Prolog: 1, 2, 3, 4, 5 ...
You and me instantly: 10^8000
Prolog can also evaluate mathematical expressions directly as well.
I recommend this book: https://www.amazon.com/Secrets-Mental-Math-Mathemagicians-Ca...
THAT’S THE POINT!
Yes, many people can successfully calculate it through learned tricks or no learned tricks.
That is all I am saying. And my question is: how is calculating it in your own head brute-force, especially if done without such tricks?
No need to complicate it, answers to my question would suffice.
Doing this calculation in your head is not brute force, which was their entire point. Their math question was an example of why the brain isn't brute-forcing solutions, replying to this:
> What makes you think your brain isn't also brute forcing potential solutions subconciously and only surfacing the useful results?
In any case, I am not sure why he kept on telling me that you do not solve it through brute-force because that is not what I said.
7 * 101 = 707 * 10 = 7,070
And computers don't brute-force multiplication either, so I'm not sure how this is relevant to the comment above?
Just note: human pattern matching is not Haskell/Erlang/ML pattern matching. It doesn't go [1] through all possible matches of every possible combination of all available criteria
[1] If it does, it's the most powerful computing device imaginable.
Well, my brain perhaps. Not sure about the rest of y'all.
There are hundreds of trillions of synapses in the brain, and much of what they do (IANANS) could reasonably be described as pattern matching: mostly sitting idle waiting for patterns. (Since dendritic trees perform a lot of computation (for example, combining inputs at each branch), if you want to count the number of pattern matchers in the branch you can't just count neurons. A neuron can recognise more than one pattern.)
So yes, thanks to its insanely parallel architecture, the brain is also an insanely brute force pattern matcher, constantly matching against who knows how many trillions of previously seen patterns. (BTW IMHO this is why LLMs work so well)
(I do recognise the gap in my argument: are all those neurons actually receiving inputs to match against, or are they 'gated'? But we're really just arguing about semantics of applying "brute force", a CS term, to a neural architecture, where it has no definition.)