That was not the incredible burn you hoped for, because it kinda suggests a lack of consideration for the practical design of a modern computer, in which memory

That was not the incredible burn you hoped for, because it kinda suggests a lack of consideration for the practical design of a modern computer, in which memory is tiered in orders of magnitude of time latency from CPU registers on down through on-die caches and so forth, each tier effectively acting as a local cache for the next level. Writes are super expensive and bust cache lines and coherency all the way down to main memory and in many applications touch persistent storage and even introduce network latencies in distributed systems. By contrast, ALUs are stupendously well optimized for the baseline computational task of adding up integers. The difference between nanoseconds and milliseconds is vast. It is consequently very often cheaper to recalculate a sum using data already in cache memory than to save it and later fetch it, or (even worse) to read a value precalculated by a neighbouring computer. Furthermore, the distinction only matters for accounting systems at high scale. For the average small business accounting, it is de minimis: your computer performs more computation when resizing a browser window than it does in recalculating an account balance from scratch.