Simulated data: the great equalizer in the AI race?

Re:Simulated data: the great equalizer in the AI race? by gilbaz on Thursday December 19, 2019 @02:59PM (#21838606)

Yeah but you're assuming that you know how their creating this data. Just throwing an option out there - what if they created a latent space of 3D people and iteratively expanded it with GANs and 2D real image datasets. That would generalize.

Just a thought, not sure what's really going on there, I just know that they probably have something interesting they're cooking up!

This is a really crazy vision

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Re:Simulated data: the great equalizer in the AI race? by kory on Thursday December 19, 2019 @03:04PM (#21838666)

Training a GAN to generate people without a significantly large dataset (if that's even possible) is probably just as difficult of a problem as just building the model you want in the end without sufficient data.

Assuming those image sets are small they will create a model with a large bias. If you're talking about fine-tuning an existing model with small datasets, this is done already and works fairly well if not overused.

It all comes down to: to create the first "data-generating" model you need a lot of data and compute. Expanding it is a different story, but that isn't where the problem lies. We come full-circle back to the same problem as what we started with: big players can afford to build these models and small players can't.

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