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? 🤷

How many pictures was this?

No, style isn't copyrightable.

It learns from images and artwork ( like humans also do ). There aren't going to be any "samples", not any more than you'll find in the work of other humans ( which was my point ).