The Age of Social Machines

Many of the most successful and important systems that impact our lives combine humans, data, and algorithms at Web Scale. These social machines are amalgamations of human and machine intelligence. This seminar will provide an update on SOCIAM, a five year EPSRC Programme Grant that seeks to gain a better understanding of social machines; how they are observed and constituted, how they can be designed and their fate determined. We will review how social machines can be of value to society, organisations and individuals. We will consider the challenges they present to our various disciplines.

Hierarchical Prediction Machines and Big Data Analytics

An emerging consensus in cognitive science views the biological brain as a hierarchically-organized predictive processing system. This is a system in which higher-order regions are continuously attempting to predict the activity of lower-order regions at a variety of (increasingly abstract) spatial and temporal scales. The brain is thus revealed as a hierarchical prediction machine that is constantly engaged in the effort to predict the flow of information originating from the sensory surfaces. Such a view seems to afford a great deal of explanatory leverage when it comes to a broad swathe of seemingly disparate psychological phenomena (e.g., learning, memory, perception, action, emotion, planning, reason, imagination, and conscious experience). In the most positive case, the predictive processing story seems to provide our first glimpse at what a unified (computationally-tractable and neurobiological plausible) account of human psychology might look like. This obviously marks out one reason why such models should be the focus of current empirical and theoretical attention. Another reason, however, is rooted in the potential of such models to advance the current state-of-the-art in machine intelligence and machine learning. Interestingly, the vision of the brain as a hierarchical prediction machine is one that establishes contact with work that goes under the heading of 'deep learning'. Deep learning systems thus often attempt to make use of predictive processing schemes and (increasingly abstract) generative models as a means of supporting the analysis of large data sets. But are such computational systems sufficient (by themselves) to provide a route to general human-level analytic capabilities? I will argue that they are not and that closer attention to a broader range of forces and factors (many of which are not confined to the neural realm) may be required to understand what it is that gives human cognition its distinctive (and largely unique) flavour. The vision that emerges is one of 'homomimetic deep learning systems', systems that situate a hierarchically-organized predictive processing core within a larger nexus of developmental, behavioural, symbolic, technological and social influences. Relative to that vision, I suggest that we should see the Web as a form of 'cognitive ecology', one that is as much involved with the transformation of machine intelligence as it is with the progressive reshaping of our own cognitive capabilities.

The parallel diplomacy and the International Relations of the regions

The inclusion of subnational entities in international politics, breaks with the exclusive privilege of handling external relations by the States. Regions and municipalities have developed international policies that strengthen local affairs in cultural, economic, politic, security and strategic cooperation aspects, through the so-called parallel diplomacy activities. The influence of regional institutions in global affairs is growing; however paradiplomacy practice is not institutionalized and received little attention in international relation studies.

Modelling official and parallel exchange rates in Colombia under alternative regimes: a non-linear approach

We examine the long-run relationship between the parallel and the official exchange rate in Colombia over two regimes; a crawling peg period and a more flexible crawling band one. The short-run adjustment process of the parallel rate is examined both in a linear and a nonlinear context. We find that the change from the crawling peg to the crawling band regime did not affect the long-run relationship between the official and parallel exchange rates, but altered the short-run dynamics. Non-linear adjustment seems appropriate for the first period, mainly due to strict foreign controls that cause distortions in the transition back to equilibrium once disequilibrium occurs

Machines at work.

Se ofrece a los lectores más jóvenes una introducción al mundo de las ciencias, para que de forma práctica y amena aprendan y descubran por sí mismos. En este volumen, se explican a traves de hechos y actividades los distintos tipos de fuerzas en los que se basa la mecánica, como parte de la física, para la cosntrucción de máquinas para el trabajo.

Minds and machines : Britain, 1750-1900.

