INTRO
When searching Neural Network on the internet, we have got 2 results – ANN (Artificial Neural Network) and BNN (Biological Neural Network). The latter one is the natural cells and connections in lots of creatures as well as human. They are made by (so called) gods’ hands. In this biological neural network, multiple neurons convey informations with bioelectricity under the assistant of some biochemical medium. In hundreds years ago, human has been dreaming about becoming the cepheid of intelligence. They invented machines to release human from labor. And they wanted more — they wanted machines to be smart enough in order to take care of almost everything human needs to do. Just like an ancient Chinese story — 女娲抟土造人 (Nvwa created human according to her own body). Human designed Artificial Neural Network according to Biological Neural Network — to make machines think.
SIMILARITIES
Since ANN is built as the structure of BNN, it basically has similar look as BNN. They are both the composition of neurons (BNN is consist of neurons as cells well ANN is consist of neurons as nodes and edges). Multiple neurons switch informations by electric power to send or receive variables from their ancestors and pass it to their descendants.
(cited from: https://blog.knoldus.com/first-interaction-artificial-neural-network/)
In the picture above, the left side shows a biological neuron, and the right side shows the connections of multiple nodes(neurons) in ANN (we also call this fully-connected layer in this case). Each node stores a very simple and single-dimensional data xi, and outputs the result from an also very simple equation like yi+1=wi*xi+bi. In this scenario, each node (neuron) only does very small part of the job, but when we connect billions of nodes together, it becomes a super powerful self-fitting function after back propagations or reward functions, which help creatures/machines to make logical decisions.
DIFFERENCE
The scale of network is a huge difference. In human nervous system, there are over 100 billion neurons and over 7,000 synaptic connections within for each node (Cited: https://aiimpacts.org/scale-of-the-human-brain/). However, machines only owns few thousands or millions of computational nodes, let alone the limited connections between them. The storage and computational speed of human neural network is much more stronger than that of machines. Furthermore, all human do to create ANN nowadays is to make math formulas to make ANN acts locally. In another word, normal machine learning networks are always right — it is a huge different from human. They are taught by human to be good, but are not eligible to recover from failures. We learn from some essays that proves some network to be self-recoverable and self-extendible. But it should take time.