Tech Mahindra Unveils Innovative Telecom Model Leveraging NVIDIA AI Technology
Tech Mahindra, a leader in technology consulting and digital solutions, has recently unveiled an innovative telecommunications model that harnesses NVIDIA AI Enterprise and AWS cloud infrastructure. This model aims to transform operations in the telecom sector by facilitating autonomous network operations, significantly enhancing efficiency and performance.
The new multimodal operations model is built upon the Llama 3.1 framework and has been specifically tailored for telecom networks. This customization has been achieved through extensive training on large datasets from network operations, utilizing the latest generative AI frameworks. The system is designed to handle both structured data such as events and alarms, as well as unstructured data including logs, images, and various types of marketing material. Such versatility allows for proactive issue resolution and improved service quality.
Traditionally, telecom companies have implemented AI use cases in a transactional manner. However, to achieve true operational efficiency, a comprehensive integration of AI capabilities across the network is required. Tech Mahindra, in collaboration with NVIDIA and AWS, is playing a crucial role in facilitating this needed transition. This partnership combines Tech Mahindra's netOps.ai network automation platform and the Tech Mahindra Optimized Framework (TENO) with NVIDIA AI Enterprise, along with AWS's Elastic Container Registry, Elastic Compute Cloud, and Elastic Kubernetes Service.
One of the main objectives of this model is to transition traditional telecom networks into fully autonomous environments, incorporating principles of self-sufficient and intent-based networks. As stated by Manish Mangal, the Chief Technology Officer of Network Services at Tech Mahindra, the shift towards autonomous networks is critical within the telecom industry. He emphasized that the collaboration with NVIDIA and AWS is groundbreaking and is tailored to enhance network security while automating network management processes to improve overall operational efficiency.
In its initial phase, the large-scale multimodal operations model will focus on enhancing operational efficiency through intelligent observability. This will introduce two critical AI-driven use cases. The first, Dynamic Network Insights Studio, will offer a comprehensive 360-degree network observability solution, yielding insights into the network's performance for AI teams, network operations, and senior executives. Complementarily, the Proactive Network Anomaly Resolution Hub is an advanced AI-powered automated resolution system. This hub will autonomously detect and resolve network anomalies, such as alarms or events, without the need for human intervention.
Chris Penrose, Vice President of Telco Business Development at NVIDIA, noted that the introduction of large-scale telecommunications models capable of understanding network language represents a transformative moment in the sector. These models enable AI-accelerated operations within telecoms. The innovative model from Tech Mahindra, grounded in NVIDIA AI Enterprise, lays the foundation for developing multiple AI agents, which will further empower fully autonomous networks.
Moreover, the architecture will seamlessly integrate AI-driven intelligence into network operations. This integration comprises three key components: efficient data ingestion from the network, data curation and model personalization to enhance AI training, and the implementation of automated actions for rapid service resolution and restoration.
With global spending on AI in telecommunications reaching multimillion-dollar investments, this collaboration reinforces Tech Mahindra's commitment to advancing AI innovation within the sector. The long-term vision of Tech Mahindra includes applying the large-scale multimodal operations model to impact additional business use cases beyond telecommunications.
For further information on collaborating with Tech Mahindra to meet your Scale at Speed™ requirements, visit their website. Stay connected with Tech Mahindra through their social media channels, including Facebook, Twitter, LinkedIn, and YouTube.
The new multimodal operations model is built upon the Llama 3.1 framework and has been specifically tailored for telecom networks. This customization has been achieved through extensive training on large datasets from network operations, utilizing the latest generative AI frameworks. The system is designed to handle both structured data such as events and alarms, as well as unstructured data including logs, images, and various types of marketing material. Such versatility allows for proactive issue resolution and improved service quality.
Traditionally, telecom companies have implemented AI use cases in a transactional manner. However, to achieve true operational efficiency, a comprehensive integration of AI capabilities across the network is required. Tech Mahindra, in collaboration with NVIDIA and AWS, is playing a crucial role in facilitating this needed transition. This partnership combines Tech Mahindra's netOps.ai network automation platform and the Tech Mahindra Optimized Framework (TENO) with NVIDIA AI Enterprise, along with AWS's Elastic Container Registry, Elastic Compute Cloud, and Elastic Kubernetes Service.
One of the main objectives of this model is to transition traditional telecom networks into fully autonomous environments, incorporating principles of self-sufficient and intent-based networks. As stated by Manish Mangal, the Chief Technology Officer of Network Services at Tech Mahindra, the shift towards autonomous networks is critical within the telecom industry. He emphasized that the collaboration with NVIDIA and AWS is groundbreaking and is tailored to enhance network security while automating network management processes to improve overall operational efficiency.
In its initial phase, the large-scale multimodal operations model will focus on enhancing operational efficiency through intelligent observability. This will introduce two critical AI-driven use cases. The first, Dynamic Network Insights Studio, will offer a comprehensive 360-degree network observability solution, yielding insights into the network's performance for AI teams, network operations, and senior executives. Complementarily, the Proactive Network Anomaly Resolution Hub is an advanced AI-powered automated resolution system. This hub will autonomously detect and resolve network anomalies, such as alarms or events, without the need for human intervention.
Chris Penrose, Vice President of Telco Business Development at NVIDIA, noted that the introduction of large-scale telecommunications models capable of understanding network language represents a transformative moment in the sector. These models enable AI-accelerated operations within telecoms. The innovative model from Tech Mahindra, grounded in NVIDIA AI Enterprise, lays the foundation for developing multiple AI agents, which will further empower fully autonomous networks.
Moreover, the architecture will seamlessly integrate AI-driven intelligence into network operations. This integration comprises three key components: efficient data ingestion from the network, data curation and model personalization to enhance AI training, and the implementation of automated actions for rapid service resolution and restoration.
With global spending on AI in telecommunications reaching multimillion-dollar investments, this collaboration reinforces Tech Mahindra's commitment to advancing AI innovation within the sector. The long-term vision of Tech Mahindra includes applying the large-scale multimodal operations model to impact additional business use cases beyond telecommunications.
For further information on collaborating with Tech Mahindra to meet your Scale at Speed™ requirements, visit their website. Stay connected with Tech Mahindra through their social media channels, including Facebook, Twitter, LinkedIn, and YouTube.
Topics Telecommunications）
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