What is Deep Learning?
Deep learning definition
In deep learning, large artificial neural networks are fed learning algorithms and ever-increasing amounts of data, continuously improving their ability to "think" and "learn.” "Deep" refers to the many layers the neural network accumulates over time, with performance improving as the network gets deeper. While most deep learning is currently done with human supervision, the aim is to create neural networks that are able to train themselves and "learn" independently.
Why deep learning?
Neural nets have been around since the 1950s, but only in recent years have both computational power and data storage capabilities advanced to the point where deep learning can be used to create exciting new technologies.
While most enterprises have yet to incorporate deep learning into their business processes or products, this type of machine learning is behind "smart" technology, ranging from voice- and image-recognition software to self-driving cars. Advances in deep learning and robotics may soon lead to smart medical imaging technology that can reliably make diagnoses, self-piloting drones, and self-maintaining machinery and infrastructure of all kinds.
HPE deep learning
HPE Pointnext: Leverage our newly enhanced Pointnext advisory, professional and operational support services offerings for deep learning, including HPE GreenLake Flex Capacity.
Flexible consumption: Consume your deep learning infrastructure using a flexible, on-demand consumption model. Get scalable capacity as needed, paying only for what you use, including servers, storage, networks, software, and services.
Galvanising manufacturing with artificial intelligence and deep learning
Discover how manufacturers are blending computer-aided engineering (CAE) and data-driven AI and deep learning technologies to improve operations and support more products, profitably.
- Drive value in manufacturing with AI and DL
- Deep learning benefits from HPC
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