I had no idea what the fuss was all about, and not much now. However, I shall write what I think it is about. I may be wrong of course.

Search engines collect and index text easily, but not images. To identify objects in images requires much more complex computing. Google wrote a software library for machine learning and artificial intelligence, called TensorFlow.

They then developed an application-specific integrated circuit, optimised to do much of the TensorFlow work in specialised hardware at a much faster rate and lower power. 

I have only a passing interest in the tasks it was designed for, mainly because I can't think of killer applications that would interest me... yet. I just have a few nascent ideas.

In the mean time, I do know a data scientist who is a maths geek and is able to write machine learning programs. I helped install TensorFlow and Keras software on her Linux laptop. Tip: just use the Linux software manager.

Keras is a software library that provides a Python interface for artificial neural networks, and acts as an interface for the TensorFlow library. 

The Keras website recommends a book called "Deep Learning with Python" which recommends using an NVIDIA graphics card, I presume to use the GPU(s) for acceleration. This is impossible on the Linux laptop which has an Intel CPU with integrated graphics. Maybe on my floortop PC which has a NVIDIA G96C [GeForce 9500 GT] graphics card, which I think has 32 CUDA cores. Whatever the case, I think the accelerator dongle will beat the graphics card acceleration. We shall run tests to measure just how much faster they make programs.