Boundaries

Boundaries

Auteur : Barrie Sosinsky

Date de publication : 2023-08-27

Éditeur : Major Sosinsky

Nombre de pages : 302

Résumé du livre

This book is a study of light and vision. It was written for people who love science. Not just their own science but science in general. Information rich, broad in scope, and written to be fun to read - this is *NOT* a textbook. Sosinsky tackles vision, the "Godzilla of Neuroscience," and hopefully wrestles it to a draw.Boundaries is a journey of exploration. Boundaries traces the path light takes: a photon through the eye to the back of the brain and addresses the question: "Is the brain a computer?" The brain is best categorized as a relational automation. Sosinsky constructs the logic for that assertion within.This book constructs a model of light. (Watch light glow.) Light's symmetry is the reference frame used in all measurements. Light's symmetry has powerful things to say about what we measure and know. It is our gateway to reality, the things we can measure. Some equations are within (apologies), but shapes and pictures are primarily used. You get 25 lemmas to live by and 894 footnotes to keep you happily busy and off the streets at night.Darwin considered the eye an "Organ of extreme Perfection and Complication." It is far from that. The author follows evolution's path from our "inner worm" to describe how we got the kind of eyes we have and why they work the way they do. This book analyzes the retina and concludes that the retina differentiates the light field. An analysis of vision based on signal differentiation is presented within.Boundaries takes a stepwise approach to learn about vision, trying to understand what each part of the system tells us in the processing sequence. Vision is a very distributed process. As an example, face recognition is described. You will meet a Box jellyfish; Hue, Pixie, and Sparky; roaming rodents, unfortunate cats, mutchered monkeys, and people encased in large magnets (magneto-brains).Boundaries examines neural networks, both the wet and sparky kinds. The book ends by analyzing artificial neural networks and "deep" learning. Our brains are bokeh difference engines. You will understand why after reading this book.

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