5 ms·

This is easily explained by accepting that there is no such thing as LRMs. LRMs are just LLMs that iterate on its own answers more (or provides itself more cont

by ivape 1y ago

This is easily explained by accepting that there is no such thing as LRMs. LRMs are just LLMs that iterate on its own answers more (or provides itself more context information of a certain type). The reasoning loop on an "LRM" will be equivalent to asking a regular LLM to "refine" its own response, or "consider" additional context of a certain type. There is no such thing as reasoning basically, as it was always a method to "fix" hallucinations or provide more context automatically, nothing else. These big companies baked in one of the hackiest prompt engineering tricks that your typical enthusiast figured out long ago and managed to brand it and profit off it. The craziest part about this was Deepseek was able to cause a multi billion dollar drop and pump of AI stocks with this one trick. Crazy times.

AlienRobot 1y ago
Is that what "reasoning" means? That sounds pretty ridiculous. I've thought before that AI is as "intelligent" as your smartphone is "smart," but I didn't think "reasoning" would be just another buzzword.
- ngneer 1y ago
  I am not too familiar with the latest hype, but "reasoning" has a very straightforward definition in my mind. For example, can the program in question derive new facts from old ones in a logically sound manner. Things like applying modus ponens. (A and A => B) => B. Or, all men are mortal and Socrates is a man, and therefore Socrates is mortal. If the program cannot deduce new facts, then it is not reasoning, at least not by my definition.
  - dist-epoch 1y ago
    When people say LLMs can't do X, I like to try it. Q: Complete 3 by generating new knowledge: 1. today is warm 2. cats likes warm temperatures 3. A: Therefore, a cat is likely to be enjoying the weather today. Q: does the operation to create new knowledge you did have a specific name? A: ... Deductive Reasoning Q: does the operation also have a Latin name? A: ... So, to be precise, you used a syllogismus (syllogism) that takes the form of Modus Ponens to make a deductio (deduction). https://aistudio.google.com/app/prompts/1LbEGRnzTyk-2IDdn53tC0HMhCL-yO8qU https://aistudio.google.com/app/prompts/1LbEGRnzTyk-2IDdn53t... People then say "of course it could do that, it just pattern matched a Logic text book. I meant in a real example, not an artificially constructed one like this one. In a complex scenario LLMs obviously can't do Modus Ponens.
    - ngneer 1y ago
      I do not know whether the state of the art is able to reason or not. The textbook example you gave is admittedly not very interesting. What you are hearing from people is that parroting is not reasoning, which is true. I wonder if the state of the art can reason its way through the following: "Adam can count to 14000. Can Adam count to 13500?" The response needs to be affirmative for every X1 and X2 such that X2 <= X1. That is reasoning. Anything else is not reasoning. The response when X2 > X1 is less interesting. But, as a human it might be "Maybe, if Adam has time" or "Likely, since counting up to any number uses the same algorithm" or "I don't know". Seems ChatGPT can cope with this. Other examples are easy to come up with, too. There must be benchmarks for this. Input to ChatGPT: "Adam can lift 1000 pounds of steel. Can Adam lift 1000 pounds of feathers?" Output from ChatGPT: "1,000 pounds of feathers would be much easier for Adam to lift compared to 1,000 pounds of steel, because feathers are much lighter and less dense." So, maybe not there yet...
