This workshop given by Robert B. Lisek uses randomness and artificial intelligence methods for creation of sound, visuals, performance, installation, interactive media, physical computing, and networking.
This is practical course with the use of Supercollider, Pure data/Max Msp, Fluxus, Python, Lisp and hacking analogue devices for detection, creation and amplification of noise. We observe the success of artificial neural networks in simulating human performance on a number of tasks: such as image recognition, natural language processing, etc. However, there are limits to state-of-the-art AI that separate it from human-like intelligence. Today’s AI algorithms are limited in how much previous knowledge they are able to keep through each new training phase and how much they can reuse. We must focus on self-improvement techniques e.g. reinforcement learning and integrate it with deep learning, recurrent networks, and so on.
The workshop consists of:
- Work with three main types of learning algorithms: Deep Learning, Reinforcement Learning, Recurrent Neural Networks, Genetic Algorithms, supervised and unsupervised learning, data sampling, backpropagation, explorations of environment, generalization, experimentation, markov models and processes (speech recognition), support vector machines (image recognition).
- Practical application of different types of random generators for constructing visual works, music compositions (random generators, random walks, monte carlo, etc), dealing with large systems of events: probability distributions (average, spread, deviation).
- Extraction of randomness from a physical processes through hacking analogue devices for detection, amplification, sonic and visual analysis (electromagnetic fields, gas particles, photons and decay of radioactive materials)
- Applications RNN and DL in building of new prototypes, artworks and network app
Robert B. Lisek is an artist, mathematician and composer who focuses on systems, networks and processes (computational, biological, social). He is involved in a number of projects focused on media art, storytelling and interactive art. Drawing upon post-conceptual art, software art and meta-media, his work intentionally defies categorization. Lisek is a pioneer of art based on Artificial Intelligence and Machine Learning. Lisek is also a composer of contemporary music, author of many projects and scores on the intersection of spectral, stochastic, concret music, musica futurista and noise. Lisek is also a scientist who conducts research in the area of foundations of science (mathematics and computer science). His research interests are category theory and high-order algebra in relation to artificial general intelligence.
Please register at: firstname.lastname@example.org
Entry: 10 €
The workshop takes part within the international cooperation project Re-Imagine Europe, supported by the European Commission from the Creative Europe program and Slovak Arts Council.