Federated AI lets a team imagine together: Federated Learning of GANs

TL;DR

This paper introduces Federated AI Imagination, a novel collaborative AI paradigm that uses federated learning and GANs to enable geographically distributed teams to jointly generate and envision ideas.

Contribution

It proposes a new AI framework combining federated learning with GANs to facilitate collaborative imagination among distributed teams.

Findings

Conceptual framework for federated collaborative imagination

Potential for enhanced creative teamwork across distances

Foundation for future implementation and testing

Abstract

Envisioning a new imaginative idea together is a popular human need. Imagining together as a team can often lead to breakthrough ideas, but the collaboration effort can also be challenging, especially when the team members are separated by time and space. What if there is a AI that can assist the team to collaboratively envision new ideas?. Is it possible to develop a working model of such an AI? This paper aims to design such an intelligence. This paper proposes a approach to design a creative and collaborative intelligence by employing a form of distributed machine learning approach called Federated Learning along with fusion on Generative Adversarial Networks, GAN. This collaborative creative AI presents a new paradigm in AI, one that lets a team of two or more to come together to imagine and envision ideas that synergies well with interests of all members of the team. In short, this paper explores the design of a novel type of AI paradigm, called Federated AI Imagination, one that lets geographically distributed teams to collaboratively imagine.