Guavus Blog

This article is an excerpt from the Tractica Research Report on Artificial Intelligence for Telecommunications Applications, published in 3Q 2019. This Tractica report details the major market drivers and barriers, technologies, key players, and forecasts related to eight telecom AI use cases.

IoT and 5G promise to revamp the mobile networking landscape but also present service providers with operational challenges driven by sheer scale. With the race to 5G well underway, it is imperative that service providers ramp up fast on machine learning and AI to establish partnerships with the leading vendors and integrators who have proven expertise in applying these new technologies in large-scale operational environments.

Guavus analytics experts explain how applying root issue analysis will drastically reduce the number of network alarms, reveal the hidden structure of issues and clearly identify the strength of the relationships between the issues.

Using AI-driven analytics to please customers and streamline operations in a 5G world Every day we’re being bombarded with emails, … Continued

Stephen Collins, Principal Analyst, ACG Research, Network Visibility and Analytics writes about the promise of cognitive systems, and how they can contribute breakthrough gains in operational efficiency. But the burning question is, how do we get there from here?

WiFi is the new battleground. Insatiable demands for bandwidth, new streaming games & apps and the need for everything NOW, makes providing networks for the modern day home a nightmare. See how AI-based analytics can make your Customer Experience smoother.

Dear Santa, With 1.9 billion children in the world, keeping track of who is naughty or nice must be an extremely daunting task, even for a person with magical powers such as yourself. But no fear, we’ve got a solution for you!

With ever increasing deployments of SDN and NFV, service providers will find analytics even more critical to operating their businesses efficiently and effectively. Here’s how cable operators can apply AI to virtualized networks.

Mobile Operators are looking for simplified, cost-efficient operational models.  Advanced analytics solutions utilizing machine intelligence and AI enable intelligent automation and simultaneously improve system availability.

Mobile Operators are looking for cost-efficient operational models.  Automation of existing static rules-based processes is not sufficient. Advanced architectures must be augmented with Closed Loop Control to enable transformed operations.

There is much confusion in the marketplace regarding what AI really means and how it can help us.  This week we tackle the difference between machine learning and AI and see how both can be applied to solve critical problems.

Supervised learning, unsupervised learning and reinforcement learning are 3 main categories of algorithms that can be used to model your data. Each of these has distinct advantages in different situations.