Amusing Ourselves until (Dis)appearing in La invención de Morel by Adolfo Bioy Casares

La invención de Morel reflect on how the use of technologies could be fascinating and dangerous at the same time; and the way the island seems to be a space of freedom while it is actually a place of prison and death. La invención de Morel presents a utopian situation that transforms into a dystopia. Characters, especially the narrator, project their desires along with the holograms, but they are deceived without realizing about their loss of reality. The novel uses phantasy and science fiction resources to reflect about the way humans self-imprison. This is studied by analogy to the effects of technologies in today's society. In this sense, the novel by Adolfo Bioy Casares is about a menace due to the human preference of imaginary life over real one.

Digital Reality Experiences as a Different Psychological Feel, Some Suggestions for Future Development

<p>Digital games experiences of 60 willing participants were recorded with two questionnaires in a survey. Infirst questionnaire, participants’ with self description, described own personality characteristics like steadfastness, social aspects and intelligence. The second questionnaire was about the personal experiences feels like pleasure, fear, nervousness and sensuality during digital reality games play. Both responses were compared with participants’ willingness to play the same digital games again. Findings reflected that human preference for digital reality game (dummies) was different as compared with other animals’ behaviors towards dummies, perhaps for pleasure that could be a mix of self-harm and self-deception or something else therefore evolving the possibility to describe digital experience as a different feel that could be positive because meanings of sadomasochism are now viewed with positive tilt (Wismeijer& Van Assen 2013) implications for future digital development also discussed.</p>

Digital Reality Experiences as a Different Psychological Feel, Some Suggestions for Future Development

<p>Digital games experiences of 60 willing participants were recorded with two questionnaires in a survey. Infirst questionnaire, participants’ with self description, described own personality characteristics like steadfastness, social aspects and intelligence. The second questionnaire was about the personal experiences feels like pleasure, fear, nervousness and sensuality during digital reality games play. Both responses were compared with participants’ willingness to play the same digital games again. Findings reflected that human preference for digital reality game (dummies) was different as compared with other animals’ behaviors towards dummies, perhaps for pleasure that could be a mix of self-harm and self-deception or something else therefore evolving the possibility