Machine learning needs lots of data, and the best place for all that data and the systems that use it is in the cloud Topics Spotlight: New Thinking about Cloud Computing ...

Unlike other cloud-based services, ML and AI platforms are available through diverse delivery models such as cognitive computing, automated machine learning, ML model management, ML model serving ...

D-Wave's Murray Thom shared his company's quantum computing applications: about 50% optimization, 20% AI and ML, 10% materials science, and 20% other.

Though compute, storage, and networking continue to be the revenue spinners for cloud vendors, it is Machine Learning that is becoming the focal point of the contemporary cloud.

Up to a point, yes: Investors we talked to are giving entrepreneurs their blessing not to give too much thought to cloud spend in their early days. But the rise of machine learning makes us ...

Like any born-in-the-cloud company, it was seeking a better way to contain its monthly cloud computing bills. And so, in the cofounders' next act, this was the problem they trained their sights on.

He solidified his credentials by gaining in-depth knowledge of critical technologies, including AI-driven cloud computing, machine learning platforms like Azure Machine Learning and TensorFlow ...