GMU:My Computer, Max, and I/Pedro Ramos: Difference between revisions

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The project consisted on a research regarding the connection and possible applications of Machine Learning in Max/MSP/Jitter, as well as the development of an environment inside of Max/MSP that could demonstrate and prototype such application. The final stage of the development consisted on getting sensor signal, in the case an Arduino, to receive physiological and potential environmental signal, and conduct it through a stochastic sound generation method in Max/MSP which the reactions were determined by Machine Learning.

The research aimed to develop a prototype on possible applications of such techniques in the development of musical instruments controlled by or sound generated in Max/MSP, interactive audio and/or video installations, amongst other possible developments. The main interest in using Machine Learning as a creative tool integrated with Max consisted on the set of possibilities that open up with the training possibilities facilitated by it, and how such possibilities can offer creatives working with Max/MSP new ways of interpreting data ~~manipulation with it~~, and as a consequence, new potential creative opportunities.

The research aimed to develop a prototype on possible applications of such techniques in the development of musical instruments controlled by or sound generated in Max/MSP, interactive audio and/or video installations, amongst other possible developments. The main interest in using Machine Learning as a creative tool integrated with Max consisted on the set of possibilities that open up with the training possibilities facilitated by it, and how such possibilities can offer creatives working with Max/MSP new ways of interpreting and manipulating data, and as a consequence, new potential creative opportunities.

==Technical Insights==

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 The project consisted on a research regarding the connection and possible applications of Machine Learning in Max/MSP/Jitter, as well as the development of an environment inside of Max/MSP that could demonstrate and prototype such application. The final stage of the development consisted on getting sensor signal, in the case an Arduino, to receive physiological and potential environmental signal, and conduct it through a stochastic sound generation method in Max/MSP which the reactions were determined by Machine Learning.
-The research aimed to develop a prototype on possible applications of such techniques in the development of musical instruments controlled by or sound generated in Max/MSP, interactive audio and/or video installations, amongst other possible developments. The main interest in using Machine Learning as a creative tool integrated with Max consisted on the set of possibilities that open up with the training possibilities facilitated by it, and how such possibilities can offer creatives working with Max/MSP new ways of interpreting data manipulation with it, and as a consequence,  new potential creative opportunities.
+The research aimed to develop a prototype on possible applications of such techniques in the development of musical instruments controlled by or sound generated in Max/MSP, interactive audio and/or video installations, amongst other possible developments. The main interest in using Machine Learning as a creative tool integrated with Max consisted on the set of possibilities that open up with the training possibilities facilitated by it, and how such possibilities can offer creatives working with Max/MSP new ways of interpreting and manipulating data, and as a consequence, new potential creative opportunities.
 ==Technical Insights==