Quo Vadis, Artificial Intelligence?

Since its conception in the mid 1950s, artificial intelligence with its great ambition to understand and emulate intelligence in natural and artificial environments alike is now a truly multidisciplinary field that reaches out and is inspired by a great diversity of other fields. Rapid advances in research and technology in various fields have created environments into which artificial intelligence could embed itself naturally and comfortably. Neuroscience with its desire to understand nervous systems of biological organisms and systems biology with its longing to comprehend, holistically, the multitude of complex interactions in biological systems are two such fields. They target ideals artificial intelligence has dreamt about for a long time including the computer simulation of an entire biological brain or the creation of new life forms from manipulations of cellular and genetic information in the laboratory. The scope for artificial intelligence in neuroscience and systems biology is extremely wide. This article investigates the standing of artificial intelligence in relation to neuroscience and systems biology and provides an outlook at new and exciting challenges for artificial intelligence in these fields. These challenges include, but are not necessarily limited to, the ability to learn from other projects and to be inventive, to understand the potential and exploit novel computing paradigms and environments, to specify and adhere to stringent standards and robust statistical frameworks, to be integrative, and to embrace openness principles

Uma proposta de arquitetura genética da informação

Tese (doutorado)—Universidade de Brasília, Faculdade de Ciência da Informação, Programa de Pós-Graduação em Ciência da Informação, 2012.Esta tese propõe um referencial epistemológico e teórico para a ideia de uma Arquitetura Genética da Informação, fundamentada pela Teoria Geral da Arquitetura da Informação, proposta por Lima-Marques (2011); no âmbito da disciplina de Arquitetura da Informação, proposta por Siqueira (2012); e considerações da Fenomenologia Genética. AArquitetura Genética da Informação compreende dois aspectos fundamentais: a gênese e a genética da informação intencional. A Gênese da Informação Intencional ocorre idealmente como fenômeno em uma das fases da redução fenomenológica; e a Genética da Informação Intencional é caracterizada em uma analogia qualitativa identicada entre a Ciência da Informação e a Genética, dentro de suas quatro principais abordagens de estudo, a saber: a Clássica, Molecular, Populacional e Quantitativa. Ontologicamente, são considerados principalmente o genoma, genótipo e fenótipo dos objetos (endurantes) e seus processos (perdurantes) em associação aos termos da informação. Como resultados da pesquisa, apresentamos a Arquitetura Genética da Informação; desenvolvemos ontologias de alto-nível de analogia entre a Arquitetura da Informação e a Genética, elicitando os termos da informação e processos biológicos que envolvem a informação; e apresentamos algumas aplicações práticas na temática de similaridade fenotípica (textual, visual, acústica e em redes de pesquisa), evolução e inovação tecnológica por memética, hereditariedade da informação e manipulação genética da informação. ______________________________________________________________________________ ABSTRACTThis thesis proposes an epistemological and theoretical framework for the idea of a Genetic Architecture of Information, founded by the General Theory of the Architecture of Information, proposed by Lima-Marques (2011); under the discipline of Architecture of Information, proposed by Siqueira (2012); and considerations of Genetic Phenomenology. The Genetic Architecture of Information comprises two main aspects: the genesis and genetic intentional information. The Genesis of Intentional Information ideally occurs as a phenomenon in one of the stages of the phenomenological reduction; and the Genetic of Intentional Information is charac- terized and identi ed in a qualitative analogy between the Information Science and Genetics, within its four main study approaches, namely: Classical, Molecular, Population and Quantitative. Ontologically, we mainly consider the genome, genotype and phenotype of objects (endurants) and processes (perdurants) in association with terms of information. As results, we present the Genetic Architecture of Information; high-level ontologies developed in analogy between Information Architecture and Genetics aiming to elicit terms of information and bio logical processes that involve information; and some practical applications, such as phenotypic similarity (textual, visual, acoustic and in research social networks), technological evolution and innovation by means of memetics, information hereditability, and genetic manipulation of information