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When Weizenbaum demonstrated Eliza to his colleagues, some thought there was an intelligent consciousness at the heart of it. Few even continued to believe this

When Weizenbaum demonstrated Eliza to his colleagues, some thought there was an intelligent consciousness at the heart of it. Few even continued to believe this after they were shown the source code, which they were able to read and understand. Human consciousness is full of biases and the most advanced AI cannot reliably determine which of two floats is bigger or even solve really simple logic puzzles for little kids. But I can see how these things mesmerize true believers.

hnfong 2y ago
At this point bringing up the ELIZA argument is basically bad faith gaslighting… Finding bugs in some models doesn’t mean you have a point about intelligence. If somebody could apply a similar argument to dismiss human intelligence, you don’t have a point. And here it goes: the most advanced human intelligence can’t reliably multiply large numbers or recall digits of Pi. Obviously humans are dumber than pocket calculators.
- psb217 2y ago
  Your counterargument is invalid. The most advanced human intelligence invented (or discovered) concepts like multiplication, pi, etc., and created tools to work around the ways in which these concepts aren't well handled by their biological substrate. When machine intelligences start inventing biological tools to overcome the limits of their silicon existence, you'll have a point.
  - biomcgary 2y ago
    Isn't the comment you are responding to an example of: "When machine intelligences start inventing biological tools to overcome the limits of their silicon existence, you'll have a point"?
  - mypalmike 2y ago
    Designing biological tools is not a commonly accepted bar for AGI.
K0balt 2y ago
While it is true that LLM’s lack agency and have many weaknesses, they form a critical part of what machine learning has lacked until transformers became all of the rage. The things that LLM’s are bad at are largely solved problems using much simpler technology. There is no reason that LLM’s have to be the only component in an intelligent agent. Biological brains have Specialized structures for specialized tasks like arithmetic. The solution is probably integration of LLMs as a part of a composite system that includes database storage, a code execution environment, and multiple agents to form a goal directed posit - evaluate loop. I’ve had pretty remarkable success with this architecture running on 12b models and I’m a nobody with no resources. LLM’s by themselves just come up with the first thing that crosses their”mind”. It shouldn’t be surprising that the very first unfiltered guess about a solution might be suboptimal. There is a vast amount of knowledge embedded in our cultural matrix, and a lot of that is captured in the common crawl and other datasets.llms are like a search engine for that data , based on meaning rather than semantics.
ben_w 2y ago
> the most advanced AI cannot reliably determine which of two floats is bigger Some of the most advanced AI are tool users and can both write and crucially also execute python, and embed the output in their responses. > or even solve really simple logic puzzles for little kids. As given in a recent discussion: https://chatgpt.com/share/ee013797-a55c-4685-8f2b-87f1b455b450 https://chatgpt.com/share/ee013797-a55c-4685-8f2b-87f1b455b4... (Custom instructions, in case you're surprised by the opening of the response).
slashdave 2y ago
Especially if you remember that the change needed for the first "breakthrough" (GPT4) was RLHF. That is, a model that was specifically trained to mesmerize.

hnfong 2y ago

At this point bringing up the ELIZA argument is basically bad faith gaslighting… Finding bugs in some models doesn’t mean you have a point about intelligence. If somebody could apply a similar argument to dismiss human intelligence, you don’t have a point. And here it goes: the most advanced human intelligence can’t reliably multiply large numbers or recall digits of Pi. Obviously humans are dumber than pocket calculators.

psb217 2y ago
Your counterargument is invalid. The most advanced human intelligence invented (or discovered) concepts like multiplication, pi, etc., and created tools to work around the ways in which these concepts aren't well handled by their biological substrate. When machine intelligences start inventing biological tools to overcome the limits of their silicon existence, you'll have a point.
- biomcgary 2y ago
  Isn't the comment you are responding to an example of: "When machine intelligences start inventing biological tools to overcome the limits of their silicon existence, you'll have a point"?
- mypalmike 2y ago
  Designing biological tools is not a commonly accepted bar for AGI.

K0balt 2y ago

While it is true that LLM’s lack agency and have many weaknesses, they form a critical part of what machine learning has lacked until transformers became all of the rage. The things that LLM’s are bad at are largely solved problems using much simpler technology. There is no reason that LLM’s have to be the only component in an intelligent agent. Biological brains have Specialized structures for specialized tasks like arithmetic. The solution is probably integration of LLMs as a part of a composite system that includes database storage, a code execution environment, and multiple agents to form a goal directed posit - evaluate loop. I’ve had pretty remarkable success with this architecture running on 12b models and I’m a nobody with no resources. LLM’s by themselves just come up with the first thing that crosses their”mind”. It shouldn’t be surprising that the very first unfiltered guess about a solution might be suboptimal. There is a vast amount of knowledge embedded in our cultural matrix, and a lot of that is captured in the common crawl and other datasets.llms are like a search engine for that data , based on meaning rather than semantics.

ben_w 2y ago

> the most advanced AI cannot reliably determine which of two floats is bigger Some of the most advanced AI are tool users and can both write and crucially also execute python, and embed the output in their responses. > or even solve really simple logic puzzles for little kids. As given in a recent discussion: https://chatgpt.com/share/ee013797-a55c-4685-8f2b-87f1b455b450 https://chatgpt.com/share/ee013797-a55c-4685-8f2b-87f1b455b4... (Custom instructions, in case you're surprised by the opening of the response).

slashdave 2y ago

Especially if you remember that the change needed for the first "breakthrough" (GPT4) was RLHF. That is, a model that was specifically trained to mesmerize.