6 ms·

> "No human requires the amount of training data we are already giving the models." Well, humans are also trained differently. We interact with other humans i

by elihu 3y ago

> "No human requires the amount of training data we are already giving the models." Well, humans are also trained differently. We interact with other humans in real time and get immediate feedback on their responses. We don't just learn by reading through reams of static information. We talk to people. We get into arguments. And so on. Maybe the ideal way to train an AI is to have it interact with lots of humans, so it can try things on its own? The implication of that is maybe the best trained AI will be the center of some important web property, like, say, the Google search engine (I'm imagining something like Google search now, but more conversational -- it asks you if that was what you're looking for, and asks clarifying questions.) Whoever has the most users will have the best AI, which creates the best product, which attracts the most users... and so on. I do agree that architectural improvements could be hugely significant too.

jojobas 3y ago
The first humans were kinda dumb. Yet by interacting with the world and each other, humans got smart. I wonder if neural network instances can interact with a simulated environment and each other, they could become smart enough for practical purposes. Kinda like alpha go zero but with "life".
- Pompidou 3y ago
  > The first humans were kinda dumb How can you assert this ? Do you have any evidence?
  - jojobas 3y ago
    Can't tell if you're joking or serious. In the latter case, the first humans (H. Habilis) had about 1/2 of H. Sapiens brain to work with, and a much smaller fraction of neocortex. If that doesn't satisfy you, let's say I was speaking about some sort of human ancestor before that, which would have been about as dumb as chimps, unless you require proof of their dumbness as well.
    - Zanni 3y ago
      Not your original objector, but ... I was willing to accept that early humans are dumb, but your explanation relies on evolution and not social interaction.
      - Andrex 3y ago
        Exactly. Humans didn't learn their way out of only having half a brain, more the opposite.
      - junofan 3y ago
        We know their brains didn’t grow much after birth, unlike humans, which also suggests faster maturity akin to living apes and likely less social support for extended adolescence.
      - jojobas 3y ago
        Humans didn't evolve knowledge, they evolved the capacity to get more knowledge. All the new knowledge they got they figured out from the environment.
    - theduder99 3y ago
      Hard to imagine anyone believes these prehuman theories. Just look at the h hablis wiki page to see 90% of it is pure speculation and debated.
  - Andrex 3y ago
    Even tracing it back to the origin of Homo erectus, the line would still be too blurry. I don't think "the first humans" can actually mean anything in a science-based discussion.
- ahmedfromtunis 3y ago
  Conversion is essential, but so is the interaction with the real world. If a bunch of AIs started discussing with each other, and learning from each other, without validation, things can go wrong very easily. I bet a lot of people thought that strapping a pair of feahterry wing was all that's needed to fly. This "knowledge" could've passed from one person to another through discussion. But it only took one (or more) person to actually try it in the real world to learn that, no, that doesn't work like that. AI communities (as in communities of AIs talking to each other) might be one filled with the most outrageous "conspiracy theories", that may sound plausible but have no substance.
jonplackett 3y ago
Yeah I'm not totally convinced humans don't have a tremendous amount of training data - interacting with the world for years with constant input from all our senses and parental corrections. I bet if you add up that data it's a lot. But once we are partially trained, training more requires a lot less.
- Majromax 3y ago
  > I bet if you add up that data it's a lot. Let's Fermi estimate that. A 4k video stream is about 50 megabits/second. Let's say that humans have the equivalent of two of those going during waking hours, one for vision and one for everything else. Humans are awake for 18 hours/day, and we'll say a human's training is 'complete' at 25. Multiply that together, and you end up with 1.8e17 bytes, or 180 petabytes of data. There's plenty of reason to think that we don't learn effectively from all of this data (there's lots of redundancy, for example), but at the grossest orders of magnitude you seem to be right that at least in theory we have access to a tremendous amount of data.
  - huijzer 3y ago
    > Let's Fermi estimate that. I couldn't agree more. Fermi estimates are underused. > Multiply that together, and you end up with 1.8e17 bytes, or 180 petabytes of data. And for comparison, GPT-4 is estimated by Bill Dally (NVIDIA) at around 10^12 or 10^13 tokens [1]. Let's assume about 1 word per token and 5 characters per word. Furthermore, US-ASCII tokens requires one byte per character in UTF-8. So, that gives about 50 terabyte [Edited after comment below]. As a side note, I would guess that GPT-4 knows more "things" if you would be able to count them all up. For example, it knows more languages, more facts about cities, more facts about persons. However, people know way more inside their specialization. [1]: https://youtu.be/kLiwvnr4L80?si=77pXmIBmlp8dsSCG&t=349 https://youtu.be/kLiwvnr4L80?si=77pXmIBmlp8dsSCG&t=349
    - Majromax 3y ago
      > Let's assume about 1 word per token and 5 characters per word. Furthermore, US-ASCII tokens requires one byte per character in UTF-8. So, that gives about 40 petabyte. Thanks, I was looking for that estimate but could not quickly find it. (Although are you sure about that 'petabyte' figure? I see 1e13 * 5 = 50e13 = 50 TB?) I love these sorts of bulk comparisons, since they let us start to reason about how much humans learn from "each bit of experience" versus LLMs. On one hand humans process a lot of sensory information (most of it by discarding, mind), but on the other humans do a lot of 'active learning' whereby experience is directly related to actions. LLMs don't have the latter, since they're trained on passive feeds of tokens.
circlefavshape 3y ago
It's not just humans we interact with - it's reality. For an LLM all "facts" are socially-determined, for a human they are not
hliyan 3y ago
Also, humans have multiple internal models for various aspects of reality, that seem to exist as a layer on top of the "raw" training. They have the ability to extrapolate based on those models (which transformers cannot do, as far I as understand). Perhaps GP is right -- perhaps what's missing in the architecture is an analog of these models.

by elihu 3y ago

jojobas 3y ago

The first humans were kinda dumb. Yet by interacting with the world and each other, humans got smart. I wonder if neural network instances can interact with a simulated environment and each other, they could become smart enough for practical purposes. Kinda like alpha go zero but with "life".

