March 20, 2018 | Written by: Ruchir Puri
Categorized: AI | Deep Learning | IBM Watson | Think 2018
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Artificial intelligence will be the most disruptive class of technologies over the next decade, fueled by near-endless amounts of data, and unprecedented advances in deep learning. The rise of deep learning has been fueled by three recent trends: the explosion in the amount of training data; the use of accelerators such as graphics processing units (GPUs); and the advancement in the training algorithms and neural network architectures.
Training of deep neural networks, known as deep learning, is currently highly complex and computationally intensive. It requires a highly-tuned system with the right combination of software, drivers, compute, memory, network, and storage resources. To realize the full potential of this rising trend, we want this technology to be more easily accessible to developers and data scientists so they can focus more on doing what they do best –concentrating on data and its refinements, training neural network models with automation over these large datasets, and creating cutting-edge models.
Today, I’m excited to announce the launch of Deep Learning as a Service within Watson Studio. Drawing from advances made at IBM Research, Deep Learning as a Service enables organizations to overcome the common barriers to deep learning deployment: skills, standardization, and complexity.
For the rest of the story visit the IBM Watson Blog.