Telecoms and AI: Working Together for a Better Future

Artificial intelligence (AI) is revolutionising many industries, and the telecoms industry is no exception. Telecom companies play a crucial role in enabling AI by providing the infrastructure and data needed to train and power AI algorithms. In this blog, we will explore how telecoms and AI work together to create a better future.

Data Collection: The Fuel for AI Algorithms

AI algorithms are only as good as the data they’re trained on. Data collection is a critical component of AI algorithm development.

Telecommunications companies have the opportunity to become a prime data source for AI. Their vast streams of customer info, network traffic stats, and more offer incredibly valuable to boost the power behind AI algorithms.

Leveraging AI-powered analytics, telecoms can gain a wealth of insights about their networks and customers that may otherwise have gone unnoticed — allowing them to refine network performance and create superior customer experiences.

It’s a win-win!

To streamline data collection, tools like Weaver Labs’ WireMQ can be used.

• WireMQ is a proprietary transactional asynchronous messaging system that enables communication between distributed systems and applications in a scalable and reliable manner.

WireMQ’s ability to fast-track the setup of communication channels and endpoints saves time and resources for AI companies, allowing them to focus on developing algorithms and using the collected data to improve the models.

You can learn more about Wire-MQ and some of its use cases here.

Edge Computing: A Game-Changer for AI

Edge computing has emerged as a new paradigm in computing that can address the significant computational power required for processing vast amounts of data in developing effective AI algorithms.

By processing data closer to the source, edge computing can significantly reduce latency and processing requirements, enabling more efficient AI algorithm development and local data processing, bringing high-performance computing capabilities and real-time analytics to the edge, where sensors and IoT devices are located.

At Weaver Labs, we proved this in 2022, when we utilised Cell-Stack to enable edge computing in the deployment of VivaCity’s AI-based solution in Manchester, leveraging an edge-cloud 5G network.

• The results were remarkable, with a 23% reduction in journey times achieved through AI-powered traffic management!

You can learn more about this project and the solution we created here.

Network Optimization: A Win-Win for Everyone

Network optimization is a critical aspect of the telecom industry, and leveraging AI algorithms can be a game-changer in improving network efficiency and reliability. By analysing data on network traffic, performance, and other factors, AI can help telecom companies optimise their networks, resulting in better services for customers and increased performance for AI applications.

At Weaver Labs, we understand the importance of network optimization and have developed modules within Cell-Stack to aid in this process.

Our monitoring module allows the gathering and managing of real-time data related to energy consumption, network usage, mesh nodes, and infrastructure.

This homogeneous data set can be easily consumed by AI applications to optimise telecom networks and improve performance, it is also crucial for many AI applications that rely on specific data points, allowing developers to build AI applications on top of Cell-Stack’s infrastructure without worrying about the complexities of data processing or storage.

The Power of Partnership: How AI and Telecoms are Creating a Better Future

Telecom companies provide the necessary infrastructure and data required for AI algorithm development whilst telecom companies can leverage AI to enhance new technology such as IoT devices and optimise their networks.

Overall, the partnership between AI and telecoms offers significant benefits for both industries, creating a win-win situation that fosters innovation, growth, and a better future!