A short YouTube talk (by James Hotson) about how AI's predictive capabilities—illustrated by code autocompletion—can scale to larger, context-aware tasks like writing entire functions from many files and automating marketing campaigns by learning from past ads and competitor data. The speaker argues these capabilities are near-term and will soon produce full campaigns and creative assets with limited human input.
Chapters
Imagine in coding and programming, we're really good at this. Autocomplete cursor made it really famous, which is, if you have a block of code, can I predict the next block of code? But then, then it said that, okay, if you have a block of code and if you have these 36 files, then based on these 36 files, in the context of these 36 files, how can I predict the next block of code? Now, if I have these 500 files about Jiva AI, for example, then how can I write an entire new function in the program with this block of code? Now this translates to everything else around us, right? In sales, in marketing, what we can say is like, here's 500 ads that I've run on Meta and Google and YouTube before, and here's ads that have worked for me, here's ads that have worked for my competitors. Now, based on this, create an entire campaign for the next month for me, right? Create meta ads, create YouTube ads, create Google, create videos for me. It's not far away for us to do that. Obviously it can do it along some humans right now, but that's what AI is going to be capable of very soon.