[ribalda]

I have realised that the age of a AI is just a movement of big corporations towards a profitable monopoly.

They are teaching us how to solve problems with hardware instead with algorithms, and we, as individuals, will never have access to their computing power.

[nl]

This is completely wrong.

I work in the field, and the way it works is like this, in this order:

1) Someone works out how to do something

2) Someone works out how to improve the accuracy

3) The accuracy maxes out

4) People improve training efficiency.

We see this over and over again. Take a look at the FastAI results on ImageNet training speed for example.

[fromthestart]

You can easily build and train commercial grade neural nets on consumer hardware. Read about, say, a state of the art image recognition net on arxiv, pull an implementation for python in tensor flow or cafe or pytorch or what have you from GitHub (tons of open source), and with nothing more than just a cursory understanding of what you're doing and some basic programming skills, you can run scripts to train and evaluate functional neural networks on your own data set. I've fully trained numerous modern architectures on a single 1080TI to perform image recognition in a matter of days.

All of this is within reach of the average developer. If there's any monopoly, it's over training data, which Google and Amazon happen to specialize in. But even large datasets exist as open source.

From what I can tell, machine learning, the precursor to AI, is here, and both knowlege and implementation are fully accessable to the general populace.