A brief overview on the evolution of drawing machines

Through the pictorial narratives engraved on the walls of the caves during prehistory, we are sure that Humans used drawing to express feelings and communicate, long before inventing writing. In the same way that utensils were used to help him, he also used several utensils to draw. In the middle of the twentieth century, with all the technological evolution, we saw machines that helped artists in drawing and others that are extensions of the artist. In a project seeking the development of a robotic system capable of drawing autonomously we were faced with the question for how long artists have used drawing machines for their aid or even their extension? In this work, we present a collection of artworks that demonstrates the use of drawing machines throughout history in the last 500 years and how they are being adapted and reinvented according to the most current and also developing technology. At present there is a vast field of experimentation of these machines with Interfaces and Sensors and Intelligent Human-Computer Interaction.(undefined

Semantic Compression of Episodic Memories

Storing knowledge of an agent's environment in the form of a probabilistic generative model has been established as a crucial ingredient in a multitude of cognitive tasks. Perception has been formalised as probabilistic inference over the state of latent variables, whereas in decision making the model of the environment is used to predict likely consequences of actions. Such generative models have earlier been proposed to underlie semantic memory but it remained unclear if this model also underlies the efficient storage of experiences in episodic memory. We formalise the compression of episodes in the normative framework of information theory and argue that semantic memory provides the distortion function for compression of experiences. Recent advances and insights from machine learning allow us to approximate semantic compression in naturalistic domains and contrast the resulting deviations in compressed episodes with memory errors observed in the experimental literature on human memory.Comment: CogSci201