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Stop Anthropomorphizing Intermediate Tokens as Reasoning/Thinking Traces (2025)

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111–120 of 296 posts

Re: Stop Anthropomorphizing Intermediate Tokens as Reasoning/Thinking Traces (2025)

#111
post #28

Is anthropomorphizing a real problem? From what I know, none of the serious LLM researchers believe it has anything to do with human reasoning, apart from Anthropic with their click-baity terminology like "LLM biology". It's just a metaphor. "Reasoning tokens" is simpler to say than "learned prompt augmentation tokens". I used to (and still do) anthropomorphize things long before LLMs, and I've seen my colleagues do…

"Esta poronga no sabe lo que está haciendo", aunque parezca femenino , en realidad no tiene género .

Re: Stop Anthropomorphizing Intermediate Tokens as Reasoning/Thinking Traces (2025)

#112

Earlier quoted context omitted.

“ This makes the output extremely like human thinking when solving a problem.” This sounds a little like someone saying a lightbulbs output is extremely like the output of stellar fusion. In one sense, yes. Bulbs are in fact designed to take over when our nearest star is beyond the horizon. But that really doesn’t mean you call the bulbs mini stars.

How much is the process of a human child in grade school working through a 3-digit x 3-digit multiplication problem (123 * 456) like a GRPO model with thinking tokens doing the same? Humans are not born being able to achieve that. It is learned behavior. You and everyone else will remember their teacher saying, "Check your work!" Both the human child and the model work through multiplication problems using the same t…

How much is the process of a human child in grade school working through a 3-digit x 3-digit multiplication problem (123 * 456) like a GRPO model with thinking tokens doing the same?

Very little, if you bother to give the biology of the child at least a cursory glance.

Let’s take a short peek:

1. Assuming this is normal grade school, and inflicts math upon children earlier in the day, this is somewhere between 7 and 10/11 am, let’s say? At this point, depending on the age, gender, and maturity of the child, every neuron in their brain involved in math is likely off their midday peak in cognitive function.

If we move the class to later, a different subset of students will be at the peak.

As far as I am aware, GRPO models do not have such internal temporal rhythms driving their behavior that will shape their performance.

2. How well a given child performs will depend on how hungry they are. But not deterministically. If you trivially think each child is like a computer, you may think the rich kid who had a breakfast buffet before coming to school will do better than the half-starved child of a janitor, but that child might mind the lesson with greater intensity. Or not. It’s not something you can pre-calculate with any certainty.

While chip to chip variability is certainly known, I’m yet to hear of a chip deciding to do math better and faster than its fellow chips to prove a point. Or to do significantly worse because it’s distracted by the bird on the window sill.

What you are noticing is that there are limited ways to solve a 3x3 digit multiplication. Humans, having standardized the process, have now found a way to record it and plug it into correctly translated signal so the same accurate result can be had without using our own minds in the moment.

But where I’d not remotely be shocked if a kid from an uncontacted tribe figured out 3 digit multiplication to keep track of his stone collection, I’d be highly shocked if an H100 that was dumped in the trash by accident somehow figured out anything at all. In fact, if it manage to move any of its electrons around on its own, it would be a certified miracle.

And then we could talk about there being real similarity even though the specific atomic composition is different.*

Re: Stop Anthropomorphizing Intermediate Tokens as Reasoning/Thinking Traces (2025)

#113

Earlier quoted context omitted.

Because plenty of people, even ones that should know better, really believe it's a conscious, thinking entity, not just some turn of phrase. I have a coworker that spends at least 10 hours a week arguing with his like you would with a conscious person. I've gently tried to explain it's like arguing with your compiler for giving you an incoherent error message - it's pointless. It doesn't understand, it can't understa…

> if it could, you arguing with it isn't going to make it "learn" or act differently. Are you talking about a specific harness that doesn't have context retention mechanisms? For example, ChatGPT with disabled memory feature? Or in general where "it" is a fixed-weights network? The latter is trivially true, of course.

Why argue with it? Why not just edit the memory yourself?

Re: Stop Anthropomorphizing Intermediate Tokens as Reasoning/Thinking Traces (2025)

#114

Earlier quoted context omitted.

Do you have a working definition of "conscious"?

We do have entry and exit conditions. We can disrupt it and study the dynamics of the disruption. We have a good sense of the many mechanisms at play that undergird it. What we lack is a full map of the exact process from sensation to consciousness across all modalities. And I’m afraid when it comes to interception, we can’t unless we observe every one of the 36 trillion or so cells in a human body, as well as the 36…

Whether human consciousness exists on neural nets or otherwise doesn't disallow an ANN in a particular configuration from being conscious. You might as well argue that human consciousness requires biological neurons, so artificial consciousness can't exist.

Re: Stop Anthropomorphizing Intermediate Tokens as Reasoning/Thinking Traces (2025)

#115
post #74

Earlier quoted context omitted.

