就像人工智能生成的艺术作品经常发生的那样，关于归属应该交给生成人工智能提示的人、人工智能本身、人工智能的创造者，还是机器学习模型“借鉴”的艺术作品，人们感到困惑。就本周六现代艺术博物馆(Museum of Modern Art)的最新展览而言，你可以把它送给前三名。最后一部分有点模糊。
MoMA将于本周末揭幕这个名为“Refik Anadol:无人监督”的24 × 24英尺的巨型项目，展览将持续到2023年3月5日。这件艺术品使用了阿纳多自己设计的人工智能模型，并使用了MoMA收藏的18万件艺术品的38万张图像，创造了一个笨拙而汹涌的移动图像流。根据博物馆发布的消息，展出的新作品是“对技术、创造力和现代艺术的独特而前所未有的思考”，重点是“重新想象现代艺术的轨迹，向其历史致敬，并梦想其未来”。
Anadol最初于2021年在Feral File平台上以数字形式发布了《无监督》，这是他于2016年开始的《机器幻觉》系列的一部分。根据Feral File上的项目描述，Anadol使用了几种不同类型的生成对抗网络(GAN)算法，从“公共可用资源”中创建生成艺术作品。然后，这些图像被(唉)作为nft出售(这也是MoMA最近正在调查的事情)。据《快公司》杂志采访阿纳多时透露，为机器幻觉提供动力的人工智能团队也使用英伟达DGX Station A100进行训练，这是一种台式机大小的盒子，用于“人工智能超级计算”。
与首次在线展览不同的是，MoMA表示，现场展览还会监测光线、运动、周围环境的体积变化，甚至是对运动图像有影响的天气。
在给Gizmodo的一封电子邮件中，MoMA的一位发言人证实，自2021年初以来，这位艺术家一直在与MoMA合作，当时最初的无监督艺术作品还没有在网上发布。这项工作直接从MoMA的公开GitHub元数据中提取。
这种GAN图像生成不同于用于驱动最现代AI艺术生成器的扩散模型，包括Stable diffusion和OpenAI的DALL-E 2。虽然两者都使用一种高斯模糊来扭曲然后重建图像，但扩散是一个迭代过程，通过使用机器学习系统来尝试生成“逼真”的视觉图像。另一方面，GANs更多地基于“对抗性”系统，该系统创建“可信数据”，然后使用“鉴别器”来决定图像的那一部分是否属于该系统。扩散模型通常基于相似的标签聚类图像，而Anadol的GAN模型让人工智能“无监督”地生成自己的图像。
MoMA的策展人米歇尔·郭(Michelle Kuo)是这次展览的组织者之一，她在发布会上说:“通常情况下，人工智能被用于分类、处理和生成世界的现实再现。相比之下，阿纳多的作品富有远见。它探索了梦境、幻觉和非理性，提出了对现代艺术和艺术创作本身的另一种理解。”
在接受《快公司》(Fast Company)采访时，阿纳多表示，从本质上讲，这种人工智能图像生成器正在成为“自己的实体”，并补充说，“我们不知道它能创造出什么样的形式。
事实上，它没有使用最引人注目的图像生成方式，这可能对这个新的人工智能艺术装置有利。虽然在2021年，知道人工智能艺术的人要少得多，但在2022年，人工智能艺术创作领域的大腕儿却充满了争议，其中大部分批评来自传统艺术家。这些系统在未经允许的情况下从互联网上收集了数百万张图像，用于训练人工智能模型。艺术家们经常发现他们的艺术风格被人工智能图像生成器所采用，这导致人们担心他们的作品可能会与那些简单地输入提示(如“毕加索风格的艺术”)的人难以区分。
还有一个棘手的版权问题，一个人是否可以声称自己拥有使用人工智能系统创作的艺术作品，而人工智能系统本身已经从其他受版权保护的作品中生成了图像。
就像人工智能生成的艺术作品经常发生的那样，关于归属应该交给生成人工智能提示的人、人工智能本身、人工智能的创造者，还是机器学习模型“借鉴”的艺术作品，人们感到困惑。就本周六现代艺术博物馆(Museum of Modern Art)的最新展览而言，你可以把它送给前三名。最后一部分有点模糊。
MoMA高级策展人保拉·安东内利(Paola Antonelli)表示，新展览“强调了它对艺术家们的支持，他们尝试用新技术作为工具，扩大他们的词汇量、影响力，以及他们帮助社会理解和管理变化的能力。”
原文：
As it often happens with AI-generated art, there’s confusion surrounding whether attribution should be handed to the person who generated the AI’s prompt, the AI itself, the AI’s creators, or the artwork the machine learning model “borrowed” from. In the case of the Museum of Modern Art’s latest exhibition on display this Saturday, you could give it to the first three. The last part is a little murky.
