Jose A. Hernandez

The main factor of intelligence is defined as the ability tocomprehend, formalising this ability with the help of new constructsbased on descriptional complexity. The result is a comprehension test,or C- test, which is exclusively defined in computational terms. Due toits absolute and non-anthropomorphic character, it is equally applicableto both humans and non-humans. Moreover, it correlates with classicalpsychometric tests, thus establishing the first firm connection betweeninformation theoretical notions and traditional IQ tests. The TuringTest is compared with the C- test and the combination of the two isquestioned. In consequence, the idea of using the Turing Test as apractical test of intelligence should be surpassed, and substituted bycomputational and factorial tests of different cognitive abilities, amuch more useful approach for artificial intelligence progress and formany other intriguing questions that present themselves beyond theTuring Test

The removal of water from mines was one of the key issues that former miners had to deal with. Roman colonists brought new technology to the Iberian Peninsula that addressed this problem. However, they did not invent this technology because it had already been applied to the growth of other endeavours in the Hellenistic society throughout the Eastern Mediterranean. In the mine, the Archimedes screw, waterwheels, bucket pulleys, and Ctesibius pumps were the primary drainage systems. In this essay, the primary characteristics, and modes of operation of machines are examined. Without leaving out the most significant finds made in the southwest of the Iberian Peninsula, one of the regions with the longest history of mining exploitation. To serve as a foundation for future research in this field, this work compares the primary mining mechanisms in ancient Huelva on a qualitative and quantitative level by the implementation of a TOPSIS methodology, a multi-criteria decision analysis method.

Uno de los grandes problemas que enfrenta la educación en la actualidad, radica en el hecho de que los profesores de pronto se ven invadidos, y en su caso, obligados a utilizar las computadoras, los dispositivos móviles e Internet en el salón de clase. La falta de programas efectivos de capacitación y formación docente en el uso y aplicación de las TIC en los procesos de enseñanza aprendizaje, se ha convertido en un problema de grandes dimensiones que alcanza prácticamente a todos los niveles educativos. Ante tal escenario, el presente trabajo pretende la adopción por parte de los profesores, de una herramienta que les sea de utilidad para orientar su formación en el campo de las TIC: “El árbol diagnóstico de las competencias digitales”, el cual ofrece un panorama general acerca de los recursos informáticos y de la Web que hemos identificado como relevantes en el ejercicio de la docencia. Este “árbol diagnóstico” es el resultado de un proceso de evaluación y seguimiento llevado a cabo con grupos de profesores que ya utilizan la tecnología en su práctica docente; y tiene la finalidad de orientar y facilitar el aprendizaje autónomo de los profesores que se inician en el uso de las TIC.

La integración de libros electrónicos como elementos destinados a favorecer la construcción de aprendizajes en los procesos educativos, supone una serie de conocimientos previos concernientes a las tendencias hipertextuales del e-book que los estudiantes universitarios deberían poseer, dadas las características de la sociedad actual en la que los jóvenes hacen uso cotidiano de ese tipo de tecnología para llevar a cabo diversas tareas. En ese tenor, el presente trabajo da cuenta de una investigación realizada con una población estudiantil de la Carrera de Cirujano Dentista, cuyo objetivo se encaminó a identificar aquellos elementos involucrados con la adopción del libro en formato electrónico como apoyo didáctico para la asignatura Metodología de la Investigación.

In the last 20 years the Turing test has been left further behind by new developments in artificial intelligence. At the same time, however, these developments have revived some key elements of the Turing test: imitation and adversarialness. On the one hand, many generative models, such as generative adversarial networks, build imitators under an adversarial setting that strongly resembles the Turing test. The term “Turing learning” has been used for this kind of setting. On the other hand, AI benchmarks are suffering an adversarial situation too, with a ‘challenge-solve-and-replace’ evaluation dynamics whenever human performance is ‘imitated’. The particular AI community rushes to replace the old benchmark by a more challenging benchmark, one for which human performance would still be beyond AI. These two phenomena related to the Turing test are sufficiently distinctive, important and general for a detailed analysis. This is the main goal of this paper. After recognising the abyss that appears beyond superhuman performance, we build on Turing learning to identify two different evaluation schemas: Turing testing and adversarial testing. We revisit some of the key questions surrounding the Turing test, such as ‘understanding’, commonsense reasoning and extracting meaning from the world, and explore how the new testing paradigms should work to unmask the limitations of current and future AI. Finally, we discuss how behavioural similarity metrics could be used to create taxonomies for artificial and natural intelligence. Both testing schemas should complete a transition in which humans should give way to machines—not only as references to be imitated but also as judges—when pursuing and measuring machine intelligence.

