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

So it’s interesting where there’s this tension between the more creative something is, the more allowance there is for error, which is good for AI. On the other hand, where AI is arguably the most useful and impactful is places where it’s just regurgitating stuff, but then the accuracy is a question. There’s a bit of a tension there.

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

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

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. 

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.

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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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

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 if you do