Live data from Hacker News

GPT-3 Creative Fiction

gwern.net

1–10 of 103 posts

Re: GPT-3 Creative Fiction

#2
Fine tuning GPT-3 is one of the biggest challenges, because it's behind an API. The weights aren't available to researchers, so we can't make it do anything it doesn't already do.

But, that's fair. It's OpenAI's weights; they can keep them locked up if they want to. What caught my attention, though, is that supposedly OpenAI is working on a way to support fine-tuning.

If you think about the logistics of that, it's a very interesting challenge. The situation is this: 240GB of weights, as a webservice. Each fine-tuning session results in another copy of 240GB. So it clearly doesn't scale -- 1TB per 4 users isn't exactly efficient.

Except, not quite. You can solve this by adding additional layers, which you then fine-tune. So the base model is 240GB or whatever, and the extra layers morph the output to do what you want. Think of it as a GPT-3 with a GPT-2 1.5B stuck on the end of it.

It's a neat idea, because theoretically you'd get two models out of it: you can "break off" the end of the fine-tuned model, and you end up with the original model. So it would be very modular.

Are there other models that you can "break apart" to get different sub-models? Sort of like adding slots that give a model different capabilities.

Re: GPT-3 Creative Fiction

#3

Fine tuning GPT-3 is one of the biggest challenges, because it's behind an API. The weights aren't available to researchers, so we can't make it do anything it doesn't already do. But, that's fair. It's OpenAI's weights; they can keep them locked up if they want to. What caught my attention, though, is that supposedly OpenAI is working on a way to support fine-tuning. If you think about the logistics of that, it's a…

You could encode the deltas cleverly and likely use much less than 240GB.

Re: GPT-3 Creative Fiction

#4

Fine tuning GPT-3 is one of the biggest challenges, because it's behind an API. The weights aren't available to researchers, so we can't make it do anything it doesn't already do. But, that's fair. It's OpenAI's weights; they can keep them locked up if they want to. What caught my attention, though, is that supposedly OpenAI is working on a way to support fine-tuning. If you think about the logistics of that, it's a…

Many ML models are like this (anything used in CV e.g. ResNet, VGG). For example, if you want to classify images as being hot dog or not hot dog (classes that do not exist in ResNet), you can take weights from a pretrained ResNet-50 and finetune the last layer based on a small training set of input images labeled hot dog and not hot dog. This lets you reuse the ResNet's feature detector layers, while plugging in specialized "is this a hot dog or not" fully connected layer.

Re: GPT-3 Creative Fiction

#6
GPT's take on the navy seal copypasta, in the style of a KGB spy:

"I have over 300 confirmed red scares."

Haha, that is genuinely one of the funniest versions of that I've ever seen, human-generated or otherwise. That level of inference is really amazing.

Re: GPT-3 Creative Fiction

#7
Great article. Well worth the read!

I enjoyed the part about sampling which is a big unsolved problem. To me, techniques like nucleus sampling and temperature sampling feels like hacks to make up for the fact that maximizing for likelihood maybe isn't the goal!? Maybe repetitive gibberish has a higher likelihood than prose written by humans? That Best of sampling decreased text quality indicates that it has. Researches have assumed that the problem would go away with ever growing models. But maybe it won't?

I don't agree that generating (symbolic) music would be less sensitive to sampling issues. On the contrary, in my opinion. In text you can often get away with grammatical errors or missing punctuation. But if the pitch or timing of one chord is wrong it's over. The audience instantly hears that it is garbage. Thus, you have to lower the temperature (or probability threshold or what have you) to make the sampling more conservative exacerbating the problem with repeated sequences.

Of course, in music you want repetitions. But not too much. The magic number (in Western music) is 4. Fewer repeats makes it feel as if the music jumps around. More repeats makes it feel as if the music is stuck or "looping."

Re: GPT-3 Creative Fiction

#8

GPT's take on the navy seal copypasta, in the style of a KGB spy: "I have over 300 confirmed red scares." Haha, that is genuinely one of the funniest versions of that I've ever seen, human-generated or otherwise. That level of inference is really amazing.

The whole section on navy seal copypasta generation is amazing.

Re: GPT-3 Creative Fiction

#9
I still find it odd that we call this "artificial intelligence" when it's advanced mimicry at best. There's no "intelligence" in the strict definition of the word, it's just elaborate pattern matching.

But I get it, it's exciting, and it's an easy way to get VC money. Perhaps one day we'll get something useful aside from the various pattern matching applications (image recognition, speech to text, etc). I'm skeptical but willing to be surprised.

Post reply on HN