      - dist-epoch 1y ago
        > "Adam can lift 1000 pounds of steel. Can Adam lift 1000 pounds of feathers?" Worked for me: https://chatgpt.com/share/6844813a-6e4c-8006-b560-c0be223eebf5 https://chatgpt.com/share/6844813a-6e4c-8006-b560-c0be223eeb... gemma3-27b, a small model, had an interesting take: > This is a classic trick question! > While Adam can lift 1000 pounds, no, he likely cannot lift 1000 pounds of feathers. > Volume: Feathers take up a huge amount of space for their weight. 1000 pounds of feathers would be an enormous volume – likely far too large for Adam to even get under, let alone lift. He'd be trying to lift a massive, bulky cloud. > Practicality: Even if he could somehow get it under a barbell, the feathers would shift and compress, making a secure grip impossible. > The question plays on our understanding of weight versus volume. It's designed to make you focus on the "1000 pounds" and forget about the practicalities of lifting something so voluminous. Tried the counting question on the smallest model, gemma-3n-34b, it can run on a smartphone: > Yes, if Adam can count to 14000, he can definitely count to 13500. Counting to a smaller number is a basic arithmetic operation. 13500 is less than 14000.
        ngneer 1y ago
- JSR_FDED 1y ago
  A reasoning model is an LLM that has had additional training phases that reward problem solving abilities. (But in a black box way - it’s not clear if the model is learning actual reasoning or better pattern matching, or memorization, or heuristics… maybe a bit of everything).
meroes 1y ago
Yep. This is exactly the conclusion I reached as an RLHF'er. Reasoning/LRM/SxS/CoT is "just" more context. There never was reasoning. But of course, more context can be good.
Too 1y ago
The million dollar question is how far can one get on this trick. Maybe this is exactly how our own brains operate? If not, what fundamental building blocks are missing to get there.
- bwfan123 1y ago
  > If not, what fundamental building blocks are missing to get there If I were to guess, the missing building block is the ability to abstract - which is the ability to create a symbol to represent something. Concrete example of abstraction is seen in the axioms of lambda calculus. 1) ability to posit a variable, 2) ability to define a function using said variable, and 3) the ability to apply functions to things. Abstraction arises from a process in the brain which we have not understood yet and could be outside of computation as we know it per [1] [1] https://www.amazon.com/Emperors-New-Mind-Concerning-Computers/dp/0192861980 https://www.amazon.com/Emperors-New-Mind-Concerning-Computer...
  - bird0861 1y ago
    No. It's not microtubules. Enough with the g-darn microtubules already. https://www.biorxiv.org/content/10.1101/712794v1 https://www.biorxiv.org/content/10.1101/712794v1 "We used an antimicrotubular agent (parbendazole) and disrupted microtubular dynamics in paramecium to see if microtubules are an integral part of information storage and processing in paramecium’s learning process. We observed that a partial allosteric modulator of GABA (midazolam) could disrupt the learning process in paramecium, but the antimicrotubular agent could not. Therefore, our results suggest that microtubules are probably not vital for the learning behavior in P. caudatum. Consequently, our results call for a further revisitation of the microtubular information processing hypothesis."

