Developing a low-code training platform to intelligently spot talent and upskill staff by matching them to relevant interactive training modules
* Targeting all operational scenarios of Autonomous Networks, the Expert Robot Family is created to possess three core capabilities: Intent-Based, Task-Based, and Knowledge-Based Expert Systems. The aim is to facilitate systematic AI capability development, sharing, and reuse in a production environment.
* The Expert Robot Family plays roles analogous to those of four talented family members in the Intent-Based, Task-Based, and Knowledge-Based closed loops across the network layer, service layer, and business layer. This approach is designed to elevate the performance of Autonomous Networks to a higher level.
* In the era of AI, where expert robots are replacing, and in some cases, surpassing humans, traditional human positions are being widely questioned.
The Talent for Tomorrow Phase II project aims to explore and implement "Human-Robot Collaboration" and "Robot-Robot Collaboration" in production environments. This initiative introduces talent transformation through the evolution of Autonomous Networks with the Large Language Model (LLM).
In Phase I of the project, we introduced three methodologies for transforming humans and robots, and we designed four new role families to achieve "Human-Robot Collaboration." This achievement aligns with the maturity model's concept of "Robot Assisting Human."
For Phase II of the project, we built upon the methodologies developed in Phase I. Our solution optimized the Phase I architecture to create Knowledge-Based, Task-Based, and Intent-Based Closed Loops.
Within the three layers of Autonomous Network architecture, our Phase II project establishes a Knowledge-Based Closed Loop with network AI as the core capability, a Task-Based Closed Loop with network digital twins as a necessary component, and an Intent-Based Closed Loop that spans all three architecture layers. This approach drives Autonomous Networks to adapt to business requirements. We introduced LLM technology to enhance expert robots within the Expert Robot Family, enabling them to reach maturity level 2, "Robots replacing Humans."
C23.0.597 Talent For Tomorrow Phase II Main Slide Deck
C23.0.597 Talent For Tomorrow Phase II Pitch
Be Universe Ahead
Phase I Recap Video
China Unicom Autonomous Networks White Paper 3.0
Email the members of the Catalyst team to request more details.