3 ms·

I don’t understand why people jump so readily to seeing intelligence here. Science fiction has as a core, central trope that humans will debase and devalue othe

I don’t understand why people jump so readily to seeing intelligence here. Science fiction has as a core, central trope that humans will debase and devalue other types of life they do not understand. Even the storied Commander Data has to fight for the right to self-determination (probably the best episode of STTNG by the way - ‘The Measure of a Man’). We were so worried that we’d undervalue intelligence when apparently our knee-jerk response is to overvalue it. Perhaps this has changed over time and we’re now primed by science fiction and instincts towards social justice, but I worry that we’re really just undervaluing ourselves. The one thing this 2023 article gets partially correct imo is that any intelligence we see in AI (as of 2026) is our own - not that it’s a mirror but that the intelligence comes from the way that the words are put together, which comes from written human language created by (allegedly) intelligent creatures put in as input in both the training and prompt, among other places. Rearranging and repeating the words, even in context, does not intelligence make. I’m not even convinced that you’re intelligent, dear reader.

garciasn 8d ago
Because to the general public, LLMs are an example of Clarke's Third Law. Most folks, who are not remotely close to even a basic understanding of how LLMs operate at a technical level and only view their output cannot possibly evaluate what they're experiencing other than to believe it's conscious, alive, and/or magic. Most people on Earth try to put what they're seeing into the context of what they understand; mental gymnastics to try and understand what is happening based on their prior experience. They have absolutely 0 understanding of how it works under the hood so, to them, it must be alive.
- emp17344 8d ago
  And this apparently also applies to many HN users, many of whom should know better.
  - garciasn 8d ago
    HN skews more technical, sure; but, that in no way means that they cannot be hoodwinked by behaviors that adhere to C3L.
- red75prime 8d ago
  > a basic understanding of how LLMs operate at a technical level An LLM with CoT is Turing-complete. Training is, basically, compression (the training data gets lossily compressed into the model's weights). The information-theoretic limit of compression is an algorithm that reproduces functionality of a system that produced the training data. No "magic" is required to get to a system that reproduces at least some facets of the human brain functionality. Three years ago I was skeptical that stochastic gradient descent (and other known techniques) are the way. But evidence kept piling up.
  - emil-lp 8d ago
    > An LLM with CoT is Turing-complete. Given arbitrarily large context window.
    - red75prime 8d ago
      Sure. As is the case of every physical realization of the abstract Turing machine: there are some limitations.
  - Marazan 8d ago
    An LLM with CoT and hitherto undiscovered ability to avoid context poisoning/pollution would be more precise.

garciasn 8d ago

Because to the general public, LLMs are an example of Clarke's Third Law. Most folks, who are not remotely close to even a basic understanding of how LLMs operate at a technical level and only view their output cannot possibly evaluate what they're experiencing other than to believe it's conscious, alive, and/or magic. Most people on Earth try to put what they're seeing into the context of what they understand; mental gymnastics to try and understand what is happening based on their prior experience. They have absolutely 0 understanding of how it works under the hood so, to them, it must be alive.

emp17344 8d ago
And this apparently also applies to many HN users, many of whom should know better.
- garciasn 8d ago
  HN skews more technical, sure; but, that in no way means that they cannot be hoodwinked by behaviors that adhere to C3L.
red75prime 8d ago
> a basic understanding of how LLMs operate at a technical level An LLM with CoT is Turing-complete. Training is, basically, compression (the training data gets lossily compressed into the model's weights). The information-theoretic limit of compression is an algorithm that reproduces functionality of a system that produced the training data. No "magic" is required to get to a system that reproduces at least some facets of the human brain functionality. Three years ago I was skeptical that stochastic gradient descent (and other known techniques) are the way. But evidence kept piling up.
- emil-lp 8d ago
  > An LLM with CoT is Turing-complete. Given arbitrarily large context window.
  - red75prime 8d ago
    Sure. As is the case of every physical realization of the abstract Turing machine: there are some limitations.
- Marazan 8d ago
  An LLM with CoT and hitherto undiscovered ability to avoid context poisoning/pollution would be more precise.