Refik Anadol

Physical Data Collection—In addition to the open archives of their data partners, the team is venturing to 16 unique rainforest locations, deploying data collection technologies ranging from lidar to photogrammetry, and capturing ambisonic audio and high-resolution visuals of these diverse ecosystems. NVIDIA’s neural network algorithms and tools let them create advanced visualizations and graphics.

AI Research—The LNM’s AI research is built on industry standards and widely accepted diffusion architectures, using tools developed by a wide range of open software communities. Diffusion models in AI generate high-quality images by first adding noise to simple distributions to create a series of increasingly noisy images. Then, a neural network is used to reverse this, systematically removing the noise to reconstruct the original image with clarity.

Building Generative Realities—Large Nature Model: Living Archive is an immersive, multisensory artwork in a growing body of work that’s created using the LNM. It's the longest continuous generative AI visualization of nature to date, offering vibrant AI simulations of the world’s rainforests in a multi-channel sound and video experience that envelopes viewers in the rainforest flora, fauna, and landscapes.

Data Universe - MoMA is a global AI Data Painting simulating a latent walk among the museum’s digitized collection. It combines RAS’s vision of handling data within a universe that it creates for itself with their approach to data visualization’s latent space as a locus for never-ending, self-generating contemplation.

Using NVIDIA StyleGAN2 ADA to capture the machine’s “hallucinations” of MoMA’s vast archive of modern art in a multi-dimensional space, RAS trains a unique AI model with subsets of the collection, creating embeddings in 1024 dimensions. These hallucinations construct new aesthetic images and color combinations through unique lines drawn by algorithmic connections.