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FIRST AI ART IN SPACE
HUMAN CELL ATLAS
/ SPACEX_INTUITIVE MACHINES

SELF-PORTRAIT OF HUMANITY

~Kennedy Space Center
CANNES FILM FESTIVAL Official Selection


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STATEMENT


FIRST AI ART DATA SPATIAL PAINTING IN SPACE BY OUCHHH in collaboration with CERN


Dream Turned Reality: Ouchhh Studio's Milestone in Space with "HUMAN CELL ATLAS_Neuroorganismic AI Data Spatial Painting of Humanity" 

This masterpiece embarked on a celestial journey aboard the pioneering Nova-C lander named “Odysseus,” carried by a SpaceX Falcon 9 rocket from NASA's Kennedy Space Center at 1:05 AM ET, February 15th. This mission, executed by Intuitive Machines, aims to mark the first American spacecraft touchdown on the Moon’s surface since the Apollo 17 mission in 1972.

We are beyond thrilled to announce a monumental achievement that has been a dream of ours since childhood. Ouchhh Studio has officially become the first studio to exhibit an Artificial Intelligence data painting art piece in space, marking a historic milestone in the history of New Media Art.

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STATEMENT


Can we create an artistic self-portrait of humanity with AI?

Introducing "HUMAN CELL ATLAS" - our Artificial Neuroorganismic AI Data Spatial Painting of humanity. This isn't just art; it's a poetic tale, an artistic self-portrait of humanity, sketched not with brushes but with lines of code and torrents of data. 

DATA JOURNEY of 37.2 TRILLION CELLS
Our canvas? The ambitious Human Cell Atlas Project. 🌍🔬 A global alliance of the brightest minds, from biologists to mathematicians, all united with a dream - mapping every cell in the human body to unlock secrets that could redefine our understanding of health and disease.

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STATEMENT


Our artistic odyssey harnessed the vastness of The Human Cell Atlas Project, leveraging cutting-edge tools like single-cell genomics, Auto Encoders, PCA analysis, and the tSNE algorithm to manifest a masterpiece that transcends dimensions.

At Ouchhh, we're painting a new chapter in the history of art and science, proving that the power of AI and human creativity knows no bounds. This venture into space is not just an exhibition; it's a statement about the endless possibilities of human creativity and the innovative spirit that drives us forward.


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firstaiartinspace.com


>SCIENTIFIC AI DATA PAINTING JOURNEY


The Human Cell Atlas Project is a project that aims to create a broad map of all human cells that cooperates with the studies of a lot of international scientists with wide expertise. In order for us to create artistic visualizations from the data collected from different studies, we used single-cell RNA-seq data from different tissues. RNA-seq is a novel technique for gathering more detailed information from the genome by quantitatively analyzing the RNA molecules in a sample. To make the analysis on the data we first preprocess and normalized the scRNA-seq data. After these processes, we had a dataset that belongs to a hundred-dimensionals universe.
So, in order to visualize, and ultimately create a baseline for artistic expression, we deployed Auto Encoders and PCA analysis to make the data visible to the human eye. Auto Encoders is a machine learning technique that deals with representing higher dimensional data in lower dimensions. After reducing the dimension of the data to three dimensions we used tSNE algorithm to visualize hidden clusters in the data.










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>SCIENTIFIC AI DATA PAINTING JOURNEY

The Human Cell Atlas Project is a project that aims to create a broad map of all human cells that cooperates with the studies of a lot of international scientists with wide expertise. In order for us to create artistic visualizations from the data collected from different studies, we used single-cell RNA-seq data from different tissues. RNA-seq is a novel technique for gathering more detailed information from the genome by quantitatively analyzing the RNA molecules in a sample. To make the analysis on the data we first preprocess and normalized the scRNA-seq data. After these processes, we had a dataset that belongs to a hundred-dimensionals universe.
So, in order to visualize, and ultimately create a baseline for artistic expression, we deployed Auto Encoders and PCA analysis to make the data visible to the human eye. Auto Encoders is a machine learning technique that deals with representing higher dimensional data in lower dimensions. After reducing the dimension of the data to three dimensions we used tSNE algorithm to visualize hidden clusters in the data.





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