+FO Artificial Intelligence – Creative Practices and Critical Perspectives
Intro Day: Thomas Knüsel
September 4
9:15 ~ 12:00 / 13:00 ~17:00
Physically @ MediaDock
After a short introduction to familiarize you with the Terms Artificial Intelligence, MachineLearning, Datasets, Training ect. We will dive into the first Experiment, we will gather a tiny Dataset to teach a Camera to detect a specific Object.
Artist Talk: Anna Ridler
17:30 ~ 18:30
Online
Anna Ridler (born 1985) is an artist and researcher who lives and works in London. She works with collections of information or data, particularly self-generated data sets, to create new and unusual narratives in a variety of mediums.
A core element of Ridler’s work lies in the creation of handmade data sets through a laborious process of selecting and classifying images and text. By creating her own data sets, Ridler is able to uncover and expose underlying themes and concepts while also inverting the usual process of scraping pre-classified images found in large databases on the internet. Her interests are in drawing, machine learning, data collection, storytelling, and technology.
External Links:
1st Workshop: Nicolas Malevé
September 5 + 6
9:15 ~ 12:00 / 13:00 ~17:00
Physically @ MediaDock
In Nicolas Malevé’s workshop we will examine large collections of photographs. We will focus on where such image collections come from, how they are assembled, how they enable machines to see and how they can become research objects or material for machine processing. We will explore in self-experiments what it means to look at huge amounts of images and to see them at high speed. We will deepen our understanding of the importance of images in today’s media world and what special role photographs play in the development of machine vision. We will learn what kind of vision and what speed of seeing correspond to the model generated by algorithms. On this basis, we will be able to ask new questions about the development of technology and how it can become a key component of our visual practices as artists and citizens.
2nd Workshop: Guillaume Massol
September 7 + 8
9:15 ~ 12:00 / 13:00 ~17:00
Physically@MediaDock
In the second workshop we will familiarise ourselves with how machine learning works in practice. After a short introduction, you will have the opportunity to try out different ML models and their different applications with an AI toolkit. Once you are familiar with the tools, you will start to work out your own individual machine learning experiments.
External Links:
https://blog.massol.me/author/guillaume/
https://github.com/gu-ma
3rd Workshop: Fabian Offert
September 11 + 12
9:15 ~ 12:00 / 13:00 ~17:00
Physically@MediaDock
In this workshop, we will attempt a deep-dive into the current state of (visual) artificial intelligence. Working only in the browser we will pick up the programming basics required to run arbitrary machine learning models, including CLIP (a multimodal model that allows us to classify images by content) and Stable Diffusion (a multimodal model that allows us to generate arbitrary images from text prompts). We will explore some of the creative and analytical applications of both models and discuss their biases and limitations. Participants are encouraged to «bring their own data», i.e. think in advance about a dataset of images they would like to work on.
External Link:
Selfstudy Time:
September 13 + 14
Presentation Day
September 15
10:00 ~ 12:00Open Studios
12:00 ~14:00
Passende Tools
Passende Recipies
