An Interview With Daniel Gross and Nat Friedman about the Democratization of AI

That was the big change. People had to wake up to the fact that it could be democratized. That’s why Stable Diffusion might end up amounting to nothing, but it will be one of the greatest products ever just because it will have changed so many people’s minds about what was possible.

I’m optimistic because it felt like AI was going to do nothing but be the Consumer Internet, it was just going to serve you stuff. This idea where actually normal people with normal jobs in their normal life can be more productive and can do more things and they’re not gated by “Will OpenAI give you permission to do it?”. No. Literally, anyone can

it is generally the case that most large companies, certainly most large enterprise companies, don’t innovate on UX and UI. Why they fail to do so I find is a fascinating question, but why is Figma possible? Why is Stripe possible? That’s because large companies, for whatever reason, don’t build great interfaces

The big shift also seems to be you can generate remarkably similar results with much smaller amounts of inputs or much dirtier input just harvesting stuff across the Internet, instead of putting in super highly-structured data. 

One of the views, famously, in the stories of progress, is how many people view the Manhattan Project as this massive moment of scientific discovery, and we did a lot of things at once, and we managed to make the nuclear bomb. But there’s another view of the Manhattan Project, which is that we assembled a lot of things that were on the shelf and ju

First, there will be amazing bolt-on uses of AI for existing products that really make those products much better and can just be added as features. They don’t change the workflow that much, but they already add a lot of value. I think Copilot is one of those, but there will also be , I think, new things that don’t fit neatly into an existing produ

 Not always. The thing I would always say with those models is that they alternate between spooky and kooky. So half the time or some fraction of the time, they’re so good, it’s spooky like, “How did it figure that out? It’s incredible. It’s reading my mind,” or “It knows this code better than I do.” Then sometimes it’s kooky, it’s just so wro

he question that we were trying to answer was, “How do you take a model which is actually pretty frequently wrong and still make that useful”? So you need to develop a UI which allows the user to get a sense and intuition themselves for when to pay attention to the suggestions and when not to, and to be able to automatically notice, “Oh, this is pr

people want to anthropomorphize everything and they want to put everything in human terms. The whole point of a computer is it just operates utterly and completely different than humans do. At the end of the day, it’s still calculating ones and zeros. So everything has to be distilled to that and it just does it at tremendously fast speed, un

Yup and I think one of the more interesting things about Stable Diffusion, this thing that we’re now seeing, where computers can generate art given a piece of text, is I don’t think it would be possible had in 1992 or 1993, Tim Berners-Lee not put the 

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