The Computational Limits of Deep Learning Are Closer Than You Think Deep learning eats so much power that even small advances will be unfeasible give the massive environmental damage they will wreak, ...

The computational advantages of deep learning in AI, integrated with digital pathology for microscopy imaging, has led to the emergence of a new field called Computational Pathology (CoPath) that is ...

Rebooting AI: Deep learning, meet knowledge graphs Gary Marcus, a prominent figure in AI, is on a mission to instill a breath of fresh air to a discipline he sees as in danger of stagnating.

In a newly published study, MIT researchers find evidence that deep learning will soon (or already has) run up against computational limits.

Developed by Meta, PyTorch is a popular machine learning library that helps develop and train neural networks.

Intel last week announced that it would open source its nGraph Compiler, a neural network model compiler that supports multiple deep learning frameworks on the front-end, and compiles optimized ...

In this seminar we present our theoretical advancements in deep learning and computer vision algorithms with focused application in CoPath. We investigate this from both data-centric and model-centric ...