MoMA is set to unveil the colossal 24 by 24-foot project called Refik Anadol: Unsupervised this weekend, with the exhibit to run through March 5, 2023. The artwork uses an artificial intelligence model designed by Anadol himself and uses 380,000 images of 180,000 art pieces from MoMA’s collection to create a bumbling and roiling stream of moving images. According to a museum release, the new work on display is “a singular and unprecedented meditation on technology, creativity, and modern art” which is focused on “reimagining the trajectory of modern art, paying homage to its history, and dreaming about its future.”
Anadol originally digitally published Unsupervised back in 2021 on the platform Feral File, as part of his Machine Hallucinations series that he started in 2016. According to the project description on Feral File, Anadol has used several different kinds of generative adversarial network (GAN) algorithms to create the generative artwork from “publicly available resources.” Those images were then sold as (sigh) NFTs (which is also something MoMA has been investigating recently). According to Fast Company, who spoke to Anadol, the team that worked on the AI that powers Machine Hallucination also trained using an Nvidia DGX Station A100, a desktop-sized box used for “AI Supercomputing.”
Different from the art’s first display online, MoMA said the in-person exhibit also monitors changes in light, movement, volume of the surroundings, and even the weather which has an impact on the moving image.
In an email with Gizmodo, a MoMA spokesperson confirmed that the artist had been working with MoMA since early 2021, before the original Unsupervised art went up online. The work draws directly from MoMA’s publicly available GitHub metadata.
This kind of GAN image generation is different from diffusion models used to power the most modern AI art generators, including Stable Diffusion and OpenAI’s DALL-E 2. While both use a kind of gaussian blur to distort and then reconstruct images, Diffusion is an iterative process that works by using machine learning systems to attempt to generate “realistic” visual images. GANs, on the other hand, are more based on an “adversarial” system that creates “plausible data” then uses a “discriminator” to decide whether that part of the image belongs. Whereas Diffusion models often cluster images based on similar tags, Anadol’s GAN model let the AI generate its own images “unsupervised.”
Michelle Kuo, a curator at MoMA who was a leader in organizing the exhibit, said in the release that “Often, AI is used to classify, process, and generate realistic representations of the world. Anadol’s work, by contrast, is visionary. It explores dreams, hallucination, and irrationality, posing an alternate understanding of modern art—and of artmaking itself.”
In an interview with Fast Company, Anadol said that, in essence, this kind of AI image generator was becoming “its own entity,” adding, “we don’t know what kind of forms it can create.
The fact that it’s not using the most high-profile kind of image generation may be to this new AI art installation’s benefit. While there were far fewer people aware of AI art in 2021, in 2022 the biggest names in AI art generators have been swarmed with controversy, with much of the blowback coming from traditional artists. These systems have scraped up millions upon millions of images from the internet without permission, which are used to train the AI models. Artists often find their art styles have been coopted by AI image generators, leading to fears their body of work could become indistinguishable from folks who simply type prompts such as: “art in the style of Pablo Picasso.”
There’s also the sticky question of copyright, and whether an individual could ever claim to own art that was created using an AI system that itself had generated images from other copyrighted work.
MoMA’s senior curator Paola Antonelli said the new exhibit “underscores its support of artists experimenting with new technologies as tools to expand their vocabulary, their impact, and their ability to help society understand and manage change.”
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