It's been doing all of the actual coding part of my job for the better part of a year, and you're commenting on a post about how it just released another round of math breakthroughs, besting a bunch of top humans. It can search the web and analyze documents it finds for me. It can do reverse engineering. It can analyze and create images.
Not sure what your definition of AGI is, but it clearly has superhuman performance on most knowledge work already. Do you think after already having demonstrated that it can solve top problems, that the final frontier it won't be able to cross is explaining its solutions to the experts that were researching those problems, and eventually to e.g. grad student or postdoc level practitioners as a lecture course/set of notes?
Isn't it curious that while LLMs are apparently on the precipice of "AGI" and possessing superhuman capabilities for knowledge work, the frontier labs are still hiring armies of humans as "Account Associates", "Account Directors", "AI Support Engineers", and "Applied AI Engineers" (https://openai.com/careers/search/). Since those roles are much more pedestrian than top math problems, one might expect the frontier labs to be at the forefront of automating those jobs using their world-beating models. Wouldn't that be a more direct flex of their economic value?
Not sure I follow: if it weren't incredibly useful, my salary wouldn't depend on it since it wouldn't be doing my work for me, innit? So if I am dependent on it, that's just agreeing that it's now replaced programming per se as a professional activity. That quote applies to the people selling the tool (not me), not the people who it will replace (me), and in the meantime who are buying/using it.
I think the point is that people (software engineers included), will be biased to believe AI won’t replace them because believing otherwise would cost them their job (and therefore salary).
I’m not taking a side on that debate, just clarifying the relevancy of that quote.
Ah, the "six months till AGI" meme, but unironically :)
Also, before citing Terence Tao on LLMs maybe you should read what he has to say about it...