>Why were OpenAI the first to make a model as good as ChatGPT then?

That's a good question. OpenAI definitely is more open to allowing the public access to these models than other companies. While OpenAI isn't as open as some would like, they have been better than others. OpenAI might have pioneered some things but the problem is those aren't proprietary. They have published enough for others to replicate.

>It seems clear there is a significant talent and experience advantage in this.

If they can hold on to that talent. Not everyone there is gonna stick around. For eg. a lot of the GPT3 team went over to start Anthropic AI, which already has a competitor in beta.

>I should also mention that no company other than OpenAI has the same quantity of data on human interactions with large language models, thanks to the past 2 and a half years of the OpenAI API.

This is a good point. But is really better than the queries Microsoft has through Bing or Google through their search? Maybe, but still feels like little for 10B. Idk.

More important question is what does OpenAI bring to the table that can't be found elsewhere?

It doesn't cost 10B to train a language model of that scale. There's no network effect like with a search engine or social media. OpenAI doesn't have access to some exclusive pile of data ( Microsoft has more of that proprietary data than OpenAI ). OpenAI doesn't have access to some exclusive cluster of compute ( Microsoft does ). There isn't that much proprietary knowledge exclusive to OpenAI. Microsoft wouldn't be training a language model for the first time either. So what? Just an expensive acquihire?

There is a lot of research on reinforcement learning for code generation via language models happening right now. So depends on how that turns out since what you're asking for isn't possible without RL. The context window issue also needs to be fully solved and the solutions on the horizon currently don't cut it. But we could have a breakthrough any day. So who knows 🤷

That's definitely what he meant. We'd be lucky to have Deep Floyd released by the end of the month.

>It automates the final phase of RLHF (reinforcement learning from human feedback) by generating its own training examples from a bunch of rules, an "AI Constitution" so to speak.

I wish they'd just say this instead of all that "constitutional" , "three rules" nonsense.

Makes sense. Should be a lot more easier than RHLF through reward function. That's well known to be finicky as hell.

Hunh....I wonder what happened...

Link to original video

That's a good point

Personally, I'd like to see this tested on a Chinchilla scale model.

I think the more important point is that viewers are still from nding it interesting enough to tune in.

Fair enough.

Are you doing it directly from a single prompt or are you using a more structured approach ( like Google recently described in the dramatron paper )? Adding "In the style of" to the prompt also helps make the quality better.

I dont think that method is fullproof, but yeah, if I took it again or gave each more time, Im sure I'd get better results. I think the ones I got most wrong are

• Some of really bad smudgy stuff that was apparently done by humans.

• Some of the really good ones that were done by Midjourney. Though I do think I can spot these much easier now. They're kind of uncannily good. Like a bit too photoreal while not actually being photoreal. The paper thing also seems to work on these ones.

66/100 on paintings. Not that great considering 50/100 is a coin toss.

Also, thanks for making the improvements I was talking about when you posted last time ( probably not on this sub ).

Is this even ML? Seems simmilar to something like patch based style transfer...

Exactly. This is the most accurate read. Making it all opt-in means others are even more unlikely to give any thought to that tag.

Thanks. I understood it partially, but your explanation made everything crystal clear and things all clicked in an instant.

I wish more papers has an "intuition" section like this.

I only gave the paper a cursory look, but isn't this the same thing as prompt editing?

>Also "just use GPT3" is bit underselling the whole interface around it.

That wasn't my intention with the comment.

>Any chance to make this open-source for hosting it locally?

Doesn't this just use GPT3?

Apparently I was wrong? Though I don't think this is in production yet.

Oh...totally missed it then. Is it already out?

Google Street View doesn't use it either. That's just a 360° panorama shot. What you're seeing is a fully 3d scene where you can move around any way you want creates from just a few images. That's where the AI comes in.

(Btw, I'm not the one downvoting you)

Not really. Google doesn't use NeRF anywhere yet. It's still new technology. I was just wondering how many images it took to train the NeRF shown here. Probably a video with a bunch of frames? 🤷