LILITH
Lilith is a work of research looking for the lost myth of the devouring femininity born during the fellowship that Elena Tilli and Samuel Chan receive at the Akademie fur Theater und digitalität in Dortmund, Germany. During this time they are interested in finding a connection between AI and ML and the process of design in the theater.
Lilith is Adam’s first wife, created by God like him, not for him or after him, but with him. Equals.
“… in their Edenic life, they never had peace together, because´ when Adam wanted to […] lie on her, the woman was offended by the imposed position and replied:“Why should I ever lie under you? I was made of dust too, so I’m just like you.“
Having refused to submit to sexual intercourse, it leaves paradise, becomes a night demon,
and is therefore erased from the Bible.
So who is Lilith? And what could Lilith mean to modern culture and society? How do we present this concept of Lilith, which is probably diverse and controversial, to others?
We propose to use Artificial Intelligence, particularly Deep Learning, to participate in finding Lilith. Many Deep Learning Networks are able to learn the features from a lot of images and recognize the similarities among large datasets. Like we are affected in our understanding by the world and the context that surrounds us, the same happens for those deep learning networks.
The dataset is the world for the AI to understand, therefore it must be carefully created. What would happen if the dataset is provided from marginalized groups and minorities, nonbinary, people of color, transgender, nuns, men, and so on? What if we ask them to provide us a few pictures each in order to build a few datasets, and process these worlds in the same deep learning network?
Once the network is trained it would create something we called the “latent space”, which contains the information and relation of the world the AI sees. These latent spaces often have multi-dimension that human beings could hardly perceive. With the help of a visualizer, we will be able to navigate in the space, but this is still very limited and counter-intuitive. This is why we would like to eventually “physicalize” the latent space into a place where people could wander and navigate with their body and mind, and not with a pointer and a computer mouse.
This project/installation, we hope, could represent and dissect the complexity of sexuality in the modern era. With a carefully curated dataset, we hope that we could also move beyond the mere dichotomy of male and female but towards an understanding of multiplicities.
LILITH
Lilith is a work of research looking for the lost myth of the devouring femininity born during the fellowship that Elena Tilli and Samuel Chan receive at the Akademie fur Theater und digitalität in Dortmund, Germany. During this time they are interested in finding a connection between AI and ML and the process of design in the theater.
Lilith is Adam’s first wife, created by God like him, not for him or after him, but with him. Equals.
“… in their Edenic life, they never had peace together, because´ when Adam wanted to […] lie on her, the woman was offended by the imposed position and replied:“Why should I ever lie under you? I was made of dust too, so I’m just like you.“
Having refused to submit to sexual intercourse, it leaves paradise, becomes a night demon,
and is therefore erased from the Bible.
So who is Lilith? And what could Lilith mean to modern culture and society? How do we present this concept of Lilith, which is probably diverse and controversial, to others?
We propose to use Artificial Intelligence, particularly Deep Learning, to participate in finding Lilith. Many Deep Learning Networks are able to learn the features from a lot of images and recognize the similarities among large datasets. Like we are affected in our understanding by the world and the context that surrounds us, the same happens for those deep learning networks.
The dataset is the world for the AI to understand, therefore it must be carefully created. What would happen if the dataset is provided from marginalized groups and minorities, nonbinary, people of color, transgender, nuns, men, and so on? What if we ask them to provide us a few pictures each in order to build a few datasets, and process these worlds in the same deep learning network?
Once the network is trained it would create something we called the “latent space”, which contains the information and relation of the world the AI sees. These latent spaces often have multi-dimension that human beings could hardly perceive. With the help of a visualizer, we will be able to navigate in the space, but this is still very limited and counter-intuitive. This is why we would like to eventually “physicalize” the latent space into a place where people could wander and navigate with their body and mind, and not with a pointer and a computer mouse.
This project/installation, we hope, could represent and dissect the complexity of sexuality in the modern era. With a carefully curated dataset, we hope that we could also move beyond the mere dichotomy of male and female but towards an understanding of multiplicities.