Repository logo
 

Book:
Neural Networks

Abstract

Neural Networks proposes to reconstruct situated practices, social histories, mediating techniques, and ontological assumptions that inform the computational project of the same name. If so-called machine learning comprises a statistical approach to pattern extraction, then neural networks can be defined as a biologically inspired model that relies on probabilistically weighted neuron-like units to identify such patterns. Far from signaling the ultimate convergence of human and machine intelligence, however, neural networks highlight the technologization of neurophysiology that characterizes virtually all strands of neuroscientific and AI research of the past century. Taking this traffic as its starting point, this volume explores how cognition came to be constructed as essentially computational in nature, to the point of underwriting a technologized view of human biology, psychology, and sociability, and how countermovements provide resources for thinking otherwise.
Dhaliwal, Ranjodh Singh; Lepage-Richer, Théo; Suchman, Lucy: Neural Networks. Lüneburg: meson press 2024.10.14619/0832
license icon

As long as there is no further specification, the item is under the following license: Creative Commons - Namensnennung - Nicht kommerziell