[HN Gopher] Controllable Fast and Slow Thinking by Learning with...
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       Controllable Fast and Slow Thinking by Learning with Randomized
       Reasoning Traces
        
       Author : hislaziness
       Score  : 29 points
       Date   : 2024-10-23 03:51 UTC (4 days ago)
        
 (HTM) web link (arxiv.org)
 (TXT) w3m dump (arxiv.org)
        
       | hislaziness wrote:
       | As I understand, the LLM uses the techniques of searchformer -
       | https://arxiv.org/abs/2402.14083. To do "slow thinking" doing a
       | A* search using a transofrmer.
        
       | aithrowawaycomm wrote:
       | AI researchers need to read more cognitive science. It is
       | genuinely embarrassing how often you see "Thinking Fast and Slow"
       | + some 50-year-old paper as the only citations, because this
       | statement:                 In human cognition theory, human
       | thinking is governed by two systems: the fast and intuitive
       | System 1 and the slower but more deliberative System 2.
       | 
       | is intuitive, psychologically seductive, and _blatantly wrong._
       | [1] There is no scientific distinction between System 1 and
       | System 2, the very idea is internally incoherent and contradicts
       | the evidence. Yet tons of ignorant people believe it. And
       | apparently AI researchers sincerely believe "ANN inference =
       | System 1 thinking." This is ridiculous: ANN inference = Pavlovian
       | response, as found in nematodes and jellyfish. But System 1
       | thinking is related to common sense found in all vertebrates, and
       | absent from all existing AI. We don't have a clue how to make a
       | computer capable of System 1 thinking.
       | 
       | This isn't just pedantry: the initial "System 1 = inference"
       | error makes "System 2 = chain-of-thought" especially flawed. CoT
       | in transformer LLMs helps solve O(n) problems but struggles with
       | O(n^2). The observation that a O(n^2) problem can be broken down
       | into n separate O(n) problems is ultimately due to _system 1_
       | reasoning: it is obviously true. But it is only obviously true to
       | smart things like humans and pigeons. Transformers do not seem
       | smart enough to grasp it: system 2 thinking must be  "glued
       | together" by tautologies or axioms, and we can only recognize
       | tautologies or discover axioms because of system 1. If the
       | problem is more complex than O(n) these tautologies and axioms
       | must be provided to the LLM, either with a careful prompt or
       | exhaustive data.
       | 
       | Kahneman's book has been largely repudiated on the science. That
       | doesn't mean it isn't a useful way to understand the kinds of
       | errors humans make in decision-making. But it does make the book
       | useless for AI researchers: I believe AGI is well over 200 years
       | away, because going all the way back to Alan Turing AI has simply
       | refused to engage with the challenges of cognitive science,
       | preferring fairy tales which confirm intuitions and trivialize
       | human minds.
       | 
       | [1] https://www.cell.com/trends/cognitive-
       | sciences/abstract/S136... and
       | https://www.psychologytoday.com/intl/blog/a-hovercraft-full-...
        
         | lukev wrote:
         | So, in one sense I agree with you. There is zero evidence that
         | the human brain runs separate systems for separate types of
         | cognition.
         | 
         | On the other hand, the reason this idea is sticky is because it
         | matches our conscious experience. In some situations, we
         | respond intuitively. In other situations, we choose to work
         | analytically using tools like research, deliberation, note-
         | taking, etc.
         | 
         | I think it's this second sense in which people are using the
         | term with respect to LLMs. And it's not a terrible analogy.
         | 
         | However, comparing "neural networks" to actual neurons is
         | almost never useful.
        
           | lukev wrote:
           | Oh, and to be pedantic:
           | 
           | > he observation that a O(n^2) problem can be broken down
           | into n separate O(n) problems is ultimately due to system 1
           | reasoning: it is obviously true.
           | 
           | As the parent of a third grader just learning this stuff, I
           | can assure you it isn't immediately obvious to everyone.
        
         | thorum wrote:
         | > We don't have a clue how to make a computer capable of System
         | 1 thinking.
         | 
         | I think you're overthinking this. System 1 thinking _as the
         | term is being used by AI researchers_ means making a fast
         | decision based on reasoning processes that are wired into your
         | brain by evolution. For any task that humans have faced for
         | millions of years this works well. It can also work well for
         | experts in a domain who have practiced a task so many times
         | that their brains have adapted to perform it unconsciously.
         | 
         | System 2 thinking is consciously using explicit reasoning
         | techniques to think through a problem, slowly and rigorously,
         | often in ways that feel unnatural due to our cognitive biases
         | but can solve problems that System 1 is unable to.
         | 
         | The analogy to LLMs is straightforward: LLMs learn to solve
         | many kinds of complex problems during training and encode
         | processes for those specific problems. They can then perform
         | these tasks in a single forward pass through their weights.
         | This is System 1 for LLMs and again, works well for any task
         | that they were exposed to repeatedly during training.
         | 
         | However they don't generalize to tasks that were not well
         | represented in the training data. Training them to use explicit
         | reasoning strategies instead (System 2) is shown to improve
         | performance and let them solve a broader range of problems.
        
           | grupthink wrote:
           | System 1 and 2 is a myth. There is only memory and
           | computation. For a complex problem, retrieving from memory is
           | fast, and performing computation is slow. Furthermore, when
           | performing computation, there are different heuristics that
           | you can use to think about a problem, e.g. If you want to
           | predict the orbit of a satellite, you can use Kepler's laws
           | which gives you the full sweeping elliptical motion.
           | Alternatively, you can use Newtons laws for which you need to
           | calculate each time step. Alternatively, you can calculate
           | all the quantum interactions between the satellite, earth,
           | and sun (are we going to call this System 3 because it is
           | more rigorous and is "closer to metal"?).
        
             | andrewchambers wrote:
             | Ok, if we can define system 1 as retrieval and system 2 as
             | computation and then we all agree.
        
             | mewpmewp2 wrote:
             | I don't get how you can conclude it is a myth. These are
             | observations on how people think. What is the myth part. I
             | can clearly observe myself doing fast intuitive decisions
             | which I might even not know the logical reasoning behind,
             | but also I can solve problems by thinking through them
             | using my internal monologue. Are these myths?
        
               | nighthawk454 wrote:
               | The error lies in thinking they're 'real' systems to be
               | taken for granted and blindly reasoned forward from,
               | instead of sometimes-helpful academic categorizations.
               | 
               | You can always factor things into groups. e.g. 'Thoughts
               | about now vs thoughts about the future'. Extending that
               | to say there are therefore two modes of thinking and that
               | the brain must handle your two groups differently, at
               | some fundamental or physiological level, and there are
               | only these two modes and all things are either one or the
               | other ... is perhaps quite misguided without more
               | support.
               | 
               | "It's only a model"
        
         | jonstewart wrote:
         | Thank you, I was hoping someone in the comments would point out
         | that all this junk hasn't been replicable.
        
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