Some artificial intelligence models can already resemble the human brain even before having learned anything. This surprising ...

As you begin your hybrid quantum approach, here are the advantages, use cases and limitations to keep in mind.

Deep neural networks have a huge advantage: They replace “feature engineering”—a difficult and arduous part of the classic machine learning cycle—with an end-to-end process that automatically learns ...

Even networks long considered "untrainable" can learn effectively with a bit of a helping hand. Researchers at MIT's Computer ...

This technical paper titled “Can one hear the shape of a neural network?: Snooping the GPU via Magnetic Side Channel” was presented by researchers at Columbia University, Adobe Research and University ...

A new approach to designing AI based on biologically inspired architecture could cut the number of data centers needed to run ...

Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, ...

AI is creeping into everything from smartphones to cars, but tailoring neural networks to each new bit of hardware is expensive and contributes to AI’s rapidly-growing carbon footprint. So MIT ...

Neural architecture search promises to speed up the process of finding neural network architectures that will yield good models for a given dataset. Neural architecture search is the task of ...