For about a decade, computer engineer Kerem Çamsari employed a novel approach known as probabilistic computing. Based on probabilistic bits (p-bits), it’s used to solve an array of complex ...

We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.

Deep learning modeling that incorporates physical knowledge is currently a hot topic, and a number of excellent techniques have emerged. The most well-known one is the physics-informed neural networks ...

While some AI courses focus purely on concepts, many beginner programs will touch on programming. Python is the go-to ...

The Center for Deep Learning’s (CDL) mission is to act as a resource for companies seeking to establish or improve access to artificial intelligence (AI) by providing technical capacity and expertise, ...

eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...

The recently published book Understanding Deep Learning by [Simon J. D. Prince] is notable not only for focusing primarily on the concepts behind Deep Learning — which should make it highly accessible ...

Microsoft announced on-device training of machine language models with the open source ONNX Runtime (ORT). The ORT is a cross-platform machine-learning model accelerator, providing an interface to ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...