flowers – Artificial Intelligence https://ars.electronica.art/ai/en Ars Electronica Festival 2017 Tue, 28 Jun 2022 13:43:24 +0000 en-US hourly 1 https://wordpress.org/?v=4.9.6 Hybrid Art – Dust Blooms: a research narrative in artistic ecology https://ars.electronica.art/ai/en/hybrid-art-dust-blooms/ Tue, 08 Aug 2017 08:27:43 +0000 https://ars.electronica.art/ai/?p=3193

Alexandra R. Toland (US)

Dust Blooms juxtaposes the beauty and function of urban flora using a synthesis of artistic and scientific methods. With her project the artist seeks to call attention to the relevance of the urban ecosystem.

Her transdisciplinary examination of the dust filtration capacity of flowers consists of three parts:

1. Field research

The dust of seven flowers that grow wild in Linz directly next to streets with heavy traffic is collected and analyzed using light microscopy to determine the type and amount of dust particles.

2. Representation

Tiny details from historical illustrations of plants are digitally “grafted” together and engraved in plates. This illustrate how the graphical representation of these plant species has developed over the last 350 years.

3. Modeling

Sculptural prototypes based on the micro-morphological features of the dandelion (taraxacum) are made from materials from today’s consumer society. Current atmospheric dust levels are measured with integrated instruments and the obtained data is made freely accessible.

Credits

artoland.wordpress.com/2016/06/28

]]> hananona https://ars.electronica.art/ai/en/hananona/ Tue, 08 Aug 2017 05:47:11 +0000 https://ars.electronica.art/ai/?p=1787

STAIR Lab. (JP) collaborating with Surface & Architecture Inc, Kyoko Kunoh, Tomohiro Akagawa, Tanoshim Inc., mokha Inc. and Tokyo Studio Co. Ltd. (JP)

The latest AI research makes it possible to teach computers the names of things by showing them many examples. The key is a large amount of training data and deep learning software. By leveraging this, the artists have developed an AI capable of classifying 406 kinds of flower by using over 300,000 flower pictures.

hananona is an interactive work that visualizes how AI classifies a flower. When it sees a flower, it identifies its name and shows its class on a visual “flower map”—a visualization of the inside of the AI brain. This is a group of image clusters, each of which is a cluster of flower photos learned as belonging to the same class. By looking at them, users can see how AI classifies the flowers.

Users are encouraged to challenge hananona with their own flower photos, or with other materials such as pictures, paintings, flower-like objects etc. so that they can observe how the AI reacts to different abstraction levels of flowers.

Credits

STAIR Lab., Chiba Institute of Technology

Creative direction, design: Surface & Architecture Inc.

Art direction: Kyoko Kunoh
Interaction design, programming: Tomohiro Akagawa
Programming: Tanoshim Inc.
Server programming: mokha Inc.
Furniture production, site setup: Tokyo Studio Co., Ltd.

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