The Conversational Network: AI-Powered Language Models for Smarter Cable Operations
- How can GenAI help operators and vendors all be more efficient and effective
- Exploring the potential of GenAI and LLMs to solve operational challenges:
- Assisting technicians and engineers
- Improving on the job training
- Writing technical documents, standards, and specifications
- Lesson learned: Challenges, tactics, tools, information sharing and innovation.
Tyler Glenn
Principal Engineer
CableLabs
Supercharging Proactive Network Maintenance by Leveraging Generative AI and ML
- Obtaining insights to develop tools and best practices for deploying AI/ML for DOCSIS® technologies
- Developing methods to to fine-tune and refine the performance of LLMs on domain-specific data: Retrieval Augmented Generation (RAG) and low rank adaption (LoRA)
- Building tools and sharing best practices for deploying AI/ML technologies
- Developing frameworks objective measures using NLP-based metrics to measure, track, and improve model performance and efficacy
Santhana Chari
VP, Broadband Analytics and Data Science
OpenVault
Leveraging JSON Data for a Network Data Chatbot
- Understanding the constraints; identifying corporate requirements and needs to further develop large language models (LLMs)
- Implementing a retrieval augmented generation (RAG) framework based on the LangChain orchestrator that runs an LLM agent
- Retrieving relevant network data in JSON snippets from a knowledge graph database
- Developing wider strategies to meet the requirements and needs in network data chatbots
David Suh
Lead Software Engineer
Cox Communications
Moderator
Jan Neumann
Senior Director, Applied AI Research
Comcast
