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by Workaccount2 448 days ago
Thinking and thought have no solid definition. We can't say Claude doesn't "think" because we don't even know what a human thinking actually is.

Given the lack of a solid definition for thinking and test to measure it, I think using the terminology colloquially is a totally fair play.

3 comments

I view LLM's as valuable algorithms capable of generating relevant text based on queries given to them.

> Thinking and thought have no solid definition. We can't say Claude doesn't "think" because we don't even know what a human thinking actually is.

I did not assert:

  Claude doesn't "think" ...
What I did assert was that the onus is on the author(s) which write articles/posts such as the one cited to support their assertion that their systems qualify as "thinking" (for any reasonable definition of same).

Short of author(s) doing so, there is little difference between unsupported claims of "LLM's thinking" and 19th century snake oil[0] salesmen.

0 - https://en.wikipedia.org/wiki/Snake_oil

No one says that a thermostat is "thinking" of turning on the furnace, or that a nightlight is "thinking it is dark enough to turn the light on". You are just being obtuse.
Yes. A thermostat involves a change of state from A to B. A computer is the same: its state at t causes its state at t+1, which causes its state at t+2, and so on. Nothing else is going on. An LLM is no different: an LLM is simply a computer that is going through particular states.

Thought is not the same as a change of (brain) state. Thought is certainly associated with change of state, but can't be reduced to it. If thought could be reduced to change of state, then the validity/correctness/truth of a thought could be judged with reference to its associated brain state. Since this is impossible (you don't judge whether someone is right about a math problem or an empirical question by referring to the state of his neurology at a given point in time), it follows that an LLM can't think.

>Thought is certainly associated with change of state, but can't be reduced to it.

You can effectively reduce continuously dynamic systems to discreet steps. Sure, you can always say that the "magic" exists between the arbitrarily small steps, but from a practical POV there is no difference.

A transistor has a binary on or off. A neuron might have ~infinite~ levels of activation.

But in reality the ~infinite~ activation level can be perfectly modeled (for all intents and purposes), and computers have been doing this for decades now (maybe not with neurons, but equivalent systems). It might seem like an obvious answer, that there is special magic in analog systems that binary machines cannot access, but that is wholly untrue. Science and engineering have been extremely successful interfacing with the analog reality we live in, precisely because the digital/analog barrier isn't too big of a deal. Digital systems can do math, and math is capable of modeling analog systems, no problem.

It's not a question of discrete vs continuous, or digital vs analog. Everything I've said could also apply if a transistor could have infinite states.

Rather, the point is that the state of our brain is not the same as the content of our thoughts. They are associated with one another, but they're not the same. And the correctness of a thought can be judged only by reference to its content, not to its associated state. 2+2=4 is correct, and 2+2=5 is wrong; but we know this through looking at the content of these thoughts, not through looking at the neurological state.

But the state of the transistors (and other components) is all a computer has. There are no thoughts, no content, associated with these states.

It seems that the only barrier between brain state and thought contents is a proper measurement tool and decoder, no?

We can already do this at an extremely basic level, mapping brain states to thoughts. The paraplegic patient using their thoughts to move the mouse cursor or the neuroscientist mapping stress to brain patterns.

If I am understanding your position correctly, it seems that the differentiation between thoughts and brain states is a practical problem not a fundamental one. Ironically, LLMs have a very similar problem with it being very difficult to correlate model states with model outputs. [1]

[1]https://www.anthropic.com/research/mapping-mind-language-mod...

There is undoubtedly correlation between neurological state and thought content. But they are not the same thing. Even if, theoretically, one could map them perfectly (which I doubt is possible but it doesn't affect my point), they would remain entirely different things.

The thought that "2+2=4", or the thought "tiger", are not the same thing as the brain states that makes them up. A tiger, or the thought of a tiger, is different from the neurological state of a brain that is thinking about a tiger. And as stated before, we can't say that "2+2=4" is correct by referring to the brain state associated with it. We need to refer to the thought itself to do this. It is not a practical problem of mapping; it is that brain states and thoughts are two entirely different things, however much they may correlate, and whatever causal links may exist between them.

This is not the case for LLMs. Whatever problems we may have in recording the state of the CPUs/GPUs are entirely practical. There is no 'thought' in an LLM, just a state (or plurality of states). An LLM can't think about a tiger. It can only switch on LEDs on a screen in such a way that we associate the image/word with a tiger.

>Rather, the point is that the state of our brain is not the same as the content of our thoughts.

