AI in Networking white paper

 This page is to track progress in updating the original 2021 white paper "Intelligent Networking, AI and Machine Learning." The goal is to have this complete and ready for publishing at ONE Summit 2024 (April 29 - May 1).

Previous Reference Documents in support of 

NFV Testing and Automation White Paper- A Service Provider’s Perspective

AI/ML data and model sharing

2021 VERSION FOR COMMENTS/SUGGESTIONS: https://docs.google.com/document/d/1RqTZXOXO3bq0Y7ErGitk090CZZ4NBDgM/edit?usp=sharing&ouid=116649357309688115842&rtpof=true&sd=true 

Could you put the 2021 version in the wiki as I am unable to access the Google docs version due to company restrictions on access.  Lingli Deng 

[ For Discussion & iteration based on 2021 version -  red text below are notes for V2]

White Paper Assumptions and Overall Objectives:

• Paper Overview: Based on the findings of a LFN sponsored survey of over 60 operators and vendors in the telecom segment, demonstrate the current state of adoption of the AI/ML technology for operators. 

2024: Leverage AI Board survey from late 2023, focus on large models & Gen AI. Discuss how emerging AI tools like LLMs could be applied to network design, build and operation. We should cover what has changed from the previous survey and how that has and will inform the community's AI research and development direction. Also talk about the AI Taskforce and how it came to be.

• Audience:  Technical and strategic leaders in the Telecom Industry interested in understanding the role that intelligent tools, AI and machine learning can have in support of their network infrastructure, customers and operations. 
• 7-10 Pages in length total – possibly might have some separate related papers on specific use cases and other information that does not fit into this one
• Purpose of White Paper is to share information about EUAG member companies’ approaches to network intelligence 

2024: Purpose is to show LFN's leadership in LLM/AI space by outlining specific plans and areas where the community will collaborate in the open. Specific examples are a plus, as well as planned PoCs.  Overall the purpose of the paper has not changed, but if possible, would like to highlight the progress that has been made in the space since the previous paper was written two years ago.  We have come a long way since then.

• Make recommendations on where Open Source communities should be focusing their resources to further the intelligent networking efforts.
• Call to action. Market and executive orientation.  Purpose is to get people excited about Intelligent Networking as emerging technology and its importance, yet have an understanding of where the gaps are in both the technology and its adoption.. Bullet list of gaps.  2-3 bullet items.  Identify missing Open-Source tools and potential projects.

2024: Promote the LFN AI Task Force; identify areas of momentum and gaps; solicit more contributors to open source efforts driven by LFN; Encourage existing and future LFN members to bring more AI work to the open source communities domain; Create some FOMO by positioning LFN as the collaboration hub for AI.  Again, expand on what we have done since the previous paper was written and future directions and work that needs to be done to get to the next stage of development.

• Do not declare or propose a definite solution just share EUAG Operator community point of view

Good news folks - We are only late by 1 week!

Work stream Schedule