Probably the latter question is an obvious bias based on my own media consumption, but even when trying my best internet-search efforts, I have a hard time finding anything interesting about GPT-4 (a name people seem to use for a new generation of LLMs following GPT-3). Obviously this is simply a result from openAI not releasing any new information making news useless.
Most of openAIs public affairs with regards to the LLMs they build seems to be focused on GPT-3 series models, in particular fine-tuned ones. That is not directly surprising, as these fine-tuned models are a great source of income for openAI. However, given their past release rate of GPT series (GPT in 2018, GPT-2 in 2019, and GPT-3 in 2020), they seem to take quite some time with their next series (it is almost 2023?). This raises two intuitive thoughts (both of which are probably by far to simple to be even close to reality): Either openAI is somewhat stuck and has a hard time keeping up with its past pace in making “game-changing” progress with their LLM work or openAI has made very extreme progress in the last years and decided to not publicise it for strategic reasons (e.g. to prevent from increasing the “race to AGI”)
Any thoughts or pointers on that?
“Become silent about it”
If you mean online media or the general vibe, one explanation is that DALL-E and diffusion models have been huge, taken up a lot of attention and OpenAI might have focused on that.
Like, very sophisticated tech leaders have gotten interested in these models, even when IMO language models have overwhelmingly larger business relevance for their products.
Actually, Copilot/codex have taken off and might be big. IMO this is underrated.
This might involve collab (with MS), and collabs are slower and harder/less gains to coordinate a buzzy media event on.
As a digression (or maybe not a digression) GPT-3 hasn’t had the sort of massive tractability you (and others) might have expected, even after 2 years, and this reduces the incentives for further, investment on a 10x model.
Related to this, several other companies have spawned their own language models of similar/larger size. So this might somewhat reduce the attraction to winning on size or even reduce the returns to climbing the hill of dominating LLM in some broader sense.
The instruct models and other sophistication is less legible and provide a larger barrier to entry (and produce other sorts of value), whereas parameter size / compute spend is not a moat.
GPT-3 has been somewhat uneconomic to run, for the larger models. Making a 10x model would make this even worse.
There is uh, deeper stuff. Umm, maybe more on this later.
Like any other buzz cycle, the first iteration is going to get a lot of buzz and appear in a lot of outlets. Articles mentioning GPT-3 haven’t even stopped coming out.
It’s good and valid you write this, but this is very likely different from the truth. For one thing, in multiple senses/channels, OpenAI isn’t totally locked down, and extreme sorts of developments would come out. Secondly, I think we’ve been truthfully told what they are working on (in the other comments), e.g. training refinements/sophistication approach to LLM.
Also, as a meta comment, in my opinion, it seems possible the beliefs that formed this valid question, may come from an information environment that seems not identical to an ideal information environment that would optimally guide future decisions related to AI or AI safety.
Thanks for the elaborate answer. I’d be curious to hear a bit more of your thoughts regarding the meta-comment in your last paragraph + hints what to change about the information environment you suspect here, if you have time
note: feel free to be as unrigorous as you want with the response, you don’t need to justify beliefs, just flesh them out a bit, I don’t intend to contest them but want to use them to improve my understanding of that situation
Ok, writing quickly. Starting on the “object level about the beliefs”:
It seems like sentiment or buzz, like the tweets about GPT-4 mentioned in the other comment can be found. That gives a different view than silence mentioned in your post. It seems it could be found by searching twitter or other social media.
It seems like the content in my comment (e.g. I’ve suggested that there are various projects that OpenAI has under way and these compete for attention/PR effort) is sort of publicly apparent, low hanging speculation.
Let’s say that OpenAI was actually unusually silent on GPT models and let’s also accept many views of AI safety in EA. It’s unclear why P(very extreme progress, more than 1 year with no OpenAI GPT release) would be large given some sort of extreme progress.
In the most terrible scenarios, we would be experiencing some sort of hostile situation already.
In other scenarios, OpenAI would aptly “simulate” a normally functioning OpenAI, e.g. releasing an incremental new model.
In my view P(very extreme progress | more than 1 year with no new GPT release) is low because many other underlying states of the world would produce silence that is unrelated to some extreme breakthrough, e.g. pivot, management change, general dysfunction, etc.
It seems like it’s a pretty specific conjunction of beliefs where there is some sort of extreme development and:
OpenAI is sort of sitting around, looking at their baby AI, but not producing any projects or other work.
They are stunned into silence and this disrupts their PR
This delay is lasting years
No one has leaked anything about it
I tried to stay sort of “object level” above, because the above sort of lays out the base level reasoning which you can find flaws in or contrast to my own.
From a meta sense, it’s not just a specific conjunction of beliefs, but it’s very hard to disprove a scenario where people are orchestrating silence about something critical—generally this seems like a situation where I want to make sure I have considered other viewpoints.
There’s been some anticipatory buzz about it on Twitter. No clue how credible this is, but the claim seems to be that we should expect it to be unveiled in early 2023. Also consider these comments from Sam Altman last year.