IBM Deep Learning as a Service: Train your AI

IBM today announced the launch of the new Deep Learning as a Service (DLaaS) program for AI developers.

With Deep Learning as a Service (DLaaS), developers will be able to train neural networks using popular frameworks such as TensorFlow, PyTorch and Caffe without buying and maintaining costly hardware.

Η επιτρέπει στους επιστήμονες δεδομένων να εκπαιδεύουν τα μοντέλα τους, χρησιμοποιώντας μόνο τους πόρους που χρειάζονται, πληρώνοντας μόνο για τη GPU usage.Deep Learning

Each data processing unit in the cloud has been created for easy use and is ready for programming deep learning networks without the need for infrastructure management by users. In accordance with white paper published by IBM researchers:

Users can choose a set of supported deep learning frameworks, a neural network model, training data, and cost constraints. The service will then take care of the rest, providing them with an interactive, repetitive AI training experience.

For users to use them they should simply prepare their data, upload it, to start learning. They can then download the learning outcomes of their application.

It looks pretty simple and could possibly save weeks programming, according to TNW.

IBM is reportedly working to cope with the difficulty in practicing neural networks or at least to reduce development time. According to a blog post published by the company:

This deep learning as a service is an experimental learning environment which means users don't have to worry about programming and problem management. Her entire life cycle is automatically managed and results can be viewed in real time and reviewed later. Each training launch is automatically started, tracked and stopped after completion, saving users time and money as they can only pay for the resources they use.

The new Deep Learning as a Service (DLaaS) service works with Watson's excellent platform. This means that it was tested on one of the most advanced AI systems on the planet.

For more information, you can see it IBM blog.

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Written by giorgos

George still wonders what he's doing here ...

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