gamechanger
Dall-E 2
311–320 of 511 posts
Re: Dall-E 2
#312Related and kind of fun:
Sam Altman demonstrates Dall-E 2 using twitter suggestions - https://news.ycombinator.com/item?id=30933478 - April 2022 (3 comments)
Re: Dall-E 2
#313The timing of the Dall-E 2 launch an hour ago seems to correspond with a recent piece of investigative journalism by Buzzfeed News about one of Sam Altman's other ventures, published 15 hours ago and discussed elsewhere actively on HN right now: https://news.ycombinator.com/item?id=30931614 I point this out because while Dall-E 2 seems interesting (I'm out of my depth, so delegating to the conversation taking place h…
I don't have any knowledge (inside or otherwise) but the Worldcoin thing already came in for several rounds of abuse on HN, so it's kind of a scandal of the second freshness at this point.
I listed some of them here - https://news.ycombinator.com/item?id=30934732, just because I remembered there had been previous discussions and listing related previous discussions is a thing.
Re: Dall-E 2
#314Earlier quoted context omitted.
How do you run such a Google Colab thing? I don't see a run button? On.. maybe "Runtime -> Run All" from the menu ... Shows me a spinning circle around "Download model" ... 26% ... Fascinating, that Google offers you a computer in the cloud for free .. Now it is running the model. Wow, I'm curious .. Ha, it worked! Nothing compared to the images in the Dall-E 2 article but still impressive.
Google is a company with a lot of spare VMs and GPUs. However, the free GPU is now a K80 which is obsolete and barely sufficient for running these types of models.
You sometimes still get T4s. I got one last week and it was great.
Re: Dall-E 2
#315One of my teachers once said “An art piece is never done”. So, I wonder what could that mean for the model to keep making improvements to the piece.
Re: Dall-E 2
#316I'm only part way through the paper, but what struck me as interesting so far is this: In other text-to-image algorithms I'm familiar with (the ones you'll typically see passed around as colab notebooks that people post outputs from on Twitter), the basic idea is to encode the text, and then try to make an image that maximally matches that text encoding. But this maximization often leads to artifacts - if you ask for…
While the whole narrative of your comment totally makes sense, I don't really see the difference between the two approaches, not on a conceptual level. You still needed to train this so called "prior" at some point (so, I'm also not sure if it's fair to call it a "prior"). I mean, the difference between your two descriptions seems to be the difference between descriptions (i.e., how you chose to name individual parts of the system), not the systems.
I'm not sure if I'm speaking clearly, I just don't understand, what's the difference between training "text encoding to an image" vs "text embedding to image embedding". In both cases you have some kind of "sunset" (even though it's obviously just a dot in a multi-dimension space, not the letters) on the left, and you try to maximize it when training the model to get either a image-embedding or a image straight away.
Re: Dall-E 2
#317I'm only part way through the paper, but what struck me as interesting so far is this: In other text-to-image algorithms I'm familiar with (the ones you'll typically see passed around as colab notebooks that people post outputs from on Twitter), the basic idea is to encode the text, and then try to make an image that maximally matches that text encoding. But this maximization often leads to artifacts - if you ask for…
Do you think some of these techniques could be slightly modified, and applied to DNA sequences?
probabilistic generative models have been applied to DNA and protein sequences for decades (my undergrad thesis from ~30 years ago did this and it wasn't even new at that point). The real question is what question you want to answer and what is this system going to do better enough to justify the time investment to prove it out?
Re: Dall-E 2
#318Earlier quoted context omitted.
Literally everyone on this website is in denial. They all approach it by asking which fields will be safe. No field is safe. “But it’s not going to happen for a long time.” Climate deniers say the same thing and you think they should be wearing the dunce hat? The average person complains bitterly about climate deniers who say that it’s “my grandkids problem lol” but when I corner the average person into admitting AI…
I'm trying to understand your point, because I think I agree with you, but it's covered in so much hyperbole and invective I'm having a hard time getting there. Can you scale it back a little and explain to me what you mean? Something like: AI is going to replace jobs at such scale that our current job-based economic system will collapse?
Most people get stuck where you are. The fastest way possible to explain it is that it will bring rapid and fundamental change. You could say jobs or terminators but focusing on the specifics is a red herring. It will change everything and the probability of a good outcome is minuscule. It’s playing Russian roulette with the whole world except rather that 1/6 for the good, it’s one in trillions for the bad. The worst and stupidest thing we have ever done.
Re: Dall-E 2
#319It's becoming clear that efficient work in the future will hinge upon one's ability to accurately describe what one wants . Unpacking that -- a large piece is the ability to understand all the possible "pitfalls" and "misunderstandings" that could happen on the way to a shared understanding. While technical work will always have a place -- I think that much creative work will become more like the management of a team…
No... These models are trained to predict.
You can definitely make them incremental. You can give it a task like "make a more accurate description from initial description and clarification". Even GPT-3-based models available today can do these tasks.
Once this is properly productionized it would be possible to implement stuff just talking with a computer.
Re: Dall-E 2
#320Some initial video by Yannic Kilcher: https://www.youtube.com/watch?v=gGPv_SYVDC8