Real AI in Networking

The purest definition of AI is software that performs a task on par with a human expert. A subset of AI, machine learning (ML) provides an ability through a set of algorithms to learn and improve from experience.

AI technology is creeping into every industry. In the networking industry, the proliferation of devices, data, and people has made IT infrastructure more complex than ever to manage, with many looking to AI for help. Together AI and ML play an increasingly critical role in taming complexity for growing IT networks.

Let us help you on your journey through AI and ML. Our high-level overviews explore the meaning of AI in the networking industry. Our discussions with experts and other resources provide insight into real-life applications and business benefits of AI.

In the first video of our technical series, you’ll learn about some of the core tools we use in our AI platform: mutual information, decision trees, reinforcement learning, and long short-term memory recurrent neural network (LSTM RNN).

How mutual information helps you understand which network features have the most information for predicting failure or success in the service-level expectations (SLE) client metrics.

How data and building decision-tree models are used to predict failures of common networking problems.

How NLP works with Marvis, our AI engine, to help you resolve problems more effectively.

How reinforcement learning helps optimize channel and RF power settings.