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機器會夢見 NFT 嗎？ ─ 台灣首檔加密藝術收藏展

機器會夢見 NFT 嗎？ ─ 台灣首檔加密藝術收藏展

VolumeDAO

機器會夢見NFT嗎？這個問題交給步入展間的您

機器會夢見 NFT 嗎？ ─ 台灣首檔加密藝術收藏展

VolumeDAO

機器會夢見NFT嗎？這個問題交給步入展間的您

전시 소개

전시명

機器會夢見 NFT 嗎？ ─ 台灣首檔加密藝術收藏展 - Do Machines Dream of NFT? ─ A Crypto Art Collection on Tezos

전시 기간

2022-03-26 ~ 2022-03-27

장소

濕地 venue B1

주소

104 臺北市中山區林森北路 107 巷 10 號

藝術GAN什麼？ ──《機器會夢見NFT嗎？》展序 自伊恩‧古德菲婁（Ian Goodfellow）2014年提出「生成對抗網路」（Generative Adversarial Network，簡稱GAN）起，這項技術已經在遊戲設計、天文研究和廣告影像等領域獲得眾多目光，視覺藝術也不例外。 生成對抗網路屬於「機器學習」（Machine Learning）中的「深度學習」（Deep Learning）。機器學習是人工智慧（Artificial Intelligence）的根本課題，著重模擬神經網路，試圖辨識、產出和精進資訊。在「生成對抗網路」這個冗長的名詞中，「對抗」是最大特點：設立「生成器」（generator）和「辨識器」（discriminator）的雙重機制，讓它們相互抗拮，共同成長。 首先，生成器自資訊的「潛藏空間」（latent space）中獲取素材，編造幾可亂真的成品；其次，辨識器根據現實中的本真對象或資料庫標的，指認生成器編造資訊之真偽。若為真，則通過檢驗，資訊確立；若為假，則再次生成，直到「瞞天過海」。我們不妨將它們的關係比作偽鈔製作者和刑事局或贗畫家和檢驗者，就算不以真偽二分，兩者的互動亦可被想成藝術家和藝評家，資訊或作品的方方面面得以更加完善。 把上述邏輯和技術應用在視覺藝術，觀者不只見到寫實卻不存在的人事物，還能欣賞生產和校正的往返歷程。我們再次玩味「觀看的方式」：判斷真與假，捕捉變與常，想像萬物之間的連結及其外觀互換的可能。此外，若機器能夠繪畫，它們「想到」和「看到」的又是什麼？這麼問或許太誇張，畢竟這一切不仍是人類的創作嗎？諸多爭議或許正是重解人機關係的契機。 「生成對抗網路」剛起步時，「非同質化代幣」（Non-Fungible Token，即NFT）的技術尚未出現。如今，隨著區塊鏈和加密貨幣的普及，越來越多藝術家以「生成對抗網路」創作，並將作品鑄成NFT。本展選品多半出自泰卓鏈（Tezos）非同質化代幣平台「Hic et Nunc」（已更名為「TEIA」），如果機器在學習過程中逐步向人趨近，那麼「他／她們」是否也會發現作品正以NFT的形式販售，甚至在午夜夢迴時若有所思？ 機器會夢見NFT嗎？這個問題交給步入展間的您──和周邊越發聰明的所有手機、電腦和電子儀器──來回答。 Since Ian Goodfellow proposed the Generative Adversarial Network (GAN) in 2014, this technology has attracted a lot of attention in fields like game design, astronomical research and advertising image, and visual art is no exception. A GAN is a Deep Learning in Machine Learning, which is an essential topic of Artificial Intelligence that focuses on the neural network simulation to identify, produce, and improve information. Of the lengthy term “Generative Adversarial Network,” “Adversarial” is the core feature: setting up the duo models of “generator” and “discriminator” for both to fight and grow with each other. First of all, the generator acquires materials from the latent space and creates seemingly genuine products. Secondly, the discriminator identifies these products as true or false on the basis of objects in reality or targets in the database. If a product is identified as true, the product passes the test, and the information is verified. Otherwise, the generator will generate information again until they cheat the discriminator. The relation between the generator and discriminator is like the one between counterfeit money makers and criminal affairs bureau or that between art forgers and art forensic investigators. Even if we do not treat it as such, their interaction can be understood as that between artists and critics, which improves information or artworks in various aspects. Applying this logic and technology mentioned above to visual art, viewers can not only see something or someone that does not exist, but also appreciate the repeated process of production and correction. By distinguishing true from false, grasping the variable and the constant, and imaging the links among all and the possibilities in appearance change, we play with “ways of viewing” yet again. Besides, if machines can paint, what do they “think of” and “see”? This question may be exaggerated. After all, aren’t all these products creation of humans? These controversies may be chances to the reinterpretation of human-machine relationship. At the onset of GAN, the technology of Non-Fungible Token (NFT) was not born yet. Nowadays, along with the popularization of blockchain and cryptocurrency, there is an increasing number of artists creating and turning works into NFTs with GANs. Most of the exhibits in this exhibition are from Hic et Nunc (now TEIA), a Tezos NFT platform. If machines are approximating humans in the process of learning, will they also discover that their works are on sale in the form of NFTs, and have some thoughts to ponder over at midnight? Do machines dream of NFT? This question is left for everyone stepping into the exhibition, as well as the ever-smarter mobile phones, computers, and electronic devices around us, to answer.

