So I've been using an eGPU for about 3 months now and it is amazing. This isn't officially supported so you end up having to do a lot of work arounds to get things like tensorflow/pytorch working.
It doesn't let you hot plug your eGPU into your computer (you have to restart for it to work) but for officially supported eGPUs you're now able to do that.
I've trained various models using a Titan XP and it's so awesome to be able to maintain the portability of your laptop and still get all of that power. A large benefit is also not having to move training data around between servers and other machines if you have it on an external drive or just on your laptop.
After you get everything up and running there isn't that much maintenance or anything you have to do regularly to keep it working. The speedup is incredible and it was definitely worth it for me personally, however it's not a walk in the park to get it set up initially.
I've tried it with an external monitor which works great but I haven't tried it with any games. From looking at the eGPU forums it seems like people aren't running into that many problems with it.
IMO it's more cost effective and stable just to buy a Ryzen 2400G system (the same cost as a good eGPU case), put in Linux and use it for training at a full speed. TB3 has 4x lower throughput than PCIe, so if you need to transfer a lot of data (any meaningful non-toy model these days), it's better to stick with internal GPU. Not mentioning Linux is 1st class/preferred platform for many frameworks like TensorFlow etc.
I say for thease sort of application why bother with MAC at all just go with Ryzen or wait for Ryzen2 out this month or go the full Threadripper or Eypc / Rome
These aren’t beta drivers. They’ve been released for quite some time and are updated with (almost) every macOS release. However I’d say they’re pretty barebones as Nvidia doesn’t seem to care too much about the Mac at this point.
In practice they work just fine, it's just very annoying to initially set them up and you have to do some patching to get the latest version of tensorflow working with it. I use one every day and I haven't run into any problems while running models with both pytorch and tensorflow.