Tiny Trainable Instruments
Name
montoyamoraga-velouria-MS-MAS-2021.pdf
Description
Thesis PDF
Size
9.27 MB
Format
Adobe PDF
Checksum (MD5)
77d6ac004a849e63ab72644f108d1b3d
Author(s)
Montoya-Moraga, Aarón
Advisor(s)
Machover, Tod
Date Issued
September 2021
Publisher
Massachusetts Institute of Technology
Abstract
Can we build flexible and reusable multimedia instruments that are trained instead of programmed? How can we build and publish our own personal databases for artistic purposes? What are the new choreographies and techniques that machine learning running on microcontrollers offer for artists and activists?
Tiny Trainable Instruments is a collection of multimedia devices, running machine learning algorithms on microcontrollers, for artistic purposes. It includes techniques for capturing data, building databases, training machine learning models, and deploying on microcontrollers. The software library created for this project allows for the creation of instruments that react to different inputs, including color, gesture, and speech, to control different multimedia outputs, including sound, light, and movement, using machine learning and embedded sensors.
This thesis emphasizes open source software and artificial intelligence ethics, and includes all the steps for creating these bridges between machine learning and media arts, that are respectful of privacy and consent because of their offline and off-the-grid nature.
MIT Department
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
Terms of Use
In Copyright - Educational Use Permitted
Copyright MIT
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