How Man-Made Neural Networks Emulate Biology to Advance AI and ML

We still have lots to learn about how a biological brain works, but what we do know is leading to breakthroughs in the implementation of artificial intelligence. Technology is approaching an inflection point in history, where humankind is able to faithfully recreate nature's greatest achievement and produce systems that can emulate the way we process information. Research into artificial neural networks is pursuing multiple avenues, two of which show great promise: convolutional neural networks (CNNs) and spiking neural networks (SNNs). While both CNNs and SNNs are inspired by the way the brain processes information, they differ in some significant ways in their implementation. The input stimuli to the brain, whether they are visual, auditory, olfactory or in any other form, are processed through successive (hierarchical) numbers of neurons, interconnected by a dense network of synapses (Figure 1).