Was the original AI winter with reference to AGI? I thought it was in reference to the resulting lack of research and interest after the "bubble bust". If we're not close to AGI now I can't imagine researchers 40 years ago really thought AGI was around the corner, right? Just curious, I'm not an expert on the history of ML!

> If we're not close to AGI now

I bet we're closer than most people think. Instruct GPT-3 can do semantic tasks just as efficiently as DALL-E 2 can draw. NLP tasks that took whole teams multiple years can be simply described in a few words and they work right away.

The entry barrier to implement new tasks will get very low. The large models will be the new operating system. This means more investments and data, leading to new improvements.

I believe GPT-3 is already close to median human level on most semantic tasks that fit in a 4000 token window. I'm researching how to use it right now for a variety of tasks, it just works from plain text requirements with no training.

GPT-3 is brilliant, undeniably.

But there's a quantum leap or two from (say) mindlessly producing comments that can occasionally fool readers on HN (as it has been used to do in the past) to it consciously joining in the conversation of its own volition and curiosity, then zoning out on Netflix while half-worrying about the future for GPT-4 jr and idly planning it's next server room refit.

It can't worry about jr because it doesn't have a dick. It's deficient in E's - embodied, embedded, enacted and extended. Our curiosities and values come from the game we play, so it would need to play the same game with us to develop them.

I think there have been several really, and they tend to follow hype periods, which over-promise.

I do think the last few years have been more productive than previous periods in advancing narrow AI, and to be fair to those researchers who just get on with the work, it is not on them if the advances are over-sold by others.