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No argument with the particles/neurons/matter approach to the subject. It is sound and if you look at us compositionally there is nothing magic about whats goi

No argument with the particles/neurons/matter approach to the subject. It is sound and if you look at us compositionally there is nothing magic about whats going on. There is, though, something about intuition or instinctual behavior which can constantly recombine/reapply itself to a task at hand. I know many will balk at intuition, and maybe its only at the very best a heuristic, but i think we need to at least unravel what it is and how it operates before we can understand what makes something classify as human-like intelligence. Is it merely executing a process which we can put our minds into with practice, or is it demonstrating something more general, higher-level.

fouc 3y ago
intuition is a form of pattern matching without reasoning, so kinda like LLM
mjburgess 3y ago
Well look, compared to the electrified bits of sand in my laptop i'd strongly defend pregnancy as something vastly more "magical" if those are the terms we must use. People who thing organic adaption, sensory-motor adaption, somatosensory representation building... ie.., all those things which ooze-and-grow so that a paino player can play, or we can here type... are these magic? Well I think it's exactly the opposite. It's a very anti-intellectual nihilism that all that need be known about the world is the electromagnetic properties of silicon-based transitors. Those who use the word "magic" in this debate are really like atheists about the moon. It all sounds very smart to deny the moon exists, but in the end, it's actually just a lack of knowledge dressed up as enlightened cynicism. There are more things to discover in a single cell of our body that we have ever known; and may ever know. All the theories of science needed to explain its operation would exhaust every page we have ever printed. We know a fraction of what we need to know. And each bit of that fraction reveals an entire universe of "magical" processes unreplicated by copper wires or silicon switches.
- mtlmtlmtlmtl 3y ago
  You make good points. I think it's a typical trait of the way computer scientists and programmers tend to think. Computer science has made great strides over the decades through abstraction, as well as distillation of complex systems into simpler properties that can easily be computed. As a result of the combination of this method of thinking and the Dunning-Kruger effect, people in our field tend to apply this to the entire world, even where it doesn't fit very well, like biology, geopolitics, sociology, psychology, etc. You see a lot of this on HN. People who seem to think they've figured out some very deep truth about another field that can be explained in one hand-waving paragraph, when really there are lots of important details they're ignoring that make their ideas trivially wrong. Economists have a similar thing going on, I feel. Though I'm not an economist.
  - mjburgess 3y ago
    Remember always, computer science is just discrete mathematics with some automatic whiteboards. It is not science. And that's the heart of the problem. The CSci crowd have a somewhat well-motivated inclination to treat abstractions as real objects of study; but have been severely misdirected by learning statistics without the scientific method. This has created a monster: the abstract objects of study are just the associations statistics makes available. You mix those two together and you have flat-out pseudoscience.
    - andoando 3y ago
      Not sure I agree in this regard. We are after all, aiming to create a mental model which describes reproducible steps for creating general intelligence. That is, the product is ultimately going to be some set of abstractions or another. I am not sure what more scientific method you could propose. And we can, in this field produce actual reproducible experiments. Really, more so than any other field.
      - mjburgess 3y ago
        There's nothing to replicate. ML models are associative statistical models of historical data. There are no experimental conditions, no causal properties, no modelled causal mechanisms, no theories at all. "Replication" means that you can reproduce an experiment designed to validate a causal hypothesis. Fitting a function to data isnt an experiment, it's just a way of compressing the data into a more efficient representation. That's all ML is. There are no explanations here (of the data) to assess.
wruza 3y ago
Intuition is a process of slight blind guesses in a system that was built/proposed by a similar organism, in a way that resembles previous systems. Once you get into things like advanced physics, advanced biology, etc, intuition evaporates. Remember these SR/GR things? How intuitive were these? I’d say the current AI is pure intuition in this Q'-ZipQA-A' sense, cause all it does is blind guessing the descent path.

fouc 3y ago

intuition is a form of pattern matching without reasoning, so kinda like LLM

mjburgess 3y ago

Well look, compared to the electrified bits of sand in my laptop i'd strongly defend pregnancy as something vastly more "magical" if those are the terms we must use. People who thing organic adaption, sensory-motor adaption, somatosensory representation building... ie.., all those things which ooze-and-grow so that a paino player can play, or we can here type... are these magic? Well I think it's exactly the opposite. It's a very anti-intellectual nihilism that all that need be known about the world is the electromagnetic properties of silicon-based transitors. Those who use the word "magic" in this debate are really like atheists about the moon. It all sounds very smart to deny the moon exists, but in the end, it's actually just a lack of knowledge dressed up as enlightened cynicism. There are more things to discover in a single cell of our body that we have ever known; and may ever know. All the theories of science needed to explain its operation would exhaust every page we have ever printed. We know a fraction of what we need to know. And each bit of that fraction reveals an entire universe of "magical" processes unreplicated by copper wires or silicon switches.

mtlmtlmtlmtl 3y ago
You make good points. I think it's a typical trait of the way computer scientists and programmers tend to think. Computer science has made great strides over the decades through abstraction, as well as distillation of complex systems into simpler properties that can easily be computed. As a result of the combination of this method of thinking and the Dunning-Kruger effect, people in our field tend to apply this to the entire world, even where it doesn't fit very well, like biology, geopolitics, sociology, psychology, etc. You see a lot of this on HN. People who seem to think they've figured out some very deep truth about another field that can be explained in one hand-waving paragraph, when really there are lots of important details they're ignoring that make their ideas trivially wrong. Economists have a similar thing going on, I feel. Though I'm not an economist.
- mjburgess 3y ago
  Remember always, computer science is just discrete mathematics with some automatic whiteboards. It is not science. And that's the heart of the problem. The CSci crowd have a somewhat well-motivated inclination to treat abstractions as real objects of study; but have been severely misdirected by learning statistics without the scientific method. This has created a monster: the abstract objects of study are just the associations statistics makes available. You mix those two together and you have flat-out pseudoscience.
  - andoando 3y ago
    Not sure I agree in this regard. We are after all, aiming to create a mental model which describes reproducible steps for creating general intelligence. That is, the product is ultimately going to be some set of abstractions or another. I am not sure what more scientific method you could propose. And we can, in this field produce actual reproducible experiments. Really, more so than any other field.
    - mjburgess 3y ago
      There's nothing to replicate. ML models are associative statistical models of historical data. There are no experimental conditions, no causal properties, no modelled causal mechanisms, no theories at all. "Replication" means that you can reproduce an experiment designed to validate a causal hypothesis. Fitting a function to data isnt an experiment, it's just a way of compressing the data into a more efficient representation. That's all ML is. There are no explanations here (of the data) to assess.

wruza 3y ago

Intuition is a process of slight blind guesses in a system that was built/proposed by a similar organism, in a way that resembles previous systems. Once you get into things like advanced physics, advanced biology, etc, intuition evaporates. Remember these SR/GR things? How intuitive were these? I’d say the current AI is pure intuition in this Q'-ZipQA-A' sense, cause all it does is blind guessing the descent path.