> If that’s not general enough to qualify for the G in AGI
Indeed it isn't.
> I don’t know what it is.
Sorry to hear it, but some people do.
The way that many other here see it is that the fact that it has lots of spikes in many different directions and some lower bounds above the level of a 10 year old, is indeed enough generality.
Probably the G in AGI is a spectrum, and it it is now a maturing process to lift the lower bounds of the spiky profile of to the best of humanity. If this will ever work with an alien intelligence is debatable. Even in the "Culture Series" the ASI had lower bounds of some skill sets that were below the best of Humanity, and thus the "Contact" department was formed, to use these humans to cover the shortcomings the ASI could not. It might indeed be our chance for a symbiosis to make up for some of these lower spike bounds.
In the end who is to say that our intelligence is not spikey, and me are just normalizing it to a circle..
But that was not the original argument, which was: this incredible and rapid advance and everything we've seen since that was broadly considered decades away before ChatGPT; so it is unwise to make flat assertions that this will not lead to AGI because we have no idea where this is leading, not to mention what AGI even is.
The response to that was "In 1800 calculators would have been considered intelligent." ¯\_(ツ)_/¯
> Sorry to hear it, but some people do.
Funny, I've never heard a cogent definition anywhere so far, least of all in this thread! To reiterate my point:
The state of AI/ML pre-ChatGPT: research and industry churning away experimenting with all kinds of tweaks and tunings with all kinds of models to make narrow gains in very narrow fields. NLP, NLU, computer vision, speech recognition, text-to-speech, planning, symbolic reasoning, analytics, translation, sentiment detection, etc. were all areas of heavy research . "Code generation" that we see today was a pipe dream until 2015 or so. Ordinary users experienced AI/ML almost exclusively as a narrow feature embedded in specific products, such as recommendation systems or spam filters or ads.
Post-ChatGPT: Any researcher or any user anywhere can prompt a model in natural language, or audio and video. with any arbitrary task, and get largely useful results.
The very concept of a single model being able to even attempt an unlimited variety of tasks, doing surprisingly well on many of them and continuously getting better at everything, coming from the previous deeply fragmented state of the art, I think reasonably qualifies as "general."
If there's another take on what AGI means given the background of the field, I'd love to read it!
I keep saying this, until ChatGPT came out 4 years ago it was basically unimaginable that a single model could do any of, let alone all, the things they are doing today. Like, seriously, go take a look at the state of the art in NLP and NLU, the very first challenge in getting computers to even “understand” natural language, let alone other things like reasoning. Everything it does automatically was once a heavily experimental deep research field with long glorious careers for the researchers.
And now it’s all gone because the Bitter Lesson won again. If that’s not general enough to qualify for the G in AGI I don’t know what it is. And we’re sitting here going, “But it sometimes writes bad code though.”