656 karma · joined June 23, 2014
The discussion is not about humans using LLLs to write papers. It is about humans who agreed not to use LLVM in reviewing papers, then did exactly that.
But at scale. Yegge gets close to it in this blog (which actually made me lol, good to see that he is back on form), but shies away from it.
If AI is producing a real productivity boom then we should be seeing a flood of high-quality non-AI related software. If building and shipping software is now easier and faster then all of the software that we have that doesn't quite work right should be displaced by high quality successors. It should be happening right now.
So where is it? Why is all this velocity going into tooling around AI instead? Face it, an entire industry has fallen into the trap of building the automation instead of the product they were trying to automate the production of.
Where is the new high quality C compiler that actually compiles the linux kernel to a measurably higher quality than gcc? If AI is really increasing productivity shouldn't we have that instead of a press-oriented hype flop?
> The operating system for the next generation of gamers
(apart from the ones in the firmware, and the hardware glitches...)
I am shocked!
In the Monty Hall problem there is added information in the second round from the informed choice (removing the empty box).
In this problem we don't have the same two-stage process with new information. If the previous process was fair then we know the remaining candidate was better than the eliminated male (and female) candidates. We also know the remaining female candidate was better than the eliminated male (and female) candidates.
So the size of the initial pools does not tell us anything about the relative result of evaluating these two candidates. Most people would choose the candidate from the smaller pool though, using an analogue of the Gambler's Fallacy.