Everything Guy Parsons said on any show that made the record, most notable first. Each card names its show and opens the statement there.
Parsons: Midjourney iterates on image models faster than OpenAI
“But then, of course, you have now tools like Midjourney, who've been, like, iterating on their text-to-image model, like, a lot more aggressively than OpenAI, who Understandably, I think maybe have some other things in the cooker, you know, which have now grow…”
Parsons: Prompt engineering will be a specialized craft, not universal skill
“I don't think it will become, like, this necessary skill that everyone needs to have, but I do think it will become, you know, like, some people are expert wood whittlers or, you know, really good at Animating hair or whatever, you know, the people that develo…”
Parsons: Art history and design backgrounds give prompt engineers an edge
“So if you've actually been to art school or you're up on your art history or your design language, then you probably got a head start on everyone else.”
Parsons: AI image models struggle with precise spatial layout prompts
“They often describe generally what the image is about, but not like how you would draw it step by step. And that's why these tools are less good at saying like, I want this thing over here and then that thing next to it and then something on top and that thing…”
Parsons: AI prompts yield diminishing returns as length increases
“And I think there's something to be said, like, I think the longer they are, there's definitely, like, diminishing returns.”
Parsons: Image-to-image AI models will power next-gen consumer interaction
“That's a really interesting space that's gonna probably power like the next generation of how people, especially consumers like interact with these products.”
Parsons: Generative AI fails when forced to produce highly specific work
“That's kind of the limitation of weather technology. Is at the moment, which is, it's amazing until you're trying to do something very specific. And especially if you want to do something very specific, this also to like a very high, like a professional standa…”
Parsons: Generative AI creates a massive market opportunity for editing apps
“Actually, I kind of think it's a big opportunity for, like, the photoshops of this world, because those are tools that presuppose you have some kind of original image to be able to, like, manipulate, whereas now there's a huge amount of, like, raw but maybe no…”
Parsons: Generative AI must evolve beyond text boxes for better usability
“The whole challenge and the whole opportunity, I think at the moment was like, how do you go beyond the text box? How do you go beyond this, like just blank rectangle to create something that is more user friendly, that's more inspiring. That's more how people…”
Parsons: Generative AI tools will be used quietly like green screens
“I suspect that when to an extent when you see these things used, especially in prominent contexts, they might not be advertised as such. Much is like green screen, right? Like when green screen is used in films, you shouldn't be like, that is an amazing use of…”
Parsons: AI developers are incentivized to eliminate prompt engineering
“There's obviously every incentive for the people that make these foundational tools to make prompt engineering, for instance, not A thing because they want everyone to be able to do it.”
Parsons: Careers will emerge around designing hidden AI prompt wrappers
“So there's probably going to be some people whose job is to like, come up with that layer of thing that the consumer or the average person is never seeing. And they think they're just talking to the AI, but really they're talking to this thing that then Adds a…”
Parsons: Prompt AI generators by describing images as existing stock captions
“Like I think if you've never used one before, like the best way to explain how they work is to always like describe something as if it already exists. Imagine that it's an image in some kind of downloadable clip art library, or it's on a photography gallery, a…”
Parsons: Stable Diffusion used 12M fine-tuning images for aesthetic quality
“Stable diffusion, I think some five billion and then like a smaller set of like twelve million for the what does nice look like fine tuning that's happened on the top and how they've optimized it.”
Parsons: Translating visual ideas into language remains a primary design challenge
“It's still quite hard to describe things with words. Designers, yeah, when they go and work, when they do work for clients, like it's one of their pet peeves because clients are like, they don't like it, but they can't explain why.”