> It's not non sequitur at all ... it points out that the argument that, because there has been a rapid and surprising advance, therefore it's AGI, is intellectually bankrupt.
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!
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!