Empathetic Virtual Agents For Customer Service
Pilot #1
About this Pilot
Discover the future of smart home technology with our cutting-edge pilot project. Led by TID and in collaboration with esteemed partners, we are pioneering a privacy-preserving, decentralized Federated Learning framework to develop personalized, high-performance language models. This innovative approach ensures your data remains secure while enhancing the functionality of Telefónica’s leading products and services, from cognitive personal assistants to smart home management systems.
Harnessing the power of Federated Learning (FL), this pilot ensures that deep-learning models are trained in a decentralized, privacy-preserving manner, keeping data secure on local devices. TID will deploy and evaluate hierarchical FL models across diverse environments, from edge devices to telco infrastructures. This innovative approach allows Telefónica and its partners to create high-performance, personalized language models without compromising data privacy. These models will enhance a range of Telefónica services, including AURA personal assistants, Movistar TV recommendations, and smart home management systems.
Main Challenges
To successfully implement this pilot, we need to address several key challenges that will drive the innovation and efficiency of our privacy-preserving language model learning framework:
Personalization
Enable continuous learning from user preferences, specific lexicon, and life routines through unsupervised algorithms, incorporating iterative design methodologies and user participation.
Privacy
Ensure privacy in residential spaces by keeping private data within the home and only sharing models for global aggregation using FL.
Global Knowledge
Maintain global knowledge through model transfer techniques to address the cold-start problem and enable faster incorporation of advanced language models across Telefónica applications.
the safari park
Safari & Adventure Park
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