I liked the original article - since I've looked at semgrep, and I'm also hoping "closing the loop" can fix some of the downsides of LLMs
I'm also willing to bet money, and I'd even thought of a challenge for 10x or 20x that amount
But if you want to bet, then you have to have something well-defined and interesting to bet on:
- leave out the term "AGI" - this only confuses things, because everyone has a different definition of it.
Just say what the problem is, precisely
- leave out "FAANG staff engineer". Because computers are already better than staff engineers on dozens and dozens of tasks, like adding two 32 bit numbers, or compiling C++ code, or running Python code. Not to mention certain things involving LLMs.
i.e. it's extremely obvious that LLMs are better at engineers at certain things -- the ones they choose to use LLMs for. That doesn't mean LLMs can replace them, which is often what people mean by "AGI".
I'm also willing to bet money, and I'd even thought of a challenge for 10x or 20x that amount
But if you want to bet, then you have to have something well-defined and interesting to bet on:
- leave out the term "AGI" - this only confuses things, because everyone has a different definition of it.
Just say what the problem is, precisely
- leave out "FAANG staff engineer". Because computers are already better than staff engineers on dozens and dozens of tasks, like adding two 32 bit numbers, or compiling C++ code, or running Python code. Not to mention certain things involving LLMs.
i.e. it's extremely obvious that LLMs are better at engineers at certain things -- the ones they choose to use LLMs for. That doesn't mean LLMs can replace them, which is often what people mean by "AGI".