Image or to image?

The proliferation of images towards an iconic communication in the hypermediacy of social media, of locative media, of Internet of Things (IoT) on one side and the visualization of real-time data, the deep learning algorithm on the other, question the essence of how reality is perceived, created and the nature and role of images itself. The common understanding of what constitutes an image is related to the representation of things and people. In the context of instant messaging, social media and Big Data, distributed and networked IoT, this seems not to be the case anymore. IoT extends the idea of social media to embrace ‘things’ into the equation, to form something that the author defines as the ‘Thingbook’. The Thingbook generates images of us from the perspective of things and data based on a heterogeneous system of technologies that sense, capture, analysis and learn about the world in real-time. Through this real-time dimension reality oscillates from a representational paradigm to a performative one and to certain extent towards a paradoxical condition. This article will collect evidence of how IoT hypermediacy is increasingly changing communication from linguistic to iconic, and how data visualization and Artificial Neural Networks are changing ways of learning from text to images at the level of the Google Cat Algorithm where Facebook and Thingbook converge. This will look into practices that make extensive use of the image in the immediacy of communication, into evidence of how information derived from sensors is recomposed into images, and, to a certain extent, how the discourse around image and IoT or Big Data questions our concept of image and reality.