Numerous species use different forms of communication in order to successfully interact in their respective environment. This article seeks to elucidate limitations of the classical conduit metaphor by investigating communication from the perspectives of biology and artificial neural networks. First, communication is a biological natural phenomenon, found to be fruitfully grounded in an organism’s embodied structures and memory system, where specific abilities are tied to procedural, semantic, and episodic long-term memory as well as to working memory. Second, the account explicates (...) differences between non-verbal and verbal communication and shows how artificial neural networks can communicate by means of ontologically non-committal modelling. This approach enables new perspectives of communication to emerge regarding both sender and receiver. It is further shown that communication features gradient properties that are plausibly divided into a reflexive and a reflective form, parallel to knowledge and reflection. (shrink)

Ordinary objects are experienced to endure over space and time, to not be collocated with each other, to be composed of proper parts, and to survive the loss of some of their parts. These qualities are on the one hand difficult to reconcile for theorists of perception and on the other hand pose a variety of problems when considered in isolation. Relying on the theoretical framework of predictive processing, this paper argues that we can use the category of a robust (...) predictive process to conceptualize qualities such as persistence and compositionality in a unified manner. Traditional problems concerning the structural properties of ordinary objects, such as the question of when two objects compose, can then be reformulated using this new category. (shrink)