jinlisp's comments

If Putnam was really a genius I think he would have been able to communicate precisely some of this insight to mere mortals. It seems that he taught the same course during 10 years and that seems time enough to mature a good introduction to his ideas. Being ineffable don't entitle you to being a genius.

What seems clear is that he was in the right moment and with the right people to produce a great theory of the mind, he was thinking about defining the mind as a creator of heuristic for generating inductive rules, that is a very interesting idea, also that seems related to cellular automata and homeostasis, fixed point theory, error recovery and many other ideas that we, with our ability to look back in time, can see are located in their neighborhood. Recently we are using LLMs to produce heuristic or rules to generate python programs to explore proofs or new models, so the gems is still alive.

The field he was interested in it is full of little diamonds waiting for someone to find them, but perhaps he just put his foot in the door without entering (or creating) the field he was trying to envision. It could be that his paper could reveal some intuition that could guide us in a new search for meaning but from this post there is no any hint about that beyond such a desire.

Thanks for such a clear and logical explanation, it is a pleasure to read explanations like this. Anyway, I am always skeptical about how law is applied, sometimes the spirit of the law is bended by the weight of the powerful organizations, perhaps there are some books which explains how the spirit of the law is not applied when powerful organizations are able to tame it.

Thank you, this is a nice point to consider. Don't know if using the weights could be considered equivalent or implying accepting the terms of services from weights creators.

Both slip and jscl takes the same time in my computer: 63 seconds to run the loop.

This is another comment of the author about maxima in the browser from four months ago: I'm experimenting with WASI and the GC extension for WASM, but that's months from today if we speak about complete port (given my time capacity at the moment). Don't know if the gc extension is used in this example.

It depends of what you need, but for example for calculus is a nice program. There is also sympy and Wolfram Mathematica. For symbolic computation I think that Mathematica is the strongest then maxima and then sympy, but sympy is based on python and I think it will get stronger. If you need numerical computation then there is octave or matlab or julia.

I was going to ask if maxima (a symbolic computation system) can be implemented in the browser, but it was answered four months ago [1]

[1] https://news.ycombinator.com/item?id=42853528

Should it be possible to implement an optimization compiler? so that compiling the code in the web page produces results similar to ECL or sbcl?

When executing (time (loop for i below (expt 10 8) count t)) it takes a long time, sbcl takes less than a second on this. So not useful when speed is required. More: (time (loop for i below 1000000 count t) takes 7 seconds on my computer, so counting to (exp 10 8) would take 700 seconds, and sbcl do that in 0.1 seconds, so in this example the ratio is 7000 times slower than sbcl.

Solving Queens using J and brute force all permutations.

   randomboard =: 3 : '? (y,y) $ y'
   testsolution =: 4 : 0          NB. solution is a list of columns.
   m =. x
   n =. #x
   solution =. y A. i. n
   regions =.  ({&m) <"1 (i. n) ,. solution
   distinctregions =. n -: # ~. regions
   adjacentregions =. 1 e. |2-/\solution
   distinctregions *  -. adjacentregions
   )
   findsolution =:3 : 0
   board =: y
   ns =. 1 i.~ (board & testsolution)"0 i. !#y
   if. (ns = !#y) do. 'No solution found' 
   else.
 echo 'Solution index is ', ": ns
 ns A. i. #y end.
   )
   
   regions =: 4 : 0
   ({&x) <"1 (i. #x) ,. y
   )
   number2solution =: 4 : 0
   y A. i. #x
   )

   writesolution =: 4 : 0
   board =. x
   sol =.y
   m1 =. m
   n1 =. #x
   count =. 0
   for_a. sol do.
     m1 =. n1 (< count , a) } m1
     count =. count + 1
   end.
   m1
   )
   
   writewithsolution=: 4 : 0
   m1 =: x writesolution y
   (":"1 x) ,. '|' ,. ":"1 m1
   )
   
   m =: randomboard 9
   echo m writewithsolution findsolution m

Solving Queens in J from a novice J programmer:

   randomboard =: 3 : '? (y,y) $ y'
   testsolution =: 4 : 0
   m =. x
   n =. #x
   n -: # ~. ({&m) <"1 (i. n) ,. y A. (i. n)
   )
   findsolution =:3 : 0
   board =: y
   ns =. 1 i.~ (board & testsolution)"0 i. !#y
   if. (ns = !#y) do. 'No solution found' else. ns A. i. #y end.
   )
     
   writesolution =: 4 : 0
   board =. x
   sol =.y
   m1 =. m
   n1 =. #x
   count =. 0
   for_a. sol do.
     m1 =. n1 (< count , a) } m1
     count =. count + 1
   end.
   m1
   )
   
   writewithsolution=: 4 : 0
   m1 =: x writesolution y
   (":"1 x) ,. '|' ,. ":"1 m1
   )
   
   m =: randomboard 9
   echo m writewithsolution findsolution m

      load 'queens.ijs'
   5 2 8 0 3 3 0 5 2|9 2 8 0 3 3 0 5 2
   8 2 3 6 7 7 4 5 1|8 9 3 6 7 7 4 5 1
   6 1 5 8 3 5 8 7 6|6 1 5 9 3 5 8 7 6
   8 4 8 8 7 5 1 1 1|8 4 8 8 9 5 1 1 1
   2 6 7 6 5 4 7 3 1|2 6 7 6 5 4 7 9 1
   6 8 1 4 1 4 3 2 7|6 8 1 4 1 9 3 2 7
   6 0 5 6 5 5 8 5 0|6 0 5 6 5 5 8 5 9
   1 7 5 5 8 1 1 0 1|1 7 5 5 8 1 9 0 1
   8 4 6 2 2 4 6 4 1|8 4 9 2 2 4 6 4 1

Solution in J (a few lines of code from a novice J programmer).

   board =: 3 : '? (y,y) $ y'
   test =: 4 : 0
   m =. x
   n =. #x
   n -: # ~. ({&m) <"1 (i. n) ,. 0 A. (i. n)
   )
   findsol =:3 : 0
   ns =. 1 i.~ (y & test)"0 i. !#y
   if. (ns = !#y) do. 'No solution found'
   else.
   ns A. i. #y
   end.
   )
  
   m =: board 5
   m
   4 4 0 1 1
   3 2 0 1 1
   2 4 1 1 0
   3 2 1 3 4
   2 0 2 2 0
   0 1 2 3 4
   findsol m
   0 1 2 3 4

  echo 'So the solution found is putting the queens   in the diagonal'

I am thinking about developing in Common Lisp a version of J. And this could be a useful library to use with that program.