The AI-Native Telco Network II

The AI-Native Network I

The AI-Native Network III

I have been working on telco networks big Data, Machine Learning, Deep Learning and AI for the last 8 years or so. Between Interpretative AI, Predictive AI and Generative AI, we have seen much progress lately, but I think a lot of the discussions about using general Large Language Models for telco networks is not applicable.

Much of the datasets in Telcos, like in government and defense, is proprietary. It is not shared outside the organization and wouldn't suffer "contamination" from external sources unless under very specific conditions, for very limited subsets.

As a result, a large part of cloud-based, public LLMs are just noise as far as telcos are concerned. The largest opportunity is in proprietary, smaller models, where the algorithmics can be somewhat outsourced but the storage, processing, training of the model are in house. This type of sovereign or proprietary AI can better account for the specificity of a network and its users than larger models trained on generic data.

The problem many encounter is that the operators don't necessarily have all the data literacy or resource necessary to develop the algorithms or even to format the dataset properly, while specialized vendors might have the AI/ML domain expertise but cannot train the models on real data, since they are proprietary and stay on-network.

The result is telcos first focusing on the architecture and infrastructure of the data network and pipeline, the formatting and scrubbing of the dataset, the storage, processing and transmission of the data between on premise, private and the interaction with hybrid / public cloud instances.

Vendors are proposing a variety of solutions with promises of savings, new revenues and new services, but in many cases, they are based on models running on synthetic data and no one knows what the result will be until tested with the real dataset, tuned and remodeled.

Training models on synthetic data might be necessary for vendors but it's a bit like training for football in the hope to play rugby. Sure. some skills are transferable, but even a world class football player won't make it to professional rugby.

This is where the opportunity lies for operators. Recruit, train telco professionals to be data literate, so that they can understand how vendors should produce datasets and how to exploit them. This is not a spectator sport where you can just buy solutions off the shelf and let your vendors manage them for you.