Interdisciplinary Conference

TABOO - TRANSGRESSION - TRANSCENDENCE

in Art & Science

26-28 November 2020, University of Applied Arts Vienna/Online

TTT2025 Call for Paper Submissions are open until 31/12/2024 3:00 pm EET
138. SIBYL
Session: Session "ORF6 / Tutelage"
Speakers: Robert Lisek

SIBYL is Artificial Intelligence that proposes new stories and generates new compositions. SIBYL is trained by techniques of composing by Pynchon, Burroughs, Gibson and Xenakis. The project offers an innovative fusion between four domains: storytelling, games design, experimental music and artificial intelligence. The project creates and tests new methods of generating music, stories and new types of audio-visual performance through interactions with autonomous AI agent. SIBYL is presented as performance and interactive installation that uses recurrent neural networks, reinforcement learning and analog sound-video synthesizers.

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, 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. In practice this means that it is necessary to build and adjust new algorithms to every new particular task. Processes such as intuition, emotions, planning, thinking and abstraction are a part of processes, which occur in the human brain. A generalization in AI means that system can generate new compositions or find solutions for new tasks that are not present in the training corpus. "General" means that one AI program realizes number of different tasks and the same code can be use in many applications. We must focus on self-improvement techniques e.g. reinforcement learning and integrate it with deep learning, recurrent neural networks, reinforced random walks.


Robert Lisek
Back

Hosting Institutions

angewandte   inarts
Text To SpeechText To Speech Text ReadabilityText Readability Color ContrastColor Contrast
Accessibility Options