- Artificial Intelligence and Applied Machine Learning Project Group launched by the Telecom Infra Project (TIP)
- Project to focus on new approaches for improving network operations and customer experience through automation
- Deutsche Telekom and Telefonica to co-chair project group within Telecom Infra Project
How can AI and Machine Learning techniques be optimally applied to identify and predict faults before they adversely impact network performance? And by predicting customer behavior, can we ensure a best experience for latency-critical services such as autonomous vehicles? Also, if so, how can we make these models applicable across the industry? These are challenges addressed in a new Telecom Infra Project (TIP) initiative that targets the application of Machine Learning (ML) and AI to improve network operations and customer experience. The establishment of the Machine Learning and Artificial Intelligence Project Group (TIP AI/ML) was jointly announced today by co-chairs Deutsche Telekom and Telefonica, together with Facebook, at TIP Summit 2017 in Santa Clara.
“To keep pace with the growth in network size and traffic volume and service complexity, as well as the adoption of new services, autonomous vehicles, drones, AR/VR and more, requires new approaches for network operations and customer experience management,” says Bruno Jacobfeuerborn, Chief Technology Officer Deutsche Telekom. “The application of machine-based decision-making and auto-remediation approaches will be key to enabling the accelerated deployment of these new services while supporting hyper traffic growth at a lower cost structure.”
“Our objective is to define and share reusable, proven practices, models and technical requirements for applying artificial intelligence and machine learning to reduce the cost to plan and operate telecommunications networks,” says Wolfgang Wölker, Deutsche Telekom co-chair for the project group. Working together, we will leverage opportunities to optimize network operator and web scale platform provider services to ensure the best end-to-end customer experience.”
The project group is collaborating across three work streams:
- ML-based network operations, optimization, and planning to enhance intelligence in network operations areas through, for example, predictive maintenance and dynamic resource allocation.
- Customer behavior-driven service optimization to enhance the overall customer experience, particularly for bandwidth-intensive, latency-sensitive, and/or data-heavy applications.
- Multi-Vendor ML-AI Data Exchange Formats to ensure the development of generalized ML models that are applicable across the industry.
About TIP
Founded February 2016, the Telecom Infra Project is an engineering-focused initiative driven by operators, suppliers, developers, integrators, and startups to disaggregate the traditional network deployment approach. The collective aim of our community is to collaborate on new technologies, examine new business approaches and spur new investments into the telecom space. The founding members – Facebook, Deutsche Telekom, Intel, Nokia and SK Telecom – have since been joined by over 500 carriers, equipment vendors and systems integrators.
Deutsche Telekom is a founding member of TIP and shares its vision of fostering exponential innovation to overcome the telco industry’s challenge of meeting the exponential growth of Internet traffic. Another recent of example of Deutsche Telekom’s commitment to TIP is its co-chairing of the initiative’s Millimeter Wave Networks Project Group (mmWAVE), which was launched in September at Mobile World Congress Americas. The implementation of the mmWAVE test network has now been completed at the TIP Community lab in Berlin.
“Our goal in TIP is to deliver the best network services to our customers, and at the same time deliver a superior capital efficiency,” says Jacobfeuerborn. “This requires more radical approaches. We value contributions from other TIP members to this space and enjoy the excellent partnership we have as part of TIP and beyond.”
About Deutsche Telekom: Company profile
