Machines that Dream: A New Challenge in Behavioral-Basic Robotics

The digital revolution is transforming contemporary society. Connective intelligence is an emerging property deriving from the embedding of intelligence into the connected data, concepts, applications, and people. Furthermore, the progress in behavioral-basic robotics opens new fields of innovative investigation.In this challenging context, might it make sense to provide machines with dreaming-like functions? Indeed, machine inactivity can be assimilated to the sleep state of living beings. Furthermore, when dreaming, we can interact with what we take to be other individuals and things and, in certain respects, the same happens in the virtual world.This paper highlights some new directions that have emerged in the field of Artificial Intelligence, focusing on the total Turing test and dreaming machines

The neural string network: An interactive collaborative drawing ‘machine’

An interactive collaborative drawing ‘machine’ designed on the concept of a neural network, allowing participants to experience a shared creative process, using the principles of open-source and social networked communication through an analogue string system. The underlying concept of the String Neural Network is to introduce participants to the idea of collaborative-shared drawing practice, as a dispersed collective that alludes to Roland Barthes ‘The Death of the Author’ (Barthes 1967) whereby each participant plays an equal role as both viewer and artist. Played out like a surrealist ‘Exquisite Corpse’ game of consequences or as a piece of Haiku poetry, the drawing participants contribute marks, signs and signifiers to an open-content drawing, akin to the development of open-source software. The string network consists of five drawing table ‘nodes’ within a room/ studio space measuring eight by eight metres square. Each node is linked to the other four via pulleys and washing lines, making it possible to peg a sheet of A4 paper to a line and winch it across to any one of the other nodes. The network system uses 10 string connections between the five drawing tables, creating a pentagram within a pentagon neural network design. Representing the interconnected synapses and neurons of the brain, the role of each participant is that of cause and effect. A single instruction initiates a series of consequences that unfold in drawings, marks and patterns that are created whilst being hoisted simultaneously across the room in quick succession. The Neural String Network project was first set up in March 2012 to coincide with ‘DecodeRecode’, a telematic art project undertaken by students at MediaCityUK Salford University, as part of the centenary celebration of Alan Turing. Each participating student was given a single word drawn from the Turing theme, such as machine, brain, code and apple that were interpreted and communicated as a drawing by a collective consciousness

Using smartwatch sensors to support the acquisition of sleep quality data for supervised machine learning

It is a common practice in supervised learning techniques to use human judgment to label training data. For this process, data reliability is fundamental. Research on sleep quality found that human sleep stage misperception may occur. In this paper we propose that human judgment be supported by software-driven evaluation based on physiological parameters, selecting as training data only data sets for which human judgment and software evaluation are aligned. A prototype system to provide a broad-spectrum perception of sleep quality data comparable with human judgment is presented. The system requires users to wear a smartwatch recording heartbeat rate and wrist acceleration. It estimates an overall percentage of the sleep stages, to achieve an effective approximation of conventional sleep measures, and to provide a three-class sleep quality evaluation. The training data are composed of the heartbeat rate, the wrist acceleration and the three-class sleep quality. As a proof of concept, we experimented the approach on three subjects, each one over 20 nights

Probing many-body localization with neural networks

We show that a simple artificial neural network trained on entanglement spectra of individual states of a many-body quantum system can be used to determine the transition between a many-body localized and a thermalizing regime. Specifically, we study the Heisenberg spin-1/2 chain in a random external field. We employ a multilayer perceptron with a single hidden layer, which is trained on labeled entanglement spectra pertaining to the fully localized and fully thermal regimes. We then apply this network to classify spectra belonging to states in the transition region. For training, we use a cost function that contains, in addition to the usual error and regularization parts, a term that favors a confident classification of the transition region states. The resulting phase diagram is in good agreement with the one obtained by more conventional methods and can be computed for small systems. In particular, the neural network outperforms conventional methods in classifying individual eigenstates pertaining to a single disorder realization. It allows us to map out the structure of these eigenstates across the transition with spatial resolution. Furthermore, we analyze the network operation using the dreaming technique to show that the neural network correctly learns by itself the power-law structure of the entanglement spectra in the many-body localized regime.Comment: 12 pages, 10 figure

Alternative Presents and Speculative Futures: Designing fictions through the extrapolation and evasion of product lineages.

The core question addressed by this invited keynote and conference paper is how fictions are designed to negotiate, critique and realise the multiplicity of possible new technological futures. Focusing on methods, processes and strategies the presentation initially describes how things/technologies become products, employing the perspective of domestication to describe the transition from extraordinary to everyday. This development suggests a product history, a traceable lineage that goes back through generations, each one a small iteration of the previous. By modelling this lineage, design fictions can do two things: 1. Project current emerging technological development to create Speculative Futures: hypothetical products of tomorrow. 2. Break free of the lineage to speculate on Alternative Presents. These fictions effectively act as cultural litmus paper, either offering vignettes of how it might be to live with the technology in question or challenging contemporary applications of technology through demonstrable alternatives. The presentation focused on how these two types of fiction are created, how they differ from science fiction, other modes of future thinking and technological critique - more specifically how both methodologies utilise designed artefacts. What informs the development, aesthetics, behaviour, interactions and function of these objects? Once created, how and where do they operate? How can we gauge and understand their impact and meaning? As a consequence of the presentation Auger was invited to run workshops and projects in Basel (Hochschule für Gestaltung und Kunst) and HEAD (Haute école d’art et de design), Geneva and is advising on the design of a new masters programme at the Basel Hochschule

Spectrum, Volume 3, Number 3

Highlights include: Sacred Heart to bestow fewer degrees -- Parking violators beware! -- Theatre’s loss is SHU’S gain -- Incoming students face Core changes -- Letters to the Editor -- The dangers of traveling -- The science of dreams -- modern art studied -- Counseling service: an overview -- College at any age -- Elections outloo