Dr. Chris Hillman, Global AI Lead at Teradata, joins eSpeaks to explore why open data ecosystems are becoming essential for enterprise AI success. In this episode, he breaks down how openness — in ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More It’s as good a time as any to discuss the implications of advances in ...

A new computing architecture enables advanced machine-learning computations to be performed on a low-power, memory-constrained edge device. The technique may enable self-driving cars to make decisions ...

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 ...

The use of deep learning has grown rapidly over the past decade, thanks to the adoption of cloud-based technology and use of deep learning systems in big data, according to Emergen Research, which ...

(a) Deep-learning-pre-processing for phase recovery. (b) Deep-learning-in-processing for phase recovery. (c) Deep-learning-post-processing for phase recovery. (d) Deep learning for phase processing.

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

Although deep learning–based image recognition technology is rapidly advancing, it still remains difficult to clearly explain ...