If you have no desktop PC or no money for a GPU, it might be a better choice to use a EC2 instance instead of buying the hardware. You pay about $11 a week for a EC2, which is quite good once you compare it against the electricity costs that come on top of running a personal computer.

The downside is that you have a slow EC2 GPU with 4 GB RAM. Conv nets that take 3 weeks on a EC2, will take less than 2 weeks on a GTX980. If you run large conv nets, the 4 GB can be limiting (for example on ImageNet or similarly sized data sets).

Another point is that is more convenient to work on your own desktop and you can run multi-GPU nets, which is not possible on EC2 because the virtualization kills the memory bandwidth between GPUs.

If you think about it, over the long term a personal system will just be more cost efficient (you can keep a good system for years). So for deep learning researcher and those that apply deep learning this is just the most cost effective option.

A example calculation: You can buy a faster system than a EC2 for roughly $400 (GTX 580 + other parts from eBay). Together with electricity costs thats about 1 year worth of EC2, or 2 years worth if you use deep learning sporadically. A high end deep learning system will be about $1000-1400, which is about 3 years worth of EC2. So a EC2 makes good sense, if you use deep learning only sporadically and work with small data sets. If you use deep learning heavily, want a faster system or want to use multiple GPUs, a personal system will be better.