AI-Generated Artificial Knowledge. Defined the very best approach: with… | by Cassie Kozyrkov | Jul, 2023


Defined the very best approach: with cats!

Why is AI-generated synthetic data all the fashion nowadays? On this article, I’ll clarify my favourite approach: with cats!

Let’s say I need to prepare a cat-not-cat classifier from scratch, however I solely have one picture to work with:

The writer’s cat, Huxley.

(All the pieces that follows is an analogy for what individuals do with tabular information and textual content information, so it applies past picture information.)

Ideally, I’m going to wish a dataset consisting of 1000’s of cat and not-cat photographs. If I’ve a digicam and plentiful entry to cats, I can take a bunch of photographs just like the one I have already got, guaranteeing that I get precisely the dataset I designed:

A photograph I took in a park in Istanbul.

However what if I don’t have a digicam and I reside catless on the moon? I might get the photographs I want from a vendor, although I must watch out since inherited data is extra harmful than major information.

Thanks, Pixabay, for being a wonderful (free) vendor of cat photographs.

However what if there’s no vendor who’ll promote me some cat photographs? (Sure, working out of cat photographs on the web is a state of affairs that’s extra sci-fi than residing on the moon, however bear with me.)

Effectively, if I can’t accumulate them and I can’t purchase them, then I’ll should make them myself. Behold, my creation:

Your writer is a veritable Michelangelo.

No good? Yeah, drawing was by no means my sturdy go well with. One other technique to make pretend information is to repeat present datapoints, besides this isn’t going to be a lot use for offering educational selection.

This method fools nobody. I’ve nonetheless solely successfully obtained one datapoint.

It’ll be like educating a human scholar by giving them the identical instance time and again, so all they be taught is that one factor. If my dataset is 30,000 copies of this Huxley picture…

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