But how is that any different than people being misled by real humans saying words that reflect real thinking, but which are actually dead wrong? The fallacy here is "thinking == correct", not "tokens == thinking"

Because the real thinking still cost the other human the same-ish energy it costs you to put words together, and because after all, the source is a human and not a machine, no, this is very different. Being mislead may be the shared outcome. But why is different category of source of the mistake and the cost to producer of making the mistake not relevant in this discussion? Where else in science do you brush aside al…

Why aren't humans simply biological machines?

There is no "science" that GP is brushing aside. You need to provide repeatable observations or experiments that GP is ignoring.

Re: Stop Anthropomorphizing Intermediate Tokens as Reasoning/Thinking Traces (2025)

#116
post #63
post #28

Is anthropomorphizing a real problem? From what I know, none of the serious LLM researchers believe it has anything to do with human reasoning, apart from Anthropic with their click-baity terminology like "LLM biology". It's just a metaphor. "Reasoning tokens" is simpler to say than "learned prompt augmentation tokens". I used to (and still do) anthropomorphize things long before LLMs, and I've seen my colleagues do…

Yes it is a very serious problem because it confuses a lot of folks with a great deal of power like judges and policymakers. The first book I ever read on ML (late 90s) dedicated the entire first or second chapter exploring the distinctions between artificial and biological neurons, and even talked a bit about the philosophy of modelling. I still remember thinking back then why would the authors spend so many pages o…

They spent so many pages discussing it only to show that the mechanism for how ANNs work is different from the mechanism for how biological brains work. It says nothing about whether they can compute the same things.

Re: Stop Anthropomorphizing Intermediate Tokens as Reasoning/Thinking Traces (2025)

#117
post #50
post #28

Is anthropomorphizing a real problem? From what I know, none of the serious LLM researchers believe it has anything to do with human reasoning, apart from Anthropic with their click-baity terminology like "LLM biology". It's just a metaphor. "Reasoning tokens" is simpler to say than "learned prompt augmentation tokens". I used to (and still do) anthropomorphize things long before LLMs, and I've seen my colleagues do…

Simplifying terminology is not a problem. The providers intentionally choosing terminology to make people think it's something it's not is a problem. I hate the term agent. Calling them companions as some do is just gross.

"Agent" is standard reinforcement learning terminology, used in Chris Watkins's thesis introducing Q-Learning in 1989.

Re: Stop Anthropomorphizing Intermediate Tokens as Reasoning/Thinking Traces (2025)

#118

Although I 100% agree that the core mechanism of GRPO is purely mechanical token-by-token probability generation, because RL only rewards exact final answers, the training forces the model to develop error-correction habits. This makes the output extremely like human thinking when solving a problem. It's like the order of the thinking tokens is what causes it to get that sweet, delicious reward, and this order seems…

“ This makes the output extremely like human thinking when solving a problem.” This sounds a little like someone saying a lightbulbs output is extremely like the output of stellar fusion. In one sense, yes. Bulbs are in fact designed to take over when our nearest star is beyond the horizon. But that really doesn’t mean you call the bulbs mini stars.

The visible light produced by both an incandescent bulb and a star is a result of black body radiation, but otherwise, I don't understand your point. A light bulb produces light, something we might have relied on stars to do before. An LLM produces thoughts, something we might have relied on people to do before. Nobody is claiming the process by which the thoughts are produced is the same, only that they both produce thoughts, just as nobody claims the process by which an LED produces light is the same as the process a star uses to produce light, only that they both produce light.

Re: Stop Anthropomorphizing Intermediate Tokens as Reasoning/Thinking Traces (2025)

#119

Earlier quoted context omitted.

Because the real thinking still cost the other human the same-ish energy it costs you to put words together, and because after all, the source is a human and not a machine, no, this is very different. Being mislead may be the shared outcome. But why is different category of source of the mistake and the cost to producer of making the mistake not relevant in this discussion? Where else in science do you brush aside al…

Why aren't humans simply biological machines? There is no "science" that GP is brushing aside. You need to provide repeatable observations or experiments that GP is ignoring.

Please define "simply biological machines". I'm not sure "biological machine" had a proper definition. What's machine like about biology exactly?

Re: Stop Anthropomorphizing Intermediate Tokens as Reasoning/Thinking Traces (2025)

#120

Earlier quoted context omitted.

We do have entry and exit conditions. We can disrupt it and study the dynamics of the disruption. We have a good sense of the many mechanisms at play that undergird it. What we lack is a full map of the exact process from sensation to consciousness across all modalities. And I’m afraid when it comes to interception, we can’t unless we observe every one of the 36 trillion or so cells in a human body, as well as the 36…

Whether human consciousness exists on neural nets or otherwise doesn't disallow an ANN in a particular configuration from being conscious. You might as well argue that human consciousness requires biological neurons, so artificial consciousness can't exist.

Odd. Why don't the details of how consciousness arises in one system inform your judgment of whether it can exist in a different system that only has partial structural overlap? Seems wildly convenient. Where else in science can you show me such a comparable situation in how you define properties?
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