Refik Anadol’s AI Data Paintings and Sculptures translate the logic of new media technology into spatial design to create immersive experiences based on vast datasets of nature, history, and human activity.
2024
Refik Anadol Studio is pioneering a groundbreaking project—the Large Nature Model (LNM). This is a unique open-source, generative AI model focused on nature, using the largest ethically sourced dataset of natural elements. This multi-modal LNM will be able to understand and generate content across multiple forms of media, such as text, images, audio, and video.
2024
Refik Anadol Studio's interactive AI research focuses on producing generative realities through real-time rendering, scent, and sensory inputs. In this project, fully interactive generative 3-D worlds are envisioned by AI but realized by 3D artists. The interactive component lets the audience navigate through millions of raw datasets from the Large Natural Model and discover how machines categorize bird sounds or images from nature. As they travel through these immersive worlds, the viewers can also verbally or textually interact with an AI-driven character that uses custom LLM models.
Generative Reality—LNM: Fauna
Machine Hallucinations—LNM: Fauna
Generative Reality—LNM: Flora
Machine Hallucinations—LNM: Flora
Generative Reality—LNM: Landscapes
Machine Hallucinations—LNM: Landscapes
Data Collection Partnerships—For the Large Nature Model, Refik Anadol Studio collects as much data as they can on the flora, fauna, and fungi of the world’s rainforests. They enhance the breadth of this nature-focused AI research by working with some of the world’s leading organizations, including The Smithsonian Institution, London’s Natural History Museum, and National Geographic, among others.
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.
Generative AI Video Research—This research integrates the aesthetic principles of the Studio’s multi-year project, Machine Hallucinations, with innovative AI techniques crafted for the LNM’s latest outputs. It showcases a fine-tuned diffusion model for video generation, which draws upon previous fluid simulation videos from Machine Hallucinations. This enhanced model transforms realistic AI video outputs to align with the distinct fluid simulation visuals characteristic of the Refik Anadol Studio.
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.
Audio Classification—Using a subset of thousands of recordings from Cornell University's Macaulay Library—particularly of Amazonian birds—Anadol and his team use cutting-edge pre-trained audio neural networks for audio tagging. A new audio is generated using a custom audio latent diffusion model trained on a broad spectrum of unlabeled audio, enabling the replication of complex sounds. The power of the Studio's model is its capability to produce realistic and immersive rainforest soundscapes.
Series of Artworks from Machine Hallucinations—MoMA Dreams
2021-2022
Generative Study I
AI Data Paintings
Anadol and his team created a unique exhibition of AI data paintings by training an AI model with the public metadata of The Museum of Modern Art’s collection spanning more than 200 years of art. Generative Study is from a series of algorithmic AI data paintings showcasing Anadol’s collaboration with GAN algorithms at the intersection of technology and aesthetics. Each frame in the series displays a cluster of chosen “latent space sequences,” as the artist goes through serendipitous allusions to modern visual expressions in the machine-mind.
Machine Hallucinations—MoMA Dreams
2021-2022
Machine Hallucinations is a multi-year research project from Refik Anadol Studio (RAS) that investigates data aesthetics based on collective visual memories of humanity. Machine Hallucinations - MoMA expands on this vision by processing 138,151 pieces of metadata from the entire MoMA archives in the mind of a machine.
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.
For MoMA - Fluid Dreams, Refik Anadol Studio’s signature fluid dynamics algorithm infinitely dreams about the MoMA archive. RAS synthesizes the vast data collected from MoMA archives into ethereal data pigments, and eventually into a representational form of fluid-inspired movements with the help of custom software and generative algorithms.
Refik Anadol (b. 1985, Istanbul, Turkey) is an internationally renowned media artist, director, and pioneer in the aesthetics of data and machine intelligence. He’s the Director of Refik Anadol Studio in Los Angeles and teaches at UCLA’s Department of Design Media Arts. Anadol’s work locates creativity at the intersection of humans and machines. Taking the data that surrounds us as primary material and the neural network of a computerized mind as a collaborator, Anadol offers us radical visualizations of our digitized memories and expands the possibilities of interdisciplinary arts. Anadol’s site-specific data paintings and sculptures, live audio/visual performances, and immersive installations take many forms, while encouraging us to rethink our engagement with the physical world, collective experiences, public art, decentralized networks, and the creative potential of AI.
Alex Morozov, Alistair Ramage, Caio Villela, Christian Burke, Cosku Turhan, Daniel Seungmin Lee, Dasha Orlova, Delaney Kough, Dogukan Yesilcimen, Efe Mert Kaya, Efsun Erkilic, Ho Man Leung, Hye Min Cho, Jules Hyun, Kelian Maissen, Kerim Karaoglu, Kyle McLean, Laura Cohen, Linda Berke, Maurizio Braggiotti, Mert Cobanov, Michael Hsiu, Nidhi Parsana, Pelin Kivrak, Sebastian Monroy, Simon Burke, Tobias Heinemann, Xi Wang, and Yufan Xie
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Refik Anadol and members of his studio discuss with NVIDIA’s Brian Dowdy how their unique AI workflow, as well as NVIDIA GPUs, SDKs, and state-of-the-art AI models, help use their work to make a positive impact on the world.
Join multimedia artist and director, Refik Anadol, and Museum of Modern Art curators, Michelle Kuo and Paola Antonelli, to explore the evolution of technology in the making of modern art.
Refik Anadol Studio (RAS) embarks upon a new journey to explore the architecture of the human brain by combining advanced neuroimaging techniques with cutting-edge AI and multi-modal data visualization tools.
Go behind the scenes with one of our amazing AI Art Gallery artists for a virtual tour of their innovative studios, and learn how AI has helped shape their creative process.
