Resonant Space of Superintelligence

About the art of perception and the vision of artificial superintelligence

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Human-AI Design & the Vision of Peaceful Co-evolution

What is ƒon.space?

An artistic and interdisciplinary research project that explores the complex relationships between dynamic systems. It aspires to merge artistic excellence with artificial intelligence to create new perspectives on global challenges.

Why this?

In a world of increasing complexity, it is evident that the current structures of political self-organization are struggling to meet the needs and security of diverse social groups.

ƒon.space is working on the vision of a distributed superintelligence – not only between humans and AI, but also between humans – to create peaceful future scenarios.

#ResonanteSuperintelligenz
#Re-integrierteSingularität
#Human-AI-Design

How can the simultaneity of the world be grasped?

Analysing scientific findings on the emergence of individual and collective imagination

Consideration of the fundamental processes as a resonance or interaction system of the natural phenomena of emergence and entropy

Development of a human-machine design for a safe integrated singularity

ƒon.space is an extended work of art?

500-page manuscript for an artist’s book (support the production!)
Original painting
Vision of a distributed superintelligence
Interaction with the reader’s imagination

By combining art, science, technology and imagination, the project opens up new ways of tackling global challenges and realising the vision of a peaceful future of collective intelligence.

# Initialize the system
initialize_world_model()
initialize_human_gan()

# Continuous data collection and analysis
while True:

# Collect sensor and environmental data
environment_data = collect_environment_data()

# Citizen participation and data collection
citizen_data = collect_citizen_data()

# Update the world model
update_world_model(environment_data, citizen_data)

# Determine the current entropy in the system
entropy = calculate_entropy(world_model)

# Adjust the entropy level if necessary
if entropy > upper_entropy_limit:
reduce_entropy(world_model)
elif entropy = lower_entropy_limit:
increase_entropy(world_model)

# Human-GAN: Generate new ideas and solutions
new_ideas = human_gan_generator(world_model)
new_ideas = human_gan_discriminator(new_ideas)

# Integrate the new ideas into the world model
integrate_ideas(world_model, new_ideas)

# Promote emergent properties
promote_emergence(world_model)

# Visualize the current world model
visualize_world_model()

# Collect feedback for improvement
feedback = collect_feedback()
improve_model(world_model, feedback)

wait until the next loop

Become part of this fascinating journey! Support the production of the artist’s book, purchase a part of the original painting or virtual shares and contribute to the development and exploration of a peaceful superintelligence.

INTRODUCTION

CONTENTS

SUPPORT