Covers general notions and hypotheses of simple traction or compression, stress analysis, and strain energy in materials.
Explores data compression through entropy definition, types, and practical examples, illustrating its role in efficient information storage and transmission.
Explores second-order model compression for massive deep neural networks, showcasing compression techniques and their impact on model accuracy.
Explores challenges in human communication, context importance, compression problems, uncertain functionality, and proof verification.
Explores material behavior in shear, shear forces, stress, equilibrium, shear laws, tension/compression, plane shear, shear rate, constrained slip, and shear strength.
