201–210 of 260 posts
Serious question: is there a warez scene for trained models yet? (I don't know how the model is accessed - are users of mainline GPT-3 given a .pb and a stack of NDAs, or do they have to access it through access-controlled API?) Wherever data is desired by many but held by a few, a pirate crew inevitably emerges.
I think this also might be an interest to you https://the-eye.eu/public/AI/pile_preliminary_components/
Serious question: is there a warez scene for trained models yet? (I don't know how the model is accessed - are users of mainline GPT-3 given a .pb and a stack of NDAs, or do they have to access it through access-controlled API?) Wherever data is desired by many but held by a few, a pirate crew inevitably emerges.
The model is huge and is currently run in the cloud on many machines.
Serious question: is there a warez scene for trained models yet? (I don't know how the model is accessed - are users of mainline GPT-3 given a .pb and a stack of NDAs, or do they have to access it through access-controlled API?) Wherever data is desired by many but held by a few, a pirate crew inevitably emerges.
I think this also might be an interest to you https://the-eye.eu/public/AI/pile_preliminary_components/
Earlier quoted context omitted.
> I think of the value proposition of GPT-X as "what would you do with a team of hundreds of people who can solve arbitrary problems only by googling them?". And honestly, not a lot of productive applications come to mind. Damn, this could replace so many programmers, we're doomed!
*realizing GPT-3 was probably created by programmers who's job really is mostly googling for stackoverflow answers* #singularity
GPT-∞: still distinguishable from human advice, but it contains a quadrillion parameters and nobody knows how exactly it’s able to tune them.
In my experience, the output from GPT-3, DALL-E, et al is similar to what you get from googling the prompt and stitching together snippets from the top results. These transformers are trained on "what was visible to google", which provides the limitation on their utility. I think of the value proposition of GPT-X as "what would you do with a team of hundreds of people who can solve arbitrary problems only by googling…
In my experience, the output from GPT-3, DALL-E, et al is similar to what you get from googling the prompt and stitching together snippets from the top results. These transformers are trained on "what was visible to google", which provides the limitation on their utility. I think of the value proposition of GPT-X as "what would you do with a team of hundreds of people who can solve arbitrary problems only by googling…
GPT-3 is trained on text prediction, and there's been a lot of commentary about the generation aspect, but some of the applications that excite me most are not necessarily about the generation of text, instead, GPT-3 (and also other language models) create very useful vector representations of natural language as a side effect that can then be used for other tasks with much less data, or with too much extra data. Usi…
I agree with this, and it isn't entirely speculative. One of the most useful applications I have seen that goes beyond googling is generating css using natural language. ie, "change the background to blue and put a star at the top of the page". There are heavily sample selected demos of this on twitter right now https://twitter.com/sharifshameem/status/1282676454690451457...
This is definitely practical, though I wouldn't design my corporate website using this. could be useful if you need to make 10 new sites a day for something with seo or domains
Earlier quoted context omitted.
That fact that you made up that number is extremely funny in this context.
I don't think so - I was aware that it was a made-up number, and highlighted the fact that it was. It's the lack of awareness of what is backed up by data that is the problem I think. Or am I missing your point?
In my experience, the output from GPT-3, DALL-E, et al is similar to what you get from googling the prompt and stitching together snippets from the top results. These transformers are trained on "what was visible to google", which provides the limitation on their utility. I think of the value proposition of GPT-X as "what would you do with a team of hundreds of people who can solve arbitrary problems only by googling…
I don't necessarily see the "team of automated googlers" as a fundamental or damning problem with GPT-like approaches. First I think people may have a lot fewer truly original ideas then they are willing to admit. Original thought is sought after and celebrated in arts as a rare commodity. But unlike in arts, where there are almost not constraints, when it comes to science or engineering almost every incremental step…
I love the initiative, but I'm starting to get scared of what a post-GPT-3 world will look like. We are already struggling to distinguish fake news from real ones, automated customer request replies from genuine replies, etc. How will I know that I have a conversation with a real human in the future? On the other side, the prospect of having an oracle that answers all trivia, fixes spelling and grammar, and allows hu…
I know! One day it's going to get so bad people are going to have to deploy critical thinking instead of accepting what they read at face value and suffer the indignity of having to think for themselves.