I have been reading a lot about how genAI and Large Language Models with machine learning (LLM/ML) will replace humans, or at least much of the work, in many white-collar positions.
I see the potential in this technology to provide a true intent-based interface to human/machine communications, especially when combined with natural language processing and a combination of voice and rich visual output, including VR.
However, I am much more interested in something greater: The ability of genAI to multiply human intelligence and abilities by giving us easy access to a rich store of information that will allow us to be superhuman. I have been seeing some demonstrations and have been briefed by several telecommunications software vendors that are doing just this. Unfortunately, I cannot reveal their names or detailed plans, yet. But expect to hear a lot about it at Mobile World Congress (#MWC24).
What can be done? Here’s a selection:
- LLM generally trained to communicate via text on a PC mobile app or via voice
- Additionally, trained on telecom-specific terminology and technology
- And
- all the network equipment manuals
- the standards
- the company’s standard processes and policies
- Access to real-time information from service assurance systems, provisioning systems, and other OSSs and BSSs without having to be trained in the use of those systems.
- Access to recommendations on next-best actions according to the previously mentioned.
- Ability to request additional information, make predictions, order diagnostic tests or make configuration changes to the network equipment.
The users would be the field technicians (that would need to talk to experts much less) and the network operations center, service operations center, and security operations center personnel. They would be able to handle a much wider set of problems without as much specific technical training on the peculiarities of the systems from which they get information. SUPERHUMAN POWERS!
Contact Mark Mortensen at mmortensen@acgc.com for more information.