Counting models for a two conjunctive formula $F$, a problem known as $\sharp $2Sat, is a classic $\sharp $P complete problem. Given a 2-CF $F$ as input, its constraint graph $G$ is built. If $G$ is acyclic, then $\sharp $2Sat can be computed efficiently. In this paper, we address the case when $G$ has cycles. When $G$ is cyclic, we propose a decomposition on the constraint graph $G$ that allows the computation of $\sharp $2Sat in incremental way. Let $T$ be a cactus graph of $G$ containing a maximal number of independent cycles, and let $\overline{T}=-E)$ be a subset of frond edges from $G$. The clauses in $\overline{T}$ are ordered in connected components $\{K_1, \ldots, K_r\}$. Each $, i=1,\ldots,r$ is a knot of the graph. The arrangement of the clauses of $\overline{T}$ allows the decomposition of $G$ in knots and provides a way of computing $\sharp $2Sat in an incremental way. Our procedure has a bottom-up orientation for the computation of $\sharp $2Sat. It begins with $F_0 = T$. In each iteration of the procedure, a new clause $C_i \in \overline{T}$ is considered in order to form $F_i = $ and then to compute $\sharp $2Sat$$ based on the computation of $\sharp $2Sat$$.

Animals, including humans, are usually judged on what they could become, rather than what they are. Many physical and cognitive abilities in the ‘animal kingdom’ are only acquired (to a given degree) when the subject reaches a certain stage of development, which can be accelerated or spoilt depending on how the environment, training or education is. The term ‘potential ability’ usually refers to how quick and likely the process of attaining the ability is. In principle, things should not be different for the ‘machine kingdom’. While machines can be characterised by a set of cognitive abilities, and measuring them is already a big challenge, known as ‘universal psychometrics’, a more informative, and yet more challenging, goal would be to also determine the potential cognitive abilities of a machine. In this paper we investigate the notion of potential cognitive ability for machines, focussing especially on universality and intelligence. We consider several machine characterisations (non-interactive and interactive) and give definitions for each case, considering permanent and temporal potentials. From these definitions, we analyse the relation between some potential abilities, we bring out the dependency on the environment distribution and we suggest some ideas about how potential abilities can be measured. Finally, we also analyse the potential of environments at different levels and briefly discuss whether machines should be designed to be intelligent or potentially intelligent

Mundus vult decipi, ergo decipiatur—the world wants to be deceived, so let it be deceived.Artificial intelligence has been a deceiving discipline: AI addresses those tasks that, if performed by humans, would require intelligence, but have been solved without featuring any genuine intelligence. This delusion has come, in return, with algorithmic techniques that can reliably solve many of these tasks, from game playing to pattern recognition. AI applications are a success.However, AI has not solved “what makes [us] clever, the puzzle of intelligence”. Those that expect that this book brings the answer will have their hopes deceived. This book is about what does not make us clever, a restatement of Fodor’s “The mind doesn’t work that way” . Partridge swings between condescending scepticism and bitter negativism with most of what AI has become, and reaches fierce disparagement of the technological singularity visionaries.The main message of the book is that science is stil ..

Todo conocimiento científico es positivo en cuanto que su contenido incrementa el control de la realidad. El desciframiento del genoma humano, con la consiguiente identificación y localización de los 50.000 a 100.000 genes que configuran su patrimonio genético, permitirá el progresivo esclarecimiento de los mecanismos reguladores de la expresión génica y pondrá al alcance del hombre posibilidades espléndidas, que requerirá años desentrañar. El acelerado ritmo en la caracterización de nuevos genes está desencadenando la posibilidad de pronosticar un número cada vez mayor de enfermedades genéticas y, por tanto, puede propiciar la práctica de una Medicina preventiva cada vez más rigurosa. Sin embargo, las posibles aplicaciones del conocimiento científico que aporta este proyecto suscitan también importantes inquietudes, desde el momento en que cada ser humano puede convertirse en un ser sin intimidad biológica. Por otra parte, la tecnología del ADN recombinante, al tiempo que aporta la enorme posibilidad de una futura terapia génica, suscita también legítimas preocupaciones sobre el correcto uso de estos conocimientos. En este artículo se abordan algunas de las cuestiones de carácter ético que ya plantea actualmente el Proyecto del Genoma Humano. Se adopta la perspectiva según la cual el respeto al patrimonio genético debería estar siempre presidido por un principio básico: no perder nunca de vista al hombre, esto es, al ser humano y su derecho a la identidad personal propia.

This paper defines in a formal and computational way the notion of ‘consilience’, a term introduced by Whewell in 1847 for the evaluation of scientific theories. Informally, as has been used to date, a model or theory is ‘consilient’ if it is predictive, explanatory and unifies the evide-nce. Centred in a constructive framework, where new terms can be intro-duced, we essay a formalisation of the idea of unification based on the avoidance of ‘sepa-ration’. However, it is soon manifest that this classical approach is vulnerable to the introduction of fantastic concepts to unify disparate sub-theories. Our second approach is constructed by using a detailed evaluation of the relationship between the theory and the evid-ence by means of reinforcement propagation. With the use of reinfor-cement, fantastic concepts can be better detected and the role of con-silience for theory construction and revision can be specialised for dif-ferent inference mechanisms like explanatory induction, abduction, deduc-tion and analogy.