A better life through information technology? The techno-theological eschatology of posthuman speculative science

This is the pre-peer reviewed version of the article, published in Zygon 41(2) pp.267-288, which has been published in final form at http://www3.interscience.wiley.com/journal/118588124/issueThe depiction of human identity in the pop-science futurology of engineer/inventor Ray Kurzweil, the speculative-robotics of Carnegie Mellon roboticist Hans Moravec and the physics of Tulane University mathematics professor Frank Tipler elevate technology, especially information technology, to a point of ultimate significance. For these three figures, information technology offers the potential means by which the problem of human and cosmic finitude can be rectified. Although Moravec’s vision of intelligent robots, Kurzweil’s hope for immanent human immorality, and Tipler’s description of human-like von Neumann probe colonising the very material fabric of the universe, may all appear to be nothing more than science fictional musings, they raise genuine questions as to the relationship between science, technology, and religion as regards issues of personal and cosmic eschatology. In an attempt to correct what I see as the ‘cybernetic-totalism’ inherent in these ‘techno-theologies’, I will argue for a theology of technology, which seeks to interpret technology hermeneutically and grounds human creativity in the broader context of divine creative activity

Multilingual Universal Sentence Encoder for Semantic Retrieval

We introduce two pre-trained retrieval focused multilingual sentence encoding models, respectively based on the Transformer and CNN model architectures. The models embed text from 16 languages into a single semantic space using a multi-task trained dual-encoder that learns tied representations using translation based bridge tasks (Chidambaram al., 2018). The models provide performance that is competitive with the state-of-the-art on: semantic retrieval (SR), translation pair bitext retrieval (BR) and retrieval question answering (ReQA). On English transfer learning tasks, our sentence-level embeddings approach, and in some cases exceed, the performance of monolingual, English only, sentence embedding models. Our models are made available for download on TensorFlow Hub.Comment: 6 pages, 6 tables, 2 listings, and 1 figur