A smarter approach to training AI modelsDeep neural networks are facing significant limitations, and new approaches could lead to major advancements in AI.
Replica theory shows deep neural networks think alikeMost successful deep neural networks follow a similar trajectory in a low-dimensional space.Different neural networks take different paths but ultimately move the same way towards accuracy.
Matrix Manifold Neural Networks | HackerNoonDeep neural networks can be adapted to Riemannian manifolds, enhancing applications in computer vision and natural language processing.
A smarter approach to training AI modelsDeep neural networks are facing significant limitations, and new approaches could lead to major advancements in AI.
Replica theory shows deep neural networks think alikeMost successful deep neural networks follow a similar trajectory in a low-dimensional space.Different neural networks take different paths but ultimately move the same way towards accuracy.
Matrix Manifold Neural Networks | HackerNoonDeep neural networks can be adapted to Riemannian manifolds, enhancing applications in computer vision and natural language processing.
A Lie Group Approach to Riemannian Batch Normalization | HackerNoonUnified framework for Riemannian Batch Normalization on Lie groups enables better control of mean and variance for manifold-valued DNNs.
Driverless cars still lack common sense. AI chatbot technology could be the answerNew AI systems, like language-capable models, can enhance driverless cars to behave more like human drivers.