Yeah, this pretty much seals it for me that Ed has basically nothing. Sure OpenAI isn’t currently profitable, but this doesn’t say to me that they can’t become so soon(ish).
I believe that AI is not a signal of all white collar jobs being replaced, it’s a signal that SWE was in its own bubble and this is the pressure to pop it.
Most software is not needed, YCombinator itself works on the philosophy of “maybe 2/300 ideas are good” and even among those their biggest hitters were social media platforms and undercutting existing services using VC money.
It was a big game that didn’t make a lot of sense in retrospect, and now with these AI super coders it just doesn’t make sense faster.
Software ate the world, and AI is the garbage disposal meant to chew up the leftovers.
Wholeheartedly agree, there are some aspects to SWE that could be considered hard, but most of the time it’s rote pattern matching or simple logic resolutions.
People were getting 6-figure salaries with 3 month boot camps before AI, any random college major could eventually become a developer with a few online courses and practicing LeetCode, the party was bound to end eventually.
Even in the case that a college degree was absolutely necessary (it wasn’t) making $150k fresh out of a bachelor’s degree was absurd for every other domain, many of which were much harder than CS.
You’re arguing to a subset of people who have made work their entire life and have retroactively justified their sacrifices with thoughts such as high compensation means what I do is socially valuable. However, at the same time they work at Meta or something making internal tools to make product developers 5% more efficient at tweaking the addiction algorithm to gain 0.2% more screen-time per user.
If we didn’t have the previous example I would interpret this as pretty solid evidence that labs were training on the Pelican “benchmark”.
I just can’t imagine a model dropping so significantly from one version to the next on such a silly task.