Automating Telecom Network Design with Infosys and NVIDIA
Infosys has introduced a new solution that leverages NVIDIA’s NIM and NeMo technologies to automate the creation of TOSCA templates, revolutionizing the telecom wireless network design process. This development aims to standardize approaches and minimize errors in network design, enhancing overall productivity in the telecom industry.
Utilizing Generative AI for Streamlined Network Design
With the use of generative AI, Infosys’ solution provides a standardized utility that generates service design templates based on prompts from network engineers. This automated tool, powered by NVIDIA NIM, simplifies parameter modifications and processes user inputs in real-time to produce customized YAML templates tailored to specific TOSCA design requirements.
- Infosys integrates pretrained and fine-tuned large language models (LLMs) like Llama 3-70B and Mistral-7B, delivered as NVIDIA NIM microservices.
- This integration ensures ease of use for stakeholders, enhancing productivity for network service designers and OSS solution architects.
Data Collection and Preparations for Enhanced Network Design
Infosys collected user guide network builder manuals, training documentation, and troubleshooting guides to provide accurate network design responses. A user-friendly chat interface with drag-and-drop features was developed to convert information seamlessly into a YAML file structure, enabling vector embeddings for retrieval augmented generation (RAG).
Addressing Technical Challenges with Innovative Solutions
To avoid delays, Infosys employed NVIDIA GPUs for swift generation of vector embeddings. The solution architecture included a React-based user interface, efficient data handling using FAISS, and robust backend services for configuration and user management. By integrating with NVIDIA NIM and NeMo microservices, Infosys enhanced generative AI capabilities for secure authentication and authorization.
Assessing LLM Performance for Enhanced Efficiency
Infosys conducted thorough tests on various LLM configurations to compare performance with and without NVIDIA NIM. The results indicated significant improvements in latency and accuracy when utilizing NVIDIA NIM and NeMo Retriever embedding microservices. This advancement enables network service designers to expedite network designs and reduce operational costs.
Illustrative Use Case
Consider a scenario where a TOSCA template needs to be generated for an Ethernet service with 100 Mbps bandwidth between 1PE and 2CE. The generative AI model can promptly provide a service template adhering to TOSCA standards in YAML format, showcasing its precision and customization capabilities based on user requirements.
Empowering Network Designers for Enhanced Efficiency
By automating TOSCA template generation, Infosys’ solution effectively eliminates the manual effort involved, enhancing efficiency and consistency for telecom companies. Through the integration of NVIDIA NIM and NeMo technologies, network service designers can streamline workflows, enhance productivity, and maintain uniformity in network design and orchestration.
Hot Take: Enhancing Telecom Network Design with AI
As a crypto enthusiast looking to stay updated on technological advancements, these innovations in telecom network design by Infosys and NVIDIA demonstrate the potential for AI to revolutionize traditional processes. By automating template generation and incorporating advanced technologies, telecom companies can achieve higher efficiency, accuracy, and cost-effectiveness in their network design operations.
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