People not sharing weights (or sharing but on non-open licenses) is an issue. Other things are not an issue (and from the tone of this post is clear that they r

People not sharing weights (or sharing but on non-open licenses) is an issue. Other things are not an issue (and from the tone of this post is clear that they repeat misheard things). First, you can load things into your network regardless if you use CPU or GPU. And if needed, people can write GPU code for other architectures/ Second, inference (prediction) is fast. Yeah, it may be not useful for real-time applications on CPU (like: self-driving cars) but for detecting one object it can be fast (see e.g. https://transcranial.github.io/keras-js/#/resnet50 https://transcranial.github.io/keras-js/#/resnet50). Third, using things like TensorFlow.js you get GPU acceleration with any GPU card, not only nVidia. It is not nearly as fast, but still faster than Python + CPU. There are real-time demos such as https://experiments.withgoogle.com/collection/ai/move-mirror/view/mirror https://experiments.withgoogle.com/collection/ai/move-mirror.... Side note: I just start https://inbrowser.ai/ https://inbrowser.ai/ for tutorials and open source templates for using fully frontend AI.