TETRA General World Models

The rapid emergence of General World Models (GWMs) marks a transformative shift for the audiovisual industry, offering the power to generate video and 3D environments in seconds.

We are proud to be part of this project, which aims to cut through the current complexity and provide teams with practical, clear guidance for this new landscape.

Our participation focuses on two specific research lines:

1. Adaptive Realities: Personalizing a VR Emotion Regulation Application

This research line explores the intersection of eXtended Reality (XR) and biometric data to create mental health interventions that respond to the user in real-time.

The Goal: To develop a VR environment that can "sense" a user's emotional state and adjust its content to help them regulate those emotions.

The Technology: By using Machine Learning (ML) to analyze multimodal data - such as eye tracking, heart rate, or skin conductance (GSR) - the system identifies signs of stress or anxiety.

2. AI & Personalized Feedback: Adaptive Virtual Tutors in Real-Time

This use case focuses on the evolution of AI avatars from simple chatbots into socially interactive mentors within virtual spaces.

The Goal: To create virtual tutors that don't just provide information but adapt their teaching style and feedback based on the learner's immediate performance and engagement levels.

The Technology: These tutors leverage socially interactive AI and real-time data processing to provide personalized guidance. Instead of a one-size-fits-all script, the tutor can explain concepts in different ways or offer encouragement when it detects the user is struggling.

Instead of adding to the hype, we are investigating the real-world impact of GWMs on creative workflows, infrastructure, and ethics. Through hands-on experiments and custom workflows, we help companies understand when it makes sense to integrate AI and how to do so with data responsibility and confidence.