Explora el contexto social, político y espiritual de las personas en Gran Bretaña entre 1750-1900, para ayudar a los alumnos a comprender las mentes de las personas a lo largo de años de grandes cambios. Apoya el desarrollo de habilidades de pensamiento con un lenguaje ameno y cuidadosamente planificado. Cada sección se ha estructurado como una investigación, en torno a una cuestión fundamental de importancia histórica. Cada capítulo está diseñado para poder ampliarse por escrito. Los estudiantes podrán ordenar y clasificar la información y aprender a conectar las cuestiones clave.

Minds and machines. Teacher's book : Britain, 1750-1900.

Explora el contexto social, político y espiritual de las personas en Gran Bretaña entre 1750-1900. Para ayudar a los alumnos a comprender las mentes de las personas a lo largo de años de grandes cambios. Tiene por objeto evitar la cobertura superficial, construyendo el conocimiento y la comprensión conceptual apoyándose en tres principios de enseñanza: motivación, rigor y adecuado ritmo.Los alumnos deben ser estimulados por el material, motivación, que debe ser directo y centrado en las metas, rigor, y deben tener la ayuda que garantice su ritmo adecuado de prendizaje.

El cinema i la constitució d'un públic popular a Barcelona. El cas del Paral·lel

Between 1895 and 1910 Barcelona saw a whole range of social, political and cultural changes due to the increasingly important emergence of the working masses. At the same time, the cinema arrived in Catalonia, becoming very quickly one of the favorite entertainments of the urban laboring population which was about creating a new culture opposed to the modernist and nineteenth-century elite .This is, broadly speaking, the context that serves as a starting point for a study of the role of cinema in shaping a mass audience in Barcelona, an analysis centered on new urban spaces intended for the leisure of the lower classes emerged with the birth of modern Barcelona, especially the “Paral•lel” avenue, whose opening in 1894 made even more apparent the great social tensions and existing inequalities in Barcelona’s society at the end of the century.

Scalability of efficient parallel K-Means

Clustering is defined as the grouping of similar items in a set, and is an important process within the field of data mining. As the amount of data for various applications continues to increase, in terms of its size and dimensionality, it is necessary to have efficient clustering methods. A popular clustering algorithm is K-Means, which adopts a greedy approach to produce a set of K-clusters with associated centres of mass, and uses a squared error distortion measure to determine convergence. Methods for improving the efficiency of K-Means have been largely explored in two main directions. The amount of computation can be significantly reduced by adopting a more efficient data structure, notably a multi-dimensional binary search tree (KD-Tree) to store either centroids or data points. A second direction is parallel processing, where data and computation loads are distributed over many processing nodes. However, little work has been done to provide a parallel formulation of the efficient sequential techniques based on KD-Trees. Such approaches are expected to have an irregular distribution of computation load and can suffer from load imbalance. This issue has so far limited the adoption of these efficient K-Means techniques in parallel computational environments. In this work, we provide a parallel formulation for the KD-Tree based K-Means algorithm and address its load balancing issues.

Optimal inverter design for an induction machine using resonant frequency matching

The frequency responses of two 50 Hz and one 400 Hz induction machines have been measured experimentally over a frequency range of 1 kHz to 400 kHz. This study has shown that the stator impedances of the machines behave in a similar manner to a parallel resonant circuit, and hence have a resonant point at which the Input impedance of the machine is at a maximum. This maximum impedance point was found experimentally to be as low as 33 kHz, which is well within the switching frequency ranges of modern inverter drives. This paper investigates the possibility of exploiting the maximum impedance point of the machine, by taking it into consideration when designing an inverter, in order to minimize ripple currents due to the switching frequency. Minimization of the ripple currents would reduce torque pulsation and losses, increasing overall performance. A modified machine model was developed to take into account the resonant point, and this model was then simulated with an inverter to demonstrate the possible advantages of matching the inverter switching frequency to the resonant point. Finally, in order to experimentally verify the simulated results, a real inverter with a variable switching frequency was used to drive an induction machine. Experimental results are presented.