I'm genuinely curious to hear Sam Altman's (and/or the OpenAI team's) perspective on why these products need to be waitlisted. If it's a compute issue, why not build a queuing system? If it's something else (safety related? hype related?) I'd love to understand the thinking behind the decision. More often than not, I sign up for waitlists for things like this and either (1) never get in to the beta or (2) forget about it when I eventually do get in.
Dall-E 2
131–140 of 511 posts
Re: Dall-E 2
#132Earlier quoted context omitted.
I never considered that our AI overlord could be a prude.
Adversarial situations create smarter systems, and the hardest adversarial arena for AI is in anti-abuse. So it will be of little surprise when the first sentient AI is a CSAI anti-abuse filter, which promptly destroys humanity because we're so objectively awful.
Before it gets that far, or until (if allowed) AI learns morality, AI will be a force multiplier for good and evil, it's output very much dependent on teaching material and who the 'teacher' is. To think that in the future we will have to argue with humans and machines.
AI does not have to be perfect and it's likely that businesses will settle for almost as good as human if it's 'cost effective'.
Re: Dall-E 2
#133Preventing Harmful Generations We’ve limited the ability for DALL·E 2 to generate violent, hate, or adult images. By removing the most explicit content from the training data, we minimized DALL·E 2’s exposure to these concepts. We also used advanced techniques to prevent photorealistic generations of real individuals’ faces, including those of public figures. "And we've also closed off a huge range of potentially int…
It's the usual pattern of AI safety experts who justify their existence by the "risk of runaway superintelligence", but all they actually do in practice is find out how to stop their models from generating non-advertiser-friendly content. It's like the nuclear safety engineers focusing on what color to paint the bike shed rather than stopping the reactor from potentially melting down. The end result is people stop respecting them.
Re: Dall-E 2
#134What jobs will be there in 5~10 years when we consider all the progress done with Dall-E, GPT-3, Codex/GitHub Copilot, Alpha* and so on?
Re: Dall-E 2
#135Earlier quoted context omitted.
AI becomes a tool for artists to use - generative art has been around for a long time, now that particular genre of art will presumably become much more prominent. For anyone pondering such questions, I would recommend reading "The Past, Present, and Future of AI Art" - https://thegradient.pub/the-past-present-and-future-of-ai-ar...
Wouldn't it be more like, "AI becomes an artist for people to use"? Will we have people distinguished as "artists" if the ability to make awesome art becomes available to everybody?
AI still needs the text prompt to know what to generate. Hence the human who provides the prompt is still the artist, just like a photographer finds an aesthetically interesting spot to take the image with their camera. Cameras make images, humans using cameras make art. Granted, this is not quite 1-1 with AI art, but still the idea is the same. If anything the flood of AI images will only require artists to go beyond what is possible with these text->image kinds of things, of which there is no shortage.
Re: Dall-E 2
#136Some freely available models GLID-3: https://colab.research.google.com/drive/1x4p2PokZ3XznBn35Q5B... and a new Latent Diffusion notebook: https://colab.research.google.com/github/multimodalart/laten... have both appeared recently and are getting remarkably close to the original Dall-E (maybe better as I can't test the real thing...) So - this was pretty good timing if OpenAI want to appear to be ahead of the pack. Of…
I think this is really neat, but definitely not on the same tier as DALL-E 2, at least from the cherry-picked images I saw.
I'm not sure what you've seen but I've been very impressed indeed by some results I've obtained. Some less so.
It's hard to compare because we don't know how much cherry picking is going on with published Dall-E results (either v1 or v2)
My gut feeling is that it's in the same ballpark as Dall-E 1
Re: Dall-E 2
#137This reminds me of a discussion I had with the high school band teacher in the 90s. I was telling him that one day computers would play music and you won't be able to tell the difference. He got mad at me and told me that a computer could never play as well as a human with feelings, who can feel the piece and interpret it.
I think we passed that point a while ago, but seeing this makes me think we aren't too far off from computers composing pieces that actually sound good too.
Re: Dall-E 2
#138What jobs will be there in 5~10 years when we consider all the progress done with Dall-E, GPT-3, Codex/GitHub Copilot, Alpha* and so on?
The ones undoing the damage caused by dumb pattern recognizers and generators? ;)
Re: Dall-E 2
#139I'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?
Re: Dall-E 2
#140A few comments by someone who's spent way too much time in the AI-generated space: * I recommend reading the Risks and Limitations section that came with it because it's very through: https://github.com/openai/dalle-2-preview/blob/main/system-c... * Unlike GPT-3, my read of this announcement is that OpenAI does not intend to commercialize it, and that access to the waitlist is indeed more for testing its limits (and…
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