3 ms·

Or saying they’re close to AGI because LLM behavior is indistinguishable from thinking to them. Especially here on HN I see “what’s the difference?” arguments a

Or saying they’re close to AGI because LLM behavior is indistinguishable from thinking to them. Especially here on HN I see “what’s the difference?” arguments all the time. It looks like it to me so it must be it. QED.

iainctduncan 1y ago
or rather "while I have never studied psychology, cognition, or philosophy, I can see no difference, so clearly they are thinking!" makes the baby jesus cry
- deleted 1y ago
  [deleted]
- zahlman 1y ago
  I haven't meaningfully studied those things either (i.e. beyond occasionally looking some things up out of curiousity - and for that matter, I've often come across the practice of philosophy in the wild and walked away thinking 'what a lot of vacuous rubbish') and yet the differences are so clear to me that I keep wondering how others can fail to discern them.
more_corn 1y ago
Having studied those things I can say that from their perspective “what’s the difference?” is an entirely legitimate question. Boldly asserting that what LLMS do is not cognition is even worse than asserting that it is. (If you dig deep into how they do what they do we find functional differences, but the outcome are equivalent) The butlerian view is actually a great place to start. He asserts that when we solve a problem through thinking and then express that solution in a machine we’re building a thinking machine. Because it’s an expression of our thought. Take for example the problem of a crow trying to drink from a bottle with a small neck. The crow can’t reach the water. It figures out that pebbles in the bottle raise the level so it drops pebbles till it can reach the water. That’s thinking. It’s non-human thinking, but I think we can all agree. Now express that same thought (use a non water displacement factor to raise the water to a level where it can do something useful) Any machine that does that expresses the cognition behind the solution to that particular problem. That might be a “one shot” machine. Butler argues that as we surround ourselves with those one shot machines we become enslaved to them because we can’t go about our lives without them. We are willing partners in that servitude but slaves because we see to the care and feeding of our machine masters, we reproduce them, we maintain them, we power them. His definition of thinking is quite specific. And any machine that expresses the solution to a problem is expressing a thought. Now what if you had a machine that could generalize and issue solutions to many problems? Might that be a useful tool? Might it be so generally useful that we’d come to depend on it? From the Butlerian perspective our LLMS are already AGI. Namely I can go to Claude and ask for the solution to pretty much any problem I face and get a reasonable answer. In many cases better than I could have done alone. So perhaps if we sat down with a double blind test LLMs are already ASI. (AI that exceeds the capability of normal humans)
- zahlman 1y ago
  > Boldly asserting that what LLMS do is not cognition is even worse than asserting that it is. Why? Understanding concepts like "cognition" is a matter of philosophy, not of science. > He asserts that when we solve a problem through thinking and then express that solution in a machine we’re building a thinking machine. Because it’s an expression of our thought. Yeah, and that premise makes no sense to me. The crow was thinking; the system consisting of (the crow's beak, dropping pebbles into the water + the pebbles) was not. Humanity has built all kinds of machines that use no logic whatsoever in their operation - which make no decisions, and operate in exactly one way when explicitly commanded to start, until explicitly commanded to stop - and yet we have solved human problems by building them.
- jibal 1y ago
  "the outcome are equivalent" Talk about a "bold assertion".
- jemiluv8 1y ago
  > Boldly asserting that what LLMS do is not cognition is even worse than asserting that it is. That's the issue I was driving at. The machine is so convincing. How can we say what it does is not "thinking" when it seems to be breaking down a query like a human does. The distinction between what an AI is and what an LLM is - is so thin that most of us will be ignorant and combine the two because you really need to see what is under the hood before you understand that the responses you're getting are from a "model" - not some sentient thinking machine. But what does it matter if it is from a "model" that understands text? It still produces more or less what other humans produce. Most of us won't care about the difference.
  - jibal 1y ago
    "It still produces more or less what other humans produce." But it doesn't ... and it's important to understand why not.
FabHK 1y ago
> Especially here on HN I see “what’s the difference?” arguments all the time. It looks like it to me so it must be it. QED. To be fair, the Turing Test (a human observer interacting with two terminals, one with a human at the other end, one with an AI, and the human not being reliably able to tell which one is the AI) has long been seen as the operationalization of the concept of general intelligence. In other words, it is precisely so that when it is - by looks, by an external interrogator - indistinguishable from intelligence that it is, in fact, intelligence.
- namaria 1y ago
  You should read the original paper. Turing argued that discussing the abilities of machines to "think" is meaningless and proposes instead to conjecture about whether a digital computer would eventually be able to imitate conversation. I think time has proved that he was right. It is meaningless to discuss things like "Artificial Intelligence". We can only discuss machines in terms of performance, not in terms of subjectivity. Whenever we try to do the latter, we end up in a semantic quagmire. This is the main reason I find the current hype irksome. The performance of machines should be evaluated objectively and in terms of the jobs they need to perform. Attributing 'intelligence' or 'thought' to machines is indeed absurd. The 'imitation game' argument is categorically not that 'if machines appear to be intelligent they in fact are'. What it really is: 'machines cannot think obviously, but what could they do that currently requires a thinking human to be in charge?'. 75 years after Turing published the relevant paper, people are still doing what he called absurd (trying to attribute thought and intelligence to machines), and quoting him to do it. The main insight, that this is a category error and we should look objectively at what jobs need to be performed and how to implement it, is completely lost.

