“Maybe someday the language models will be able to write books better than I can. But here’s the thing: Using those models in such a way absolutely misses the point, because it looks at art only as a product. Why did I write [my first manuscript]?… It was for the satisfaction of having written a novel, feeling the accomplishment, and learning how to do it. I tell you right now, if you’ve never finished a project on this level, it’s one of the most sweet, beautiful, and transcendent moments. I was holding that manuscript, thinking to myself, ‘I did it. I did it.’”

They are pieces of a larger 10-part 'Luna Series' hanging in the store and available for pick up today!

Oh yeah. If you're generating text that could burn anywhere from 0.17 watt hours to 2 watt hours, equal to running this grill for about four seconds. Generating an image add 1.7 watt hours. All that, less than 10 seconds on the grill. But short videos can use far more power. In tests of various open source models, videos took anywhere between 20 watt hours and 110 watt hours. At 110 watt hours, one steamed electric grill steak, about equal to one video generation. I wouldn't eat it, but my dog would. At 220 watt hours, it was looking much more edible. So two video generations equals one pretty good looking steak.

After a bit of experimentation (and in a discovery that led us to collaborate), Southen found that it was in fact easy to generate many plagiaristic outputs, with brief prompts related to commercial films (prompts are shown).

In traditional artforms characterized by direct manipulation [32]of a material (e.g., painting, tattoo, or sculpture), the creator has a direct hand in creating thefinal output, and therefore it is relatively straightforward to identify the creator’s intentions andstyle in the output. Indeed, previous research has shown the relative importance of “intentionguessing” in the artistic viewing experience [33, 34], as well as the increased creative valueafforded to an artwork if elements of the human process (e.g., brushstrokes) are visible [35].However, generative techniques have strong aesthetics themselves [36]; for instance, it hasbecome apparent that certain generative tools are built to be as “realistic” as possible, resultingin a hyperrealistic aesthetic style. As these aesthetics propagate through visual culture, it can bedifficult for a casual viewer to identify the creator’s intention and individuality within the out-puts. Indeed, some creators have spoken about the challenges of getting generative AI modelsto produce images in new, different, or unique aesthetic styles [36, 37].

So what does a conscious universe have to do with AI and existential risk? It all comes back to whether our primary orientation is around quantity, or around quality. An understanding of reality that recognises consciousness as fundamental views the quality of your experience as equal to, or greater than, what can be quantified.Orienting toward quality, toward the experience of being alive, can radically change how we build technology, how we approach complex problems, and how we treat one another.

i'll ask now maurice to tell us a bit about his work

Dall-E is actually a combination of a few different AI models. A transformer translates between that latent representation language and English, taking English phrases and creating “pictures” in the latent space. A latent representation model then translates between that lower-dimensional “language” in the latent space and actual images. Finally, there’s a model called CLIP that goes in the opposite direction; it takes images and ranks them according to how close they are to the English phrase.

Then, once a model generates content, it will need to be evaluated and edited carefully by a human. Alternative prompt outputs may be combined into a single document. Image generation may require substantial manipulation.