Lazarus Chan

Pneuma.to

Artwork 1 Details :

A fluidity structure composed with symbols and breaths. We breathe to speak. Language is a fundamental component of our civilization. When our society evolves, language will transform gradually. From Quipu to Alphabet, humans invented methods for communication and recorded their conditions. In the digital age, we translated our language into different formats of information technology standards. Those technologies constrain our choice of words and reform our language indirectly. Behind all the computer documents, inexplicable machine codes update occasionally, and the hidden layers are not apparent. Due to these continuous changes, our technologies alienated us from our language. To show the fluidity of grammar and the uncertainty of digital languages, “Pneuma.to” composes a visual of distorted symbols with the sound input from a wireless device. The device’s appearance is likewise a mixture of flute and obelisk, the audience could blow or speak to the device, generating symbols to the projection on a particular position. After that, those symbols are contained in the projection during the software runtime, moving and combining into signs which wait for the audience’s interpretations, giving them meaning as language. https://www.lazaruschan.com/new-media-art/pneuma-to

Stochastic Camera (version 0.2) - the melting crystal ball (formula 1)

Artwork 2 Details :

“Stochastic Camera” is an art project series started from 2018. In version 0.2, it re-examines and reflects on the algorithmic logic of machine learning image processing. The project started from recording different ice balls melt within 3 hours for 8 days, captured around 24 hours of melting ice ball footage and transformed them into raw pixel data for further calculations. The melting ice ball symbolizes the future world may no longer need the crystal ball for witchcraft, and it also serves as a refractive object to extend the camera len’s glass. Stochastic Camera (version 0.2) utilize two separated formulas which represented overall stability and individuals’ autonomy. Those formulas are inspired by the ensemble average and stochastic processes for predictions, calculate a total average of data and predict the momentum of each pixel, leading to two sets of pixel data and moving images. Formula 1 : Ensemble Average It averages the pixel data matrix of 8 ice balls’ footages. With this formula, there are relationships between pixels that affect each of them in order to compose a stable overall image. The final image is similar to overlaying 8 video footages, but there is a major difference on the data handling. This method means that erasing all strong changes by compress those data to an average value, bundling every single pixels for an overall representation.

Stochastic Camera (version 0.2) - the melting crystal ball (formula 2)

Artwork 3 Details :

“Stochastic Camera” is an art project series started from 2018. In version 0.2, it re-examines and reflects on the algorithmic logic of machine learning image processing. The project started from recording different ice balls melt within 3 hours for 8 days, captured around 24 hours of melting ice ball footage and transformed them into raw pixel data for further calculations. The melting ice ball symbolizes the future world may no longer need the crystal ball for witchcraft, and it also serves as a refractive object to extend the camera len’s glass. Stochastic Camera (version 0.2) utilize two separated formulas which represented overall stability and individuals’ autonomy. Those formulas are inspired by the ensemble average and stochastic processes for predictions, calculate a total average of data and predict the momentum of each pixel, leading to two sets of pixel data and moving images. Formula 2 : Stochastic processes : Individual pixel’s momentum It identifies the probability of a individual pixel being abrove or below its average. Unlike other neural networks for image processing, which use the neighbouring pixel data as references to affect the target pixel’s changes. Instead, the neighbouring pixel data is not considered at all, and each of the pixel is given maximum autonomy to evolve.