craig at starfirelighting.com
Fri Jan 20 09:56:22 EST 2023
Startling, and beautifully presented.
I had no idea ChatGPT was that powerful and knowledgeable.
We are doomed.
> On Jan 20, 2023, at 8:05 AM, Alex Tweedly via use-livecode <use-livecode at lists.runrev.com> wrote:
> Fascinating. Thank you so much for that Geoff.
> I've been afraid to play with ChatGPT so far - too worried abut getting sucked in and spending way too much time ....
> I did take a look at your third example (since I can never resist a performance challenge :-)
> There are a number of minor tweaks that could be made to improve performance
> 1. set initial value to infinity rather than calculating a distance between the first two points.
> 2. "number of elements in pPoints" is unvarying within any one call - so extract it to a variable at the start
> 3. use the square of the distance rather than the actual distance - save N**2 calls to sqrt
> 4. use "DX * DX" rather than "DX ^ 2" (about 25% faster)
> 5. calculate distance in-line rather than call a function
> but those all add up to maybe 10% performance improvement (or less - I didn't test it). That's useful - but not enough.
> For a modest number of points (2000 random points), this takes approx 16.5 seconds !!
> We need a better algorithm. If we use a "linear scan", we can change it from essentially Order(N**2) to approx Order(N).
> - sort the points by X coordinate
> - while scanning the inner loop, as soon as the difference in Xcoord from the 'outer' point exceeds the minDist so far, you can reject not just this point, but all subsequent points, and hence exit the inner loop immediately.
> This brings the time down from 16500 millisecs to 25 millisecs.
> BUT - I have no clue how I'd go about describing this to ChatGPT :-)
> NB I changed the input parameter to be the list of points rather than the array.
> function closestPointsSQ pLines
> sort pLines by item 1 of each
> put pLines into pPoints
> split pPoints by CR
> put infinity into minDist
> put the number of elements in pPoints into N
> repeat with i = 1 to N-1
> repeat with j = i + 1 to N
> put item 1 of pPoints[j] - item 1 of pPoints[i] into t1
> if t1 * t1 > minDist then exit repeat
> put item 2 of pPoints[j] - item 2 of pPoints[i] into t2
> put t1 * t1 + t2 * t2 into dist
> if dist < minDist then
> put dist into minDist
> put pPoints[i] & " " & pPoints[j] into closestPoints
> else if dist = minDist then
> put return & pPoints[i] & " " & pPoints[j] after closestPoints
> end if
> end repeat
> end repeat
> return closestPoints
> end closestPointsSQ
> -- Alex.
> On 20/01/2023 06:02, Geoff Canyon via use-livecode wrote:
>> I tested three use cases, with variations, using ChatGPT for (live)code
>> generation. There was a lot of back and forth. In the end, I solved all the
>> problems I set, but in some cases I had to hold ChatGPT's hand pretty
>> That said, I learned some things as well -- about LiveCode. ChatGPT's code
>> for Fizz Buzz was faster than mine.
>> My code was faster for reversing lines. But ChatGPT, when asked to "make
>> the code faster" gave several suggestions, some of which were wrong or
>> impossible, but one of them was my method, and when I said "write that
>> option" it did, with only a few corrections needed.
>> And one of the ideas, while wrong, caused me to think of a different way to
>> solve the problem, and that way ended up being faster than my original
>> solution by over 3x on reversing 10k lines. Getting ChatGPT to write this
>> new method was *hard*.
>> In any case, I wrote it all down in a google doc
>> If you're curious, have a read. That URL is open for comments/edit
>> suggestions. If you have any I'd love to hear them.
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