Recent studies in the field of artificial intelligence (in particular generative adversarial networks) have demonstrated outstanding results in the synthesis of hyperrealistic imagery [e.g. neural network Style Gan 2, https://arxiv.org/abs/1912.04958]. Along with the rendering of photorealistic images, data scientists and machine vision specialists have demonstrated extraordinary capabilities of the aforementioned class of artificial neural networks in simulating artistic techniques and style transfer. The degree of quality and accuracy of those algorithmic outputs strikes the imagination. These developments and the emerging prospect of their further applications and calibrations do pose new challenges in the fields of media, journalism and, of course, artistic production, raising a set of new aesthetic issues. The work Chinese ink is meant to facilitate an inquiry into traditional Chinese ink calligraphy technique; my interest is not related to the imagery, visual style or iconography in Chinese painting, but rather to the physical properties, material specificity and historical connotations of industrialisation of technic itself as seen through the lens of the present context. The way in which the ink behaves - as a material produced from soot and glue of animal origin or sometimes graphite-based mineral types, in contact with a special coarse-grained and pre-moistened paper, still remains superior in certain qualities as opposed to European inks. Radiating black lacquer sheen Chinese ink sticks are rubbed and diluted with water to a thick or thin liquid consistency, which allows for achieving a wide range of shades of black and grey, such depth and tone richness had hardly been achieved with European inks. In China ink is considered the cult of tradition and state-of-the-art technology. The work Chinese Ink visually examines applications of the generative-adversarial network in the synthetic simulation of the original technique.