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

I think the real discovery is the fact that we have the Internet and that it might go down in history as the only way we could’ve made AI is we digitized the world.

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

 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

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. 

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

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

Yeah, I think that’s right. I think the Internet and the ability for pretty much anyone to just go,  at relatively low cost, scrape the data they need off the Internet and train on it is a big democratizing force. Now, that said, there is a norm in the community that if you have a algorithmic breakthrough, you publish your research,  but

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

The thing that Copilot gave us that we, again, only realized in retrospect was this randomized psychological reward.  It’s like a slot machine where the ongoing cost of using it at any given moment is not very high, but then periodically you hit this jackpot where it generates a whole function for you and you’re utterly delighted .