by ivape 1y ago

AlienRobot 1y ago

Is that what "reasoning" means? That sounds pretty ridiculous. I've thought before that AI is as "intelligent" as your smartphone is "smart," but I didn't think "reasoning" would be just another buzzword.

ngneer 1y ago
I am not too familiar with the latest hype, but "reasoning" has a very straightforward definition in my mind. For example, can the program in question derive new facts from old ones in a logically sound manner. Things like applying modus ponens. (A and A => B) => B. Or, all men are mortal and Socrates is a man, and therefore Socrates is mortal. If the program cannot deduce new facts, then it is not reasoning, at least not by my definition.
- dist-epoch 1y ago
  When people say LLMs can't do X, I like to try it. Q: Complete 3 by generating new knowledge: 1. today is warm 2. cats likes warm temperatures 3. A: Therefore, a cat is likely to be enjoying the weather today. Q: does the operation to create new knowledge you did have a specific name? A: ... Deductive Reasoning Q: does the operation also have a Latin name? A: ... So, to be precise, you used a syllogismus (syllogism) that takes the form of Modus Ponens to make a deductio (deduction). https://aistudio.google.com/app/prompts/1LbEGRnzTyk-2IDdn53tC0HMhCL-yO8qU https://aistudio.google.com/app/prompts/1LbEGRnzTyk-2IDdn53t... People then say "of course it could do that, it just pattern matched a Logic text book. I meant in a real example, not an artificially constructed one like this one. In a complex scenario LLMs obviously can't do Modus Ponens.
  - ngneer 1y ago
    I do not know whether the state of the art is able to reason or not. The textbook example you gave is admittedly not very interesting. What you are hearing from people is that parroting is not reasoning, which is true. I wonder if the state of the art can reason its way through the following: "Adam can count to 14000. Can Adam count to 13500?" The response needs to be affirmative for every X1 and X2 such that X2 <= X1. That is reasoning. Anything else is not reasoning. The response when X2 > X1 is less interesting. But, as a human it might be "Maybe, if Adam has time" or "Likely, since counting up to any number uses the same algorithm" or "I don't know". Seems ChatGPT can cope with this. Other examples are easy to come up with, too. There must be benchmarks for this. Input to ChatGPT: "Adam can lift 1000 pounds of steel. Can Adam lift 1000 pounds of feathers?" Output from ChatGPT: "1,000 pounds of feathers would be much easier for Adam to lift compared to 1,000 pounds of steel, because feathers are much lighter and less dense." So, maybe not there yet...
    - dist-epoch 1y ago
      > "Adam can lift 1000 pounds of steel. Can Adam lift 1000 pounds of feathers?" Worked for me: https://chatgpt.com/share/6844813a-6e4c-8006-b560-c0be223eebf5 https://chatgpt.com/share/6844813a-6e4c-8006-b560-c0be223eeb... gemma3-27b, a small model, had an interesting take: > This is a classic trick question! > While Adam can lift 1000 pounds, no, he likely cannot lift 1000 pounds of feathers. > Volume: Feathers take up a huge amount of space for their weight. 1000 pounds of feathers would be an enormous volume – likely far too large for Adam to even get under, let alone lift. He'd be trying to lift a massive, bulky cloud. > Practicality: Even if he could somehow get it under a barbell, the feathers would shift and compress, making a secure grip impossible. > The question plays on our understanding of weight versus volume. It's designed to make you focus on the "1000 pounds" and forget about the practicalities of lifting something so voluminous. Tried the counting question on the smallest model, gemma-3n-34b, it can run on a smartphone: > Yes, if Adam can count to 14000, he can definitely count to 13500. Counting to a smaller number is a basic arithmetic operation. 13500 is less than 14000.
      - ngneer 1y ago
JSR_FDED 1y ago
A reasoning model is an LLM that has had additional training phases that reward problem solving abilities. (But in a black box way - it’s not clear if the model is learning actual reasoning or better pattern matching, or memorization, or heuristics… maybe a bit of everything).

meroes 1y ago

Yep. This is exactly the conclusion I reached as an RLHF'er. Reasoning/LRM/SxS/CoT is "just" more context. There never was reasoning. But of course, more context can be good.

Too 1y ago

The million dollar question is how far can one get on this trick. Maybe this is exactly how our own brains operate? If not, what fundamental building blocks are missing to get there.

bwfan123 1y ago
> If not, what fundamental building blocks are missing to get there If I were to guess, the missing building block is the ability to abstract - which is the ability to create a symbol to represent something. Concrete example of abstraction is seen in the axioms of lambda calculus. 1) ability to posit a variable, 2) ability to define a function using said variable, and 3) the ability to apply functions to things. Abstraction arises from a process in the brain which we have not understood yet and could be outside of computation as we know it per [1] [1] https://www.amazon.com/Emperors-New-Mind-Concerning-Computers/dp/0192861980 https://www.amazon.com/Emperors-New-Mind-Concerning-Computer...
- bird0861 1y ago
  No. It's not microtubules. Enough with the g-darn microtubules already. https://www.biorxiv.org/content/10.1101/712794v1 https://www.biorxiv.org/content/10.1101/712794v1 "We used an antimicrotubular agent (parbendazole) and disrupted microtubular dynamics in paramecium to see if microtubules are an integral part of information storage and processing in paramecium’s learning process. We observed that a partial allosteric modulator of GABA (midazolam) could disrupt the learning process in paramecium, but the antimicrotubular agent could not. Therefore, our results suggest that microtubules are probably not vital for the learning behavior in P. caudatum. Consequently, our results call for a further revisitation of the microtubular information processing hypothesis."