An AI model is a standalone file with internal numerical representations of data, not a server or program, and it can only predict the next word.
CJ explains that the end result of AI training is a single file containing billions/trillions of numbers, which works by predicting the next word sequentially. It's not connected to the internet and is fundamentally just a file, like a photo on your phone. ✦ AI generated
CJ · Syntax · 2026-07-30 · original ↗
starts at this moment · 3:00
The end result of all of that upfront analyzing of all of that data is a single file that predicts words. It's not a server farm, it's not a computer, it's not a program running on a computer, it's a file with trillions or billions of numbers inside of it. Now, if you're not familiar with this file metaphor we use in computers, think about your camera roll on your phone. Every single photo you take is a file. It's an individual thing that you can send to other people or open up on your phone. That's a file. And these models are also files. They're just a particular kind of file that's very large and have a bunch of numbers inside of them. Now, this is the key distinction to make because the model file itself is not connected to the internet. It was essentially created by analyzing the occurrence and relationships of every word on the internet. And so, the model file has all of that information embedded inside of it as a collection of numbers. You could think of it like an encyclopedia that predicts words, but it's not connected to anything. It can't access the internet. It is literally just a file that when run through some other program, predicts words.
verbatim transcript · starts at 3:00
3:00full answer from the model. Now, it's important to note that the end result of all of that upfront analyzing all of all of that data is a single file that predicts words. It's not a server farm, it's not a computer, it's not a program running on a computer, it's a file with trillions or billions of numbers inside of it. Now, if you're not familiar with this file metaphor we use in computers,
3:20think about your camera roll on your phone. Every single photo you take is a file. It's an individual thing that you can send to other people or open up on your phone. That's a file. And these models are also files. They're just a a particular kind of file that's very large and have a bunch of numbers inside of them. Now, this is the key distinction to make because the model
3:41file itself is not connected to the internet. It was essentially created by analyzing the occurrence and relationships of every word on the internet. And so, the model file has all of that information embedded inside of it as a collection of numbers. You could think of it like an encyclopedia that predicts words, but it's not connected to anything. It can't access the internet. It is literally just a file
4:01that when run through some other program, predicts words. Now, the process of creating these models and analyzing all of this data is where a lot of the news is coming from. Because when you slurp up all the data from the internet, there's going to be a lot of copyrighted works in there, as well as works from news organizations or individual blogs or musicians or artists, and they didn't necessarily
4:22agree up front that their data could be used to create this model file. And these models were not not only trained on all of the data that exists on the internet, but also trained on more curated or synthetic data. And this is where this idea of distillation comes in. >> [music] >> It's essentially where you can prompt a model to see how it responds, then save that response in its own file.