解剖智能:实时编码作为表演性解剖

IF 0.2 3区 艺术学 0 MUSIC
Joana Chicau, Jonathan Reus
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引用次数: 0

摘要

本文描述了通过艺术研究项目Anatomies of Intelligence开发的“解剖”实时编码方法。在这项工作中,我们研究了如何使用实时编码作为对数据语料库进行表演性探索的方法,以及在该语料库上运行的机器学习算法。该项目的艺术框架将启蒙运动早期的解剖学认识论与当代机器学习相碰撞,为新颖、具体的艺术方法的出现创造了肥沃的空间。我们让观众沉浸在一种身临其境的现场编码体验中,图像和声音由我们的解剖方法驱动,揭示了在艺术家制作的数据集上实时运行的机器学习算法的潜在节奏和结构。为了支持这些表演,我们开发了一款基于浏览器的定制软件,即网络剧院,用于现场/在线视听表演。在这篇文章中,我们描述了这项工作,并反思了我们作为表演者和观众反馈的经验,这表明我们基于检查“现成”算法的现场编码解剖方法,为机器学习和数据库提供了一种独特的体验入口。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Anatomical Intelligence: Live coding as performative dissection
This article describes the method of ‘dissective’ live coding, as developed through the artistic-research project Anatomies of Intelligence. In this work we investigate how live coding can be used as an approach for performative explorations of a data corpus and a machine learning algorithm operating on this corpus. The artistic framework of this project collides early Enlightenment-era anatomical epistemologies with contemporary machine learning, creating a fertile space for novel, embodied artistic methods to emerge. We engage audiences in an immersive, live-coded experience where image and sound are driven by our dissective approach, revealing the underlying rhythms and structures of a machine learning algorithm running live on an artist-made dataset. To support these performances we have developed a custom browser-based software, the Networked Theatre, used for both hybrid in-person/online audiovisual performances. In this article we describe this work and reflect on our experience as performers and audience feedback, which suggests that our dissective method of live coding, based on examining ‘ready-made’ algorithms, offers a unique experiential entryway into the bodies of machine learning and data corpi.
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来源期刊
CiteScore
1.20
自引率
16.70%
发文量
38
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