Based on what exactly ? This is just an assertion. One that doesn't seem to have much in the way of evidence. 'It's not the same trust me bro' is the thesis of your argument. Not very compelling.

It's not difficult. When you think about a tiger, you are not thinking about the brain state associated with said thought. A tiger is different from a brain state.

We can safely generalize, and say the content of a thought is different from its associated brain state.

Also, as I said

>> The correctness of a thought can be judged only by reference to its content, not to its associated state. 2+2=4 is correct, and 2+2=5 is wrong; but we know this through looking at the content of these thoughts, not through looking at the neurological state.

This implies that state != content.

Please, take the pencil and draw the line between thinking and non-thinking systems. Hell I'll even take a line drawn between thinking and non-thinking organisms if you have some kind of bias towards sodium channel logic over silicon trace logic. Good luck.
Even if you can't define the exact point that A becomes not-A, it doesn't follow that there is no distinction between the two. Nor does it follow that we can't know the difference. That's a pretty classic fallacy.

For example, you can't name the exact time that day becomes night, but it doesn't follow that there is no distinction.

A bunch of transistors being switched on and off, no matter how many there are, is no more an example of thinking than a single thermostat being switched on and off. OTOH, if we can't think, then this conversation and everything you're saying and "thinking" is meaningless.

So even without a complete definition of thought, we can see that there is a distinction.

> For example, you can't name the exact time that day becomes night, but it doesn't follow that there is no distinction.

There is actually a very detailed set of definitions of the multiple stages of twilight, including the last one which defines the onset of what everyone would agree is "night".

The fact that a phenomena shows a continuum by some metric does not mean that it is not possible to identify and label points along that continuum and attach meaning to them.

Looks like we replied to each others comments at the same time, haha
Your assertion that sodium channel logic and silicon trace logic are 100% identical is the primary problem. It's like claiming that a hydraulic cylinder and a bicep are 100% equivalent because they both lift things - they are not the same in any way.
People chronically get stuck in this pit. Math is substrate independent. If the process is physical (i.e. doesn't draw on magic) then it can be expressed with mathematics. If it can be expressed with mathematics, anything that does math can compute it.

The math is putting the crate up on the rack. The crate doesn't act any different based on how it got up there.

Or submarines swim ;)
think about it more
Honestly, arguing seems futile when it comes to opinions like GP. Those opinions resemble religious zealotry to me in that they take for granted that only humans can think. Any determinism of any kind in a non-human is seized upon as proof its mere clockwork, yet they can’t explain how humans think in order to contrast it.
> Honestly, arguing seems futile when it comes to opinions like GP. Those opinions resemble religious zealotry to me in that they take for granted that only humans can think. Any determinism of any kind in a non-human is seized upon as proof its mere clockwork, yet they can’t explain how humans think in order to contrast it.

Putting aside the ad hominems, projections, and judgements, here is a question for you:

If I made a program where a NPC[0] used the A-star[1] algorithm to navigate a game map, including avoiding obstacles and using the shortest available path to reach its goal, along with identifying secondary goal(s) should there be no route to the primary goal, does that qualify to you as the NPC "thinking"?

0 - https://en.wikipedia.org/wiki/Non-player_character

1 - https://en.wikipedia.org/wiki/A*_search_algorithm

Answer: I suppose no? But my point is only this:

1. People with the "AI isn't thinking" opinions move the goalposts, the borderline between "just following a deterministic algorithm" and "thinking" wherever needed in order to be right.

2. I argue that the brain itself must either be deterministic (just wildly complex) or, for lack of a better word, supernatural. If it's not deterministic, only God knows how our thinking process works. Every single person postulating about whether AI is "thinking" cannot fully explain why a human chooses a particular action, just as AI researchers can't explain why Claude does a certain thing in all scenarios. Therefore they are much more similar than they are different.

3. But really, the important thing is, unless you're approaching this from a religious POV (which is arguably much more interesting) the obsessive sorting of highly complex and not-even-remotely-fully-understood processes into "thinking" and "NOT thinking" groups is pointless and silly.

> 1. People with the "AI isn't thinking" opinions move the goalposts, the borderline between "just following a deterministic algorithm" and "thinking" wherever needed in order to be right.

I did not present an opinion regarding whether "AI thinks" or not, but instead said:

  The onus of clarifying the article's assertions ...

  As it pertains to anthropomorphizing an algorithm (a.k.a. 
  stating it "thinks") is on the author(s).
As to the concept of thinking, regardless of entity considered, I proffer the topic a philosophical one having no "right or wrong" answer so much as having an opportunity to deepen enlightenment of those who contemplate question.