I think that crucial to working with AI is that, as it stands, the need for expensive hardware to train it makes it currently a centralizing technology. However, there are things we can do to combat that. For example, the AI Horde offers distributed computing for AI applications.

And how is it not all still just theft with extra steps that is imoral to use?

We gotta find datasets that are ethically collected. As a practitioner, that means not using data for training unless you are certain it wasn't stolen. To be completely honest, I am quite skeptical of the ethics of the datasets that the popular AI products were trained on. Hence why I refuse to use those products.

Personally, I'm a lot more interested in the applications to robotics and industrial automation than generating anime tiddies and building chat bots. Like I'm not looking to convince you that these tools are "intelligent", merely useful. In a similar vein, PID controllers are not "smart" at all, but they are the backbone of industrial automation. (Actually, a proven use for "AI" algorithms is to make an adaptive PID controller so that's it can respond to changes in the plant over time.)

[–] NuraShiny@hexbear.net 1 points 4 months ago (1 children)

These datasets do not exist, you got that right.

I highly doubt there is much AI deep learning needed to keep a robot arms PIDs accurate. That seems like something a regular old algorithm can do.

[–] PM_ME_VINTAGE_30S@lemmy.sdf.org 1 points 4 months ago* (last edited 4 months ago)

A deep neural adaptive PID controller would be a bit overkill for a simple robot arm, but for say a flexible-link robot arm it could prove useful. They can also work as part of the controller for systems governed by partial differential equations, like in fluid dynamics. They're also great for system identification, the results of which might indicate that the ultimate controller should be some "boring" algorithm.