Exploring the possibility of improving computer engineering methods through the study of biology, as certain biological processes have the ability to store memories and hold volatile RAM in the electrical state which has yet to be implemented in computer science.
This episode explores the concept of neuromorphic computing and how it ties into the workings of the brain. The focus is on the idea of supervised learning, where an external user can control synaptic weights to achieve desired network activity, as well as the concept of attractors and network dynamics.
All cells in our body, including somatic and stem cells, form electrical networks during embryogenesis. Planaria hold the answer to deep questions and have been around for 400 million years.
The speaker reflects on whether we are far away from understanding how to effectively build a computer, given the complexity of the human mind and neurons, and discusses the concept of automata prior to space time and how it relates to understanding space time.
The universe is a life-like process because of its ability to remember and record memories, leading to more sophisticated processes of memory-building. This allows for the creation of physical objects with features that have memory bonds, as opposed to entropy-driven destruction.
The brain is an emergent property consisting of a bunch of different neurons firing together, resulting in a phenomenon of experiencing something more than just the neurons firing, which is insufficiently defined.