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VolumeDAO

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VolumeDAO

VolDAO，成立於 2021 年底，台灣第一個立基在 Tezos 鏈的 NFT 藏家群體。Vol 是 Volume 的簡稱，除了有「音量」或「聲量」的意思，更是藏品的單位名稱，如「卷」、「冊」或「輯」。在收藏值得投資的、能夠開拓未來藝術史的作品之餘，我們也策畫展覽，嘗試為元宇宙打造良善的公領域。讓我們追求值得收藏的作品，成為敢於行動的藏家。 VolDAO, established at the end of 2021, is the first NFT collector community in Taiwan on the basis of Tezos. “Vol” is the abbreviation of “Volume”. Aside from “volume” or the extended meaning of “buzz” in the context of social media, it is also a unit for collection, like “volume,” “book,” or “part.” We collect works worthy of investment and able to make history of art in the future. Meanwhile, we curate events and endeavor to build a better public sphere for the metaverse. Let us pursue artworks worthy of collecting and be collectors of action.
迷莫‧阿克騰 Memo Akten

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迷莫‧阿克騰 Memo Akten

迷莫‧阿克騰是來自土耳其伊斯坦堡的跨領域藝術家、實驗電影製作人、音樂家和電腦科學家。他以新興技術和電腦計算為媒介，創作圖像、聲音、電影、大型互動裝置和表演。他著醉心於探索自然的本質和人類處境，從生物和人工智能、計算機創造力、意識、神經科學、物理學、生物學、生態學、哲學、儀式和宗教等領域汲取靈感。他擁有倫敦金匠大學的人工智能和人機交互表現博士學位，並且是加州大學聖地亞哥分校 (UCSD) 的計算機藝術助理教授。 Akten 經常就藝術、科學、技術和文化等話題發表主題演講。作為博士學位的一部分，他專注於人機交互和人工智能表現的創造性探索，在這一領域，他被認為是世界領先的先驅之一。 迷莫‧阿克騰因其作品“Forms”於 2013 年獲得了 Prix Ars Electronica Golden Nica。他曾在大皇宮（法國，巴黎）、巴比肯藝術中心（英國，倫敦）、維多利亞與亞伯特博物館、莫斯科現代藝術館（俄羅斯，莫斯科）、McaM明當代美術館（中國，上海）等。他還與 Lenny Kravitz、U2、Depeche Mode 和 Richard Dawkins 教授等名人合作。 Memo Akten is a multi-disciplinary artist, experimental filmmaker, musician and computer scientist from Istanbul, Turkey. He works with emerging technologies and computation as a medium, to create images, sounds, films, large-scale responsive installations and performances. Fascinated by trying to understand the nature of nature and the human condition, he draws from fields such as biological and artificial intelligence, computational creativity, consciousness, neuroscience, physics, biology, ecology, philosophy, ritual and religion. He has a PhD in Artificial Intelligence and expressive human-machine interaction from Goldsmiths University of London, and is Assistant Professor of Computational Arts at University of California, San Diego (UCSD). Akten is a frequent keynote speaker on topics involving art, science, technology and culture. As part of his PhD, he specializes in expressive human-machine interaction and creative explorations of Artificial Intelligence, and in this field he is considered one of the world’s leading pioneers. Akten received the Prix Ars Electronica Golden Nica for his work ‘Forms’ in 2013. He has exhibited and performed internationally at venues such as The Grand Palais (Paris FR), The Barbican (London UK), Victoria & Albert Museum, Moscow Museum of Modern Art (Moscow RU), Shanghai Ming Contemporary Art Museum (Shanghai CN) and many others. He has also collaborated with celebrities such as Lenny Kravitz, U2, Depeche Mode and Professor Richard Dawkins.
Ganbrood

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Ganbrood

Ganbrood本名巴斯‧烏特維克（Bas Uterwijk），居住在阿姆斯特丹，是一名自由攝影師，他使用 GAN（生成對抗式網絡）生成著名歷史人物的逼真肖像。經過數千張照片的AI訓練，這些深度學習的網絡能夠生成看起來（至少從表面上看）人眼真實的照片。從米開朗基羅的大衛和拿破崙到自由女神像，Ganbrood使用人工智能創建攝影類圖像，試著讓我們了解這些人的真實面貌。 based in Amsterdam, Ganbrood is a freelance photographer that uses GAN (generative adversarial network) to generate hyper-realistic portraits of famous historical figures. trained with thousands of photographs, these deep learning networks are able to generate photographs that look — at least superficially — genuine to the human eye. from michelangelo’s david and napoleon to the statue of liberty, uterwijk uses artificial intelligence to create photography-type images that might give us an idea of how these people really looked like.
馬里奧‧克林格曼 Mario Klingemann

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馬里奧‧克林格曼 Mario Klingemann

馬里奧‧克林格曼是一位德國藝術家，也是 Google 藝術與文化部門的常駐藝術家，以神經網絡、編碼和演算法方面的工作而聞名。他被認為是在藝術中使用計算機學習的先驅。他的作品通過機器學習和人工智能來檢驗創造力、文化和感知，並展出於奧地利電子藝術節、紐約現代美術館、紐約大都會美術館、倫敦Photographers’畫廊、巴黎龐畢度藝術中心和大英圖書館。 Mario Klingemann is a German artist and Google Arts and Culture resident known for his work involving neural networks, code, and algorithms. He is considered a pioneer in the use of computer learning in the arts. His works examine creativity, culture, and perception through machine learning and artificial intelligence, and have appeared at the Ars Electronica Festival, the Museum of Modern Art New York, the Metropolitan Museum of Art New York, the Photographers’ Gallery London, the Centre Pompidou Paris, and the British Library.

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