[HN Gopher] The Architecture of Learning: From Statistics to Int...
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       The Architecture of Learning: From Statistics to Intelligence
        
       Author : scapbi
       Score  : 71 points
       Date   : 2025-10-01 05:49 UTC (3 days ago)
        
 (HTM) web link (little-book-of.github.io)
 (TXT) w3m dump (little-book-of.github.io)
        
       | bulla wrote:
       | This is superbly written.
        
         | olooney wrote:
         | Then you may enjoy _Elements of Statistical Learning_ [1] or
         | Kevin Murphy's books[2][3][4], which this chapter is heavily
         | indebted to; it is mostly a short gloss of the topics covered
         | in those books.
         | 
         | [1]: https://hastie.su.domains/ElemStatLearn/
         | 
         | [2]: https://probml.github.io/pml-book/book0.html
         | 
         | [3]: https://probml.github.io/pml-book/book1.html
         | 
         | [4]: https://probml.github.io/pml-book/book2.html
        
       | pfekin_2nd wrote:
       | This is brilliant, thanks.
        
       | thorum wrote:
       | "not a X, but a Y" - 8 matches
       | 
       | "is more than a X... it is Y" - 3 matches
       | 
       | "not just X, but Y" - 4 matches
        
         | ForceBru wrote:
         | Why not just say what you want to say??? Surely these
         | statistics are supposed to suggest some "obvious" conclusion,
         | probably that the article is somehow bad. What do you mean by
         | these numbers???
        
           | SchizoMode wrote:
           | They're saying it was written by an LLM because of the style
           | of writing.
        
         | jal278 wrote:
         | Yeah -- I don't get why this is front-page -- reads like LLM
         | quasi-insight:
         | 
         | "Through activation, lifeless equations became living systems.
         | The neuron was no longer a mere calculator; it was a decider -
         | a locus of transformation where signal met significance." --
         | wtf
        
         | godelski wrote:
         | More than that, it uses a lot of words to say so little.
         | 
         | Even a quick scan shows some pretty critical errors. In 76.4
         | Two parameters govern its perception:             * ( ):
         | neighborhood radius        * ( MinPts ): minimum points per
         | dense region
         | 
         | Or later in 76.7                 In Fuzzy C-Means (FCM), each
         | point (x_i) receives membership values (u_{ik}) in (
         | 0,1       ), satisfying (k u{ik} = 1). The objective is to
         | minimize:
         | 
         | These are not human mistakes. They are categorically different
         | 
         | Also, the math really smells of AI. It has equations but it is
         | like they have no substance. It has the form, but not the
         | feeling. I know all this math and looking through I don't know
         | how anyone could learn from such text. I'm not sure how it
         | could even serve as a good reference. Where are the
         | derivations? Where are the corollaries? Where are the
         | implications? The extensions? The... depth?
         | 
         | 0/10. I think you would be worse off by reading this
        
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       (page generated 2025-10-04 23:01 UTC)