Pompidou 3y ago
> The first humans were kinda dumb How can you assert this ? Do you have any evidence?
- jojobas 3y ago
  Can't tell if you're joking or serious. In the latter case, the first humans (H. Habilis) had about 1/2 of H. Sapiens brain to work with, and a much smaller fraction of neocortex. If that doesn't satisfy you, let's say I was speaking about some sort of human ancestor before that, which would have been about as dumb as chimps, unless you require proof of their dumbness as well.
  - Zanni 3y ago
    Not your original objector, but ... I was willing to accept that early humans are dumb, but your explanation relies on evolution and not social interaction.
    - Andrex 3y ago
      Exactly. Humans didn't learn their way out of only having half a brain, more the opposite.
    - junofan 3y ago
      We know their brains didn’t grow much after birth, unlike humans, which also suggests faster maturity akin to living apes and likely less social support for extended adolescence.
    - jojobas 3y ago
      Humans didn't evolve knowledge, they evolved the capacity to get more knowledge. All the new knowledge they got they figured out from the environment.
  - theduder99 3y ago
    Hard to imagine anyone believes these prehuman theories. Just look at the h hablis wiki page to see 90% of it is pure speculation and debated.
- Andrex 3y ago
  Even tracing it back to the origin of Homo erectus, the line would still be too blurry. I don't think "the first humans" can actually mean anything in a science-based discussion.
ahmedfromtunis 3y ago
Conversion is essential, but so is the interaction with the real world. If a bunch of AIs started discussing with each other, and learning from each other, without validation, things can go wrong very easily. I bet a lot of people thought that strapping a pair of feahterry wing was all that's needed to fly. This "knowledge" could've passed from one person to another through discussion. But it only took one (or more) person to actually try it in the real world to learn that, no, that doesn't work like that. AI communities (as in communities of AIs talking to each other) might be one filled with the most outrageous "conspiracy theories", that may sound plausible but have no substance.

jonplackett 3y ago

Yeah I'm not totally convinced humans don't have a tremendous amount of training data - interacting with the world for years with constant input from all our senses and parental corrections. I bet if you add up that data it's a lot. But once we are partially trained, training more requires a lot less.

Majromax 3y ago
> I bet if you add up that data it's a lot. Let's Fermi estimate that. A 4k video stream is about 50 megabits/second. Let's say that humans have the equivalent of two of those going during waking hours, one for vision and one for everything else. Humans are awake for 18 hours/day, and we'll say a human's training is 'complete' at 25. Multiply that together, and you end up with 1.8e17 bytes, or 180 petabytes of data. There's plenty of reason to think that we don't learn effectively from all of this data (there's lots of redundancy, for example), but at the grossest orders of magnitude you seem to be right that at least in theory we have access to a tremendous amount of data.
- huijzer 3y ago
  > Let's Fermi estimate that. I couldn't agree more. Fermi estimates are underused. > Multiply that together, and you end up with 1.8e17 bytes, or 180 petabytes of data. And for comparison, GPT-4 is estimated by Bill Dally (NVIDIA) at around 10^12 or 10^13 tokens [1]. Let's assume about 1 word per token and 5 characters per word. Furthermore, US-ASCII tokens requires one byte per character in UTF-8. So, that gives about 50 terabyte [Edited after comment below]. As a side note, I would guess that GPT-4 knows more "things" if you would be able to count them all up. For example, it knows more languages, more facts about cities, more facts about persons. However, people know way more inside their specialization. [1]: https://youtu.be/kLiwvnr4L80?si=77pXmIBmlp8dsSCG&t=349 https://youtu.be/kLiwvnr4L80?si=77pXmIBmlp8dsSCG&t=349
  - Majromax 3y ago
    > Let's assume about 1 word per token and 5 characters per word. Furthermore, US-ASCII tokens requires one byte per character in UTF-8. So, that gives about 40 petabyte. Thanks, I was looking for that estimate but could not quickly find it. (Although are you sure about that 'petabyte' figure? I see 1e13 * 5 = 50e13 = 50 TB?) I love these sorts of bulk comparisons, since they let us start to reason about how much humans learn from "each bit of experience" versus LLMs. On one hand humans process a lot of sensory information (most of it by discarding, mind), but on the other humans do a lot of 'active learning' whereby experience is directly related to actions. LLMs don't have the latter, since they're trained on passive feeds of tokens.

circlefavshape 3y ago

It's not just humans we interact with - it's reality. For an LLM all "facts" are socially-determined, for a human they are not

hliyan 3y ago

Also, humans have multiple internal models for various aspects of reality, that seem to exist as a layer on top of the "raw" training. They have the ability to extrapolate based on those models (which transformers cannot do, as far I as understand). Perhaps GP is right -- perhaps what's missing in the architecture is an analog of these models.