The generic city one makes no sense. Does the author want each city to invent a new physics? Not only are there quite a few different looking buildings in each of the cities, but given the constraints of not have unlimited funds, surely one can understand that many columns of steel, concrete, and glass will look like columns of steel, concrete, and glass from afar.
Those are urban areas with a dense grouping of relatively small and lower priced construction. The Alex Murrell link has pictures of dense groupings of enormous buildings with very high priced construction.
That's funny - to me, Jodhpur is most immediately appealing of the three. It reminds me of the medinas I visited in Fez and Marrakesh: overwhelming at first, as a visitor, but compelling, and full of life. I'd rather live in a thriving urban place like that, all human-scale and pedestrian, than some sprawling, soulless, car-dependent suburb like the ones a majority of North Americans inhabit.
If you have a simulation where realtime is 60 fps, you could simulate a little over 4.5 hours per second if you could run it at 1M fps. That would definitely help with learning rate.
He's not saying "break realtime into microsecond chunks."
He's saying: run through 4.5 hours of 16 millisecond chunks of time in a second. This is good for regression testing or producing training data quickly.
python3 -c 'import random, time, itertools; any(time.sleep(0.01) or print(random.choice("\u2571\u2572"), end="", flush=True) for x in itertools.repeat(None))'
The broader contexts could be this: look at this puzzle as a way for reinvent sorting as a delegation of operations (split + combine) instead of traditional "swapping" of values. As CPU arithmetic is faster then memory operations some real treasure may be hidden in this new approach.
That is clearly nonsense, as the results of performing the arithmetic still need to be written back to memory, so it's just a swap with extra operations. See also the xor-swap.
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