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仍在寻找(不)稳定平衡:可视化无数据训练生成神经网络的过程

Still searching for an (un)stable equilibrium: visualising the process of training generative neural networks without data

Terence Broad

arXiv 2609.13172首次发表:更新:

发表机构

Creative Computing Institute, University of the Arts London(伦敦艺术大学创意计算研究所)

机构由 AI 辅助整理,请以论文原文为准。

AI 中文总结

本文介绍(不)稳定平衡系列第二组作品,通过视频可视化无数据训练生成神经网络的过程,以审美体验引导观众理解AI,作为AI可解释性的批判性艺术实践。

AI 中文摘要

(不)稳定平衡是一个持续进行的系列作品,其基础是一种无数据训练生成神经网络的实践。本文介绍了(不)稳定平衡系列的第二组作品,其中无数据训练的过程被可视化为一组视频片段。这些作品展示了一个生成网络试图收敛到一个未定义的固定点,陷入一场无尽且无法解决的平衡追寻。本文所述的视频片段引导观众通过审美体验而非技术阐述来理解人工智能,并力求给出对人工智能可能是什么的概念性理解,而非对当前现状的复述。该项目隶属于更广泛的艺术实践集合,这些实践作为人工智能可解释性的替代性和批判性模式。

英文摘要

(un)stable equilibrium is an ongoing series of works that is based on a practice of training generative neural networks without data. This paper introduces the second series of (un)stable equilibrium works, in which the process of training without data is visualised in a series of video pieces. These works show a generative network attempting to converge to a fixed point that is undefined, caught in an endless, unresolvable search for equilibrium. The video pieces described in this paper guide the viewer toward an understanding of AI through aesthetic experience rather than technical exposition, and strive to give a conceptual understanding of what AI could be, rather than a restatement of what it currently is. This project sits within a broader set of artistic practices that serve as an alternative and critical modes of explainability for AI.

CommentsIn Proceedings of Explainable AI for the Arts Workshop 2026 (XAIxArts 2026) arXiv:2607.20131

论文原文

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