Description

Our project aims to provoke a reflection on the relationship between humans and AI by exploring the potential of algorithms to predict the future. In an era where we increasingly rely on Artificial Intelligence to make decisions and forecasting, our present is reduced to mere data points, accurately processed to construct highly plausible future scenarios. But is this truly reality? The Life of Chuck challenges this reality through an immersive art installation where the user engages in dialogue with an AI chatbot. During this interaction, the algorithm analyzes the user's personality and generates a prediction of their future. To make it possible, we developed a system displaying immersive scenarios of the user's future. The user interacts in real-time, watching themselves age across decades. This visualization is paired with a musical score designed to heighten the emotional impact of the experience.

Challenges, accomplishment and lessons learned

The initial objective was to use both technological and sensory infrastructures to close the gap between conceptual imagination and reality. We had to achieve the best balance between what we wanted to accomplish and what was practical because this imaginative space frequently collided with technical limitations. One of the biggest challenges after choosing the best tools was developing the project simultaneously in several software environments while maintaining communication between them. Execution isn't the only consideration in a generative and interactive installation like "the Life of Chuck"; controlling latency within applications and across communications was essential for an improved user experience. Additionally, the high processing power needed by certain algorithms denoted a clear dependency on large-scale servers and external providers.

Technology

Software: touchdesigner, supercollider, python
Library: google-genai, mediapipe,opencv-python, python-osc, essentia-tensorflow, websockets, numpy
Packages/libraries touchdesigner: StreamDiffusionTD, FaceMesh, td_pip, mediapipe, numpy, sounddevice, absl-py, cffi, flatbuffers, pycparser

Media