Continual Learning with Deep Artificial Neurons

Understand

Neurons in real brains are enormously complex computational units.

• Among other things, they're responsible for transforming inbound electro-chemical vectors into outbound action potentials, updating the strengths of intermediate synapses, regulating their own internal states, and modulating the behavior of other nearby neurons.
• One could argue that these cells are the only things exhibiting any semblance of real intelligence.
• It is odd, therefore, that the machine learning community has, for so long, relied upon the assumption that this complexity can be reduced to a simple sum and fire operation.