| 000 | 02456nam a22002417a 4500 | ||
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| 005 | 20240210141309.0 | ||
| 008 | 240210b |||||||| |||| 00| 0 eng d | ||
| 020 | _a9780262046183 | ||
| 028 |
_a: Technical Bureau India _b: E/261, Shastri Nagar, Delhi _c: TB3707 _d: 08/02/2024 |
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| 082 | _a776 AUD | ||
| 100 | _aAudry, Sofian. | ||
| 245 |
_aArt in the age of Machine Learning. _c/ Sofian Audry. |
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| 260 |
_a, London _b: MIT Press _c, 2021. |
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| 300 |
_axi,193p. _c: 24cm. |
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| 365 | _b2693 | ||
| 520 | _aOver the past decade, an artistic movement has emerged that draws on machine learning as both inspiration and medium. In this book, transdisciplinary artist-researcher Sofian Audry examines artistic practices at the intersection of machine learning and new media art, providing conceptual tools and historical perspectives for new media artists, musicians, composers, writers, curators, and theorists. Audry looks at works from a broad range of practices, including new media installation, robotic art, visual art, electronic music and sound, and electronic literature, connecting machine learning art to such earlier artistic practices as cybernetics art, artificial life art, and evolutionary art. Machine learning underlies computational systems that are biologically inspired, statistically driven, agent-based networked entities that program themselves. Audry explains the fundamental design of machine learning algorithmic structures in terms accessible to the nonspecialist while framing these technologies within larger historical and conceptual spaces. Audry debunks myths about machine learning art, including the ideas that machine learning can create art without artists and that machine learning will soon bring about superhuman intelligence and creativity. Audry considers learning procedures, describing how artists hijack the training process by playing with evaluative functions; discusses trainable machines and models, explaining how different types of machine learning systems enable different kinds of artistic practices; and reviews the role of data in machine learning art, showing how artists use data as a raw material to steer learning systems and arguing that machine learning allows for novel forms of algorithmic remixes. | ||
| 650 | _aMachine learning | ||
| 650 | _aNew media art | ||
| 650 | _aFundamental design of machine learning | ||
| 650 | _aAlgorithmic | ||
| 700 | _aSofian Audry | ||
| 942 | _cBOOK | ||
| 999 |
_c61435 _d61435 |
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