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Joined 3 months ago
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Cake day: February 18th, 2026

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  • Yes, this would work — but it comes with a subtle statistical bias: the character ‘W’ ends up underrepresented. With a naïve “avoid COW” approach, only about 25% of the grid will typically be ‘W’.

    A more elegant solution would be:

    • fill the grid completely at random
      • search for every “COW” cluster
        • whenever one is found, copy a random character from one cell in the cluster into another cell of the same cluster
      • Iterate until no “COW” remains

    That keeps the distribution much closer to uniform while still guaranteeing a valid puzzle. Then just insert the single “COW” manually wherever you want the hidden solution to be.

    Julia code example
    s= (320,180)            #size
    m=rand(['C','O','W'],s) #random init
    c=1
    while c>0      #iterate till solved
        c=0
        for i in 1:first(s)
            for j in 1:last(s)
    
                #check for 'COW' in each cluster of 3 and copy a character
                #from a rendom cell to an other random cell of the cluster if found
                
                if i>2 &&  m[i-2:i,j] ==['C','O','W']   #vertical
                    c +=1
                    r =shuffle([1,2])
                    m[i-r[1],j] = m[i-r[2],j]
                end
                if j>2 && m[i,j-2:j]  ==['C','O','W']   #horizontal
                    c +=1
                    r =shuffle([0,1,2])
                    m[i,j-r[1]] = m[i,j-r[2]]
                end
            end
        end
    end
    

    The neat part is that this preserves an almost perfectly balanced character frequency.

    For comparison, the puzzle in the example image seems to contain roughly:

    C: ~260 (~25%) O: ~520 (~50%) W: ~244 (~25%)

    So the original author clearly used a different generation strategy.

    Possibly on purpose: visually, ‘C’ and ‘O’ are much easier to confuse than ‘W’. Reducing the number of 'W’s therefore increases the search difficulty. In that sense, the approach suggested by @Snazz@lemmy.world is probably preferable: keep the distribution mostly balanced, but intentionally bias it just enough to make the puzzle psychologically annoying.

    I wonder if there is a non iterative way to generate this puzzle with a ‘uniform’ character distribution 🤔










  • That’s also what I currently experience in my position. A lot of workflows are going to be automated by some AI stuff, but whenever someone is planning to produce physical goods in masses you can not effort doing stupid misstakes. When you simply put the output of the LLM in to the input of your CNC, Ion-Implanter, Litograph-Machine, Welding Robot, Aribag or Breaking systems. A mistake is going to be sooo fucking expensive that the human in the loop is not an cost factor anymore. And when you do high precision stuff an approximate solution is never sufficient.




  • I definitively also observe the recent increase of spam (mostly on info@domain) however spamassassin (after some training) does a decent job sorting the trash out. Also I use a unique email address for each website I register, this way a lot of spam was removed by blocking an email-address I’ve used for login to facebook 10 years ago.