One of our tenets as an industry collaboration hub is to be on the cusp of innovation, and AI plays a pivotal role. There are plenty of high-level AI messages out there, what it can and will do for networks– but real work is happening within LF Networking, as real operations and developers across the ecosystem are coming together to collaborate on what’s next, with the LFN AI Task Force.
The output of the work from the LFN community, which is comprised of about 80% of the world’s Top 10 Telecom CAPEX spenders globally, will be shown at ONE Summit as concrete call to actions for community
Read below to see what’s in store both at ONE Summit and within the LFN AI Taskforce in general, and how you can get involved.
AI for Networking and Networking for AI – what is it?
As 5G, IoT and edge computing technologies gain traction, new opportunities arise but also come new complexities for network operations, such as:
- Operation of leading edge and legacy technologies, hybrid networks, multiple radio spectrums for private and public 5G connectivity
- Ever growing number of connected devices
- Emerging requirements from industrial use cases push the boundaries of network performance and require optimization of power and bandwidth.
AI for networking helps to address these challenges by offering new technological approaches to operating networks. Networking for AI on the other hand, refers to building networks that are designed for AI workloads that tend to have extreme requirements on the network infrastructure.
How LFN Fits into AI for Networks
LFN, as the nexus for open source networking software development, is naturally positioned to build next generation tools for network operators, with as a strong:
- Locus for industry knowledge
- Network infrastructure experience (Virtualized and containerized)
- Community structure geared towards collaboration and innovation
As we look towards integrating AI into our projects and initiatives as a way to improve the project outputs, we’re focusing on these key areas:
- Making network data sets available to developers and open source communities
- Applying emerging AI tools and methodologies to developing open source networking software
- Using AI centric approach to solve network design, build and operations
Enter the LFN AI TaskForce
Last year, we convened the “LFN AI Taskforce,” an initiative with the goal of helping to identify, define, and operationalize the role of AI in open networking by exploring use cases, domain-specific AI models, and identifying data sets from large carriers to leverage for training the models. Key elements of the initiative include:
- Identifying the real areas in which Telco, Cloud, and Enterprise should work in AI, from “AI for the Network” and “Network for AI” perspectives
- There are some strong foundation already laid via infrastructure projects, such as ONAP, that are intent-based with large data sets, which is more than 70% of the prep work to enable AI for networking
- Working closely with our sister sub-foundations, LF AI & Data (a horizontal construct not domain-specific) & the OpenSSF Foundation (a security vertical).
- LFN focuses on different layers of the solution stack (e.g., the network & network infrastructure layer).
Learn more & join us!
Join us at this year’s ONE Summit, taking place April 29-May 1 in San Jose, CA, to be part of the AI movement within open networking. We’re bringing the AI content into our existing, premiere open network ecosystem events with an entire track focused on AI Implementation Across Telecom + Cloud and Enterprise & Edge, as well as keynotes, demos and interactive sessions on AI.
You can also peruse the LFN AI Taskforce wiki page to see what’s going on in real time, and stay tuned for more details on use cases, best practices, data sets, and more.
