[joe_the_user]

I think there's a divide between "impressive" and "good".

I think deep learning will keep creating more impressive, more "unintuitive and unexpected", more "wow" results. The "wow" will get bigger and bigger. Gpt-3 is more impressive, more "wow"-y than Gpt-2. Gpt-3 very impressively seems to demonstrate understanding of various ideas, Gpt-3 indeed very impressively develops ideas over several sentences. No argument with the "unintuitive and unexpected" part.

The problem is the whole thing doesn't seem definitively good (in Gtp-3's case, doesn't produce good or even OK writing). It's not robust, reliable, trustworthy. The standard example is the self-driving car. They still haven't got those reliable but with more processing power, a company could probably add more bells and whistles to the self-driving process but still without making it safe. And GPT-3 seems in that vein - more "makes sense if you're not paying attention", the same "doesn't really say coherent things".

I'm trying to trace a middle ground between the two reactions. I'm perhaps laughing a little at those just looking at impressive but I acknowledge there's something real there. Indeed, the more you notice something real there, the more you notice something real missing there too.

[Polylactic_acid]

Thats similar to my thoughts. That demo video of generating html was very impressive, I have never seen anything that can do that, but its also 1000x less useful than squarespace or wordpress. The tool in its current state is totally useless even if it is very impressive.

[p1esk]

It's not robust, reliable, trustworthy

Is human writing robust, reliable, trustworthy? Would you agree that some humans produce vastly better writing than others? Have you never read comments here on HN that appeared to be incoherent rambling, logically faulty, or just shallow, trite and cliched?

GPT-1 is a significant improvement over earlier RNN based language models. GPT-2 is a significant improvement over GPT-1. GPT-3 is a significant improvement over GPT-2, especially in terms of "robustness". All these achievements appeared in the course of just 3 years, and we haven't yet reached the ceiling of what these large transformer based models can do. We can reasonably expect that GPT-4 will be a significant improvement over GPT-3 because it will be trained on more and better quality data, it will be bigger, and it might be using better word encoding methods. Aside from that, we haven't even tried finetuning GPT-3, I'd expect it would result in a significant improvement over the generic GPT-3. Not to mention various potential architectural and conceptual improvements, such as an ability to query external knowledge bases (e.g. Wikipedia, or just performing a google search), or an ability to constrain its output based on an elaborate profile (e.g. assuming a specific personality). There are most likely people at OpenAI who are working on GPT-4 right now, and I'm sure Google, Microsoft, Facebook, etc are experimenting with something equally ambitious.

I agree that GPT writing is not "good" if we compare it to high quality human writing. However, it is qualitatively getting better and better with each iteration. At some point, as soon as a couple years from now, it will become consistent and coherent enough to be interesting and/or useful to regular people. Just like self-driving cars in a couple of years might reach the point where the risk of dying is higher when you drive than when AI drives you.