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We have made progress in efficiency, not functionality. Instead of searching google or stack overflow or any particular documentation, we just go to Chatgpt. I

We have made progress in efficiency, not functionality. Instead of searching google or stack overflow or any particular documentation, we just go to Chatgpt. Information compression is cool, but I want actual AI.

danielmarkbruce 3y ago
The idea that there has been no progress in functionality is silly. Your whole brain might just be doing "information compression" by that analogy. An LLM is sort of learning concepts. Even Word2Vec "learned" than king - male + female = queen and that's a small model that's really just one part (not exact, but similar) of a transformer.
- ActorNightly 3y ago
  Let me rephrase that. One level deep information compression is cool, but I want actual AI. Its true that our brains compress information, but we compress it in a much more complex manner, in the sense that we can not only recall stuff, but also execute a decision tree that often involves physical actions to find the answer we are looking for.
  - danielmarkbruce 3y ago
    An LLM isn't just recalling stuff. Brand new stuff, which it never saw in it's training, can come out. The minute you take a token and turn it into an embedding, then start changing the numbers in that embedding based on other embeddings and learned weights, you are playing around with concepts. As for executing a decision tree, ReAct or Tree of Thought or Graph of Thought is doing that. It might not be doing it as well as a human does, on certain tasks, but it's pretty darn amazing.
    - ActorNightly 3y ago
      >Brand new stuff, which it never saw in it's training, can come out. Sort of. You can get LLMs to produce some new things, but these are statistical averages of existing information. Its kinda like a static "knowledge tree", where it can do some interpolation, but even then, its interpolation based on statistically occurring text.
      - danielmarkbruce 3y ago
        The interpolation isn't really based on statistically occurring text. It's based on statistically occurring concepts. A single token can have many meanings depending on context and many tokens can represent a concept depending on context. A (good) LLM is capturing that.
        bagful 3y ago
        Neither just text or just concepts, but text-concepts — LLMs can only manipulate concepts as they can be conveyed via text. But I think wordlessly, in pure concepts and sense-images, and serialize my thoughts to text. That I have thoughts that I am incapable of verbalizing is what makes me different from an LLM - and, I would argue, actually capable of conceptual synthesis. I have been told some people think “in words” though.
        danielmarkbruce 3y ago
        Nope, you could shove in an embedding that didn't represent an existing token. It would work just fine. (if not obvious.. you'd shove it in right after the embedding layer...)
p1esk 3y ago
Fascinating. What’s “actual AI”?
- mdp2021 3y ago
  > What’s “actual AI” Is Ibn Sina (Avicenna, year ~1000) fine? > [the higher faculty proper of humans is] the primary function of a natural body possessing organs in so far as it commits acts of rational choice and deduction through opinion; and in so far as it perceives universal matters Or, "Intelligence is the ability to reason, determining concepts". (And a proper artificial such thing is something that does it well.)
- taneq 3y ago
  It’s whatever computers can’t do, dummy! :P
- ActorNightly 3y ago
  Something that can reason and figure things out without having ever been exposed to the information during training.
  - p1esk 3y ago
    This either includes GPT-4 or excludes people
- homarp 3y ago
  It is a tool that has the ability to craft a prompt that will break current state of the art model. It is a tool that can be given a project in language X and produce an idomatic port in language Y. It is a tool that given a 20 pages paper spec will ask the questions needed to clarify the specs.

danielmarkbruce 3y ago

The idea that there has been no progress in functionality is silly. Your whole brain might just be doing "information compression" by that analogy. An LLM is sort of learning concepts. Even Word2Vec "learned" than king - male + female = queen and that's a small model that's really just one part (not exact, but similar) of a transformer.

ActorNightly 3y ago
Let me rephrase that. One level deep information compression is cool, but I want actual AI. Its true that our brains compress information, but we compress it in a much more complex manner, in the sense that we can not only recall stuff, but also execute a decision tree that often involves physical actions to find the answer we are looking for.
- danielmarkbruce 3y ago
  An LLM isn't just recalling stuff. Brand new stuff, which it never saw in it's training, can come out. The minute you take a token and turn it into an embedding, then start changing the numbers in that embedding based on other embeddings and learned weights, you are playing around with concepts. As for executing a decision tree, ReAct or Tree of Thought or Graph of Thought is doing that. It might not be doing it as well as a human does, on certain tasks, but it's pretty darn amazing.
  - ActorNightly 3y ago
    >Brand new stuff, which it never saw in it's training, can come out. Sort of. You can get LLMs to produce some new things, but these are statistical averages of existing information. Its kinda like a static "knowledge tree", where it can do some interpolation, but even then, its interpolation based on statistically occurring text.
    - danielmarkbruce 3y ago
      The interpolation isn't really based on statistically occurring text. It's based on statistically occurring concepts. A single token can have many meanings depending on context and many tokens can represent a concept depending on context. A (good) LLM is capturing that.
      - bagful 3y ago
        Neither just text or just concepts, but text-concepts — LLMs can only manipulate concepts as they can be conveyed via text. But I think wordlessly, in pure concepts and sense-images, and serialize my thoughts to text. That I have thoughts that I am incapable of verbalizing is what makes me different from an LLM - and, I would argue, actually capable of conceptual synthesis. I have been told some people think “in words” though.
        danielmarkbruce 3y ago
        Nope, you could shove in an embedding that didn't represent an existing token. It would work just fine. (if not obvious.. you'd shove it in right after the embedding layer...)

p1esk 3y ago

Fascinating. What’s “actual AI”?

mdp2021 3y ago
> What’s “actual AI” Is Ibn Sina (Avicenna, year ~1000) fine? > [the higher faculty proper of humans is] the primary function of a natural body possessing organs in so far as it commits acts of rational choice and deduction through opinion; and in so far as it perceives universal matters Or, "Intelligence is the ability to reason, determining concepts". (And a proper artificial such thing is something that does it well.)
taneq 3y ago
It’s whatever computers can’t do, dummy! :P
ActorNightly 3y ago
Something that can reason and figure things out without having ever been exposed to the information during training.
- p1esk 3y ago
  This either includes GPT-4 or excludes people
homarp 3y ago
It is a tool that has the ability to craft a prompt that will break current state of the art model. It is a tool that can be given a project in language X and produce an idomatic port in language Y. It is a tool that given a 20 pages paper spec will ask the questions needed to clarify the specs.