These things work well on the extremely limited task impetus that we give them. Even if we sidestep the question of whether or not LLMs are actually on the path to AGI, Imagine instead the amount of computing and electrical power required with current computing methods and hardware in order to respond to and process all the input handled by a person at every moment of the day. Somewhere in between current inputs and handling the full load of inputs the brain handles may lie “AGI” but it’s not clear there is anything like that on the near horizon, if only because of computing power constraints.

Way back, Perl got off the ground really because, in contrast to the C compilers of the era, code written on one Unix ran on the others, usually unmodified. In my first jobs, where we had heterogeneous mixes of commercial Unixes, this was unbeatable. It also wrote like higher level shell, which made it easy to learn for systems people, who really were the only ones that cared about running things on multiple platforms most of the time anyway.

As things became more homogeneous, and furthermore as other languages also could do that “one weird trick” of cross platform support, the shortcomings of both Perl and its community came to the fore.