iainctduncan 1y ago

or rather "while I have never studied psychology, cognition, or philosophy, I can see no difference, so clearly they are thinking!" makes the baby jesus cry

deleted 1y ago
[deleted]
zahlman 1y ago
I haven't meaningfully studied those things either (i.e. beyond occasionally looking some things up out of curiousity - and for that matter, I've often come across the practice of philosophy in the wild and walked away thinking 'what a lot of vacuous rubbish') and yet the differences are so clear to me that I keep wondering how others can fail to discern them.

more_corn 1y ago

Having studied those things I can say that from their perspective “what’s the difference?” is an entirely legitimate question. Boldly asserting that what LLMS do is not cognition is even worse than asserting that it is. (If you dig deep into how they do what they do we find functional differences, but the outcome are equivalent) The butlerian view is actually a great place to start. He asserts that when we solve a problem through thinking and then express that solution in a machine we’re building a thinking machine. Because it’s an expression of our thought. Take for example the problem of a crow trying to drink from a bottle with a small neck. The crow can’t reach the water. It figures out that pebbles in the bottle raise the level so it drops pebbles till it can reach the water. That’s thinking. It’s non-human thinking, but I think we can all agree. Now express that same thought (use a non water displacement factor to raise the water to a level where it can do something useful) Any machine that does that expresses the cognition behind the solution to that particular problem. That might be a “one shot” machine. Butler argues that as we surround ourselves with those one shot machines we become enslaved to them because we can’t go about our lives without them. We are willing partners in that servitude but slaves because we see to the care and feeding of our machine masters, we reproduce them, we maintain them, we power them. His definition of thinking is quite specific. And any machine that expresses the solution to a problem is expressing a thought. Now what if you had a machine that could generalize and issue solutions to many problems? Might that be a useful tool? Might it be so generally useful that we’d come to depend on it? From the Butlerian perspective our LLMS are already AGI. Namely I can go to Claude and ask for the solution to pretty much any problem I face and get a reasonable answer. In many cases better than I could have done alone. So perhaps if we sat down with a double blind test LLMs are already ASI. (AI that exceeds the capability of normal humans)

zahlman 1y ago
> Boldly asserting that what LLMS do is not cognition is even worse than asserting that it is. Why? Understanding concepts like "cognition" is a matter of philosophy, not of science. > He asserts that when we solve a problem through thinking and then express that solution in a machine we’re building a thinking machine. Because it’s an expression of our thought. Yeah, and that premise makes no sense to me. The crow was thinking; the system consisting of (the crow's beak, dropping pebbles into the water + the pebbles) was not. Humanity has built all kinds of machines that use no logic whatsoever in their operation - which make no decisions, and operate in exactly one way when explicitly commanded to start, until explicitly commanded to stop - and yet we have solved human problems by building them.
jibal 1y ago
"the outcome are equivalent" Talk about a "bold assertion".
jemiluv8 1y ago
> Boldly asserting that what LLMS do is not cognition is even worse than asserting that it is. That's the issue I was driving at. The machine is so convincing. How can we say what it does is not "thinking" when it seems to be breaking down a query like a human does. The distinction between what an AI is and what an LLM is - is so thin that most of us will be ignorant and combine the two because you really need to see what is under the hood before you understand that the responses you're getting are from a "model" - not some sentient thinking machine. But what does it matter if it is from a "model" that understands text? It still produces more or less what other humans produce. Most of us won't care about the difference.
- jibal 1y ago
  "It still produces more or less what other humans produce." But it doesn't ... and it's important to understand why not.

FabHK 1y ago

> Especially here on HN I see “what’s the difference?” arguments all the time. It looks like it to me so it must be it. QED. To be fair, the Turing Test (a human observer interacting with two terminals, one with a human at the other end, one with an AI, and the human not being reliably able to tell which one is the AI) has long been seen as the operationalization of the concept of general intelligence. In other words, it is precisely so that when it is - by looks, by an external interrogator - indistinguishable from intelligence that it is, in fact, intelligence.

namaria 1y ago
You should read the original paper. Turing argued that discussing the abilities of machines to "think" is meaningless and proposes instead to conjecture about whether a digital computer would eventually be able to imitate conversation. I think time has proved that he was right. It is meaningless to discuss things like "Artificial Intelligence". We can only discuss machines in terms of performance, not in terms of subjectivity. Whenever we try to do the latter, we end up in a semantic quagmire. This is the main reason I find the current hype irksome. The performance of machines should be evaluated objectively and in terms of the jobs they need to perform. Attributing 'intelligence' or 'thought' to machines is indeed absurd. The 'imitation game' argument is categorically not that 'if machines appear to be intelligent they in fact are'. What it really is: 'machines cannot think obviously, but what could they do that currently requires a thinking human to be in charge?'. 75 years after Turing published the relevant paper, people are still doing what he called absurd (trying to attribute thought and intelligence to machines), and quoting him to do it. The main insight, that this is a category error and we should look objectively at what jobs need to be performed and how to implement it, is completely lost.