training from scratch is a perfect blank slate [...]? I don't think training runs are done entirely from scratch. Most training runs in practice will start from some pretrained weights or distill an existing model - taking some model pretrained on ImageNet or Common Crawl and fine-tuning it to a specific task. But even when the weights are randomly initialized, the hyperparameters and architectural choices (skip connections, attention, ...) will have been copied from previous models/papers by what performed well empirically, sometimes also based on trying to transfer our own intuition (like stacking convolutional layers as a rough approximation of our visual system), and possibly refined/mutated through some grid search/neural architecture search on data.
- mystified5016 2y ago
  Newborn brains aren't blank, they are complex beyond our current ability to understand. All mammals are born with a shocking amount of instinctual knowledge built right into their genome. All organisms are born pre-trained because if you can't hide or survive the moment you're born, you get eaten.

Krasnol 2y ago

I'd guess it's because we don't want to have another human. We want something better. Therefore, the expectations on the learning process are way beyond what humans do. I guess some are expecting some magic word (formula) which would be like a seed with unlimited potential. So like humans after all but faster. I guess it's just hard to write a book about the way you write that book.

andoando 2y ago

It does but it also generalizes extremely well

tripplyons 2y ago
I haven't seen a convincing argument that it is more sample efficient than a neural network that has seen an equivalent amount of lifetime information. Yann LeCun gave an interesting explanation of how even in the first few years of a child's life, they have seen much more information than the largest pretrained models have.

aithrowawaycomm 2y ago

Newborns (and certainly toddlers) seem to understand the underlying concepts for these things when it comes to visual/hepatic object identification and "folk physics": A short list of abilities that cannot be performed by CompressARC includes: Assigning two colors to each other (see puzzle 0d3d703e) Repeating an operation in series many times (see puzzle 0a938d79) Counting/numbers (see puzzle ce9e57f2) Translation, rotation, reflections, rescaling, image duplication (see puzzles 0e206a2e, 5ad4f10b, and 2bcee788) Detecting topological properties such as connectivity (see puzzle 7b6016b9) Note: I am not saying newborns can solve the corresponding ARC problems! The point is there is a lot of evidence that many of the concepts ARC-AGI is (allegedly) measuring are innate in humans, and maybe most animals; e.g. cockroaches can quickly identify connected/disconnected components when it comes to pathfinding. Again, not saying cockroaches can solve ARC :) OTOH even if orcas were smarter than humans they would struggle with ARC - it would be way too baffling and obtuse if your culture doesn't have the concept of written standardized tests. (I was solving state-mandated ARCish problems since elementary school.) This also applies to hunter-gatherers, and note the converse: if you plopped me down among the Khoisan in the Kalahari, they would think I was an ignorant moron. But it makes as much sense scientifically to say "human-level intelligence" entails "human-level hunter-gathering" instead of "human-level IQ problems."

Ukv 2y ago
> there is a lot of evidence that many of the concepts ARC-AGI is (allegedly) measuring are innate in humans I'd argue that "innate" here still includes a brain structure/nervous system that evolved on 3.5 billion years worth of data. Extensive pre-training of one kind or another currently seems the best way to achieve generality.
- onemoresoop 2y ago
  Sure and LLMs ain’t nothing of this sort. While they’re an incredible feat in technology, they’re just a building block for intelligence, an important building block I’d say.
- SiempreViernes 2y ago
  So all billons spent finding tricks and architectures that perfom well haven't resulted in any durable structures in contemporary LLMs? Each new training from scratch is a perfect blank slate and the only thing ensuring words come out is the size of the corpus?
  - Ukv 2y ago
    > Each new training from scratch is a perfect blank slate [...]? I don't think training runs are done entirely from scratch. Most training runs in practice will start from some pretrained weights or distill an existing model - taking some model pretrained on ImageNet or Common Crawl and fine-tuning it to a specific task. But even when the weights are randomly initialized, the hyperparameters and architectural choices (skip connections, attention, ...) will have been copied from previous models/papers by what performed well empirically, sometimes also based on trying to transfer our own intuition (like stacking convolutional layers as a rough approximation of our visual system), and possibly refined/mutated through some grid search/neural architecture search on data.
mystified5016 2y ago
Newborn brains aren't blank, they are complex beyond our current ability to understand. All mammals are born with a shocking amount of instinctual knowledge built right into their genome. All organisms are born pre-trained because if you can't hide or survive the moment you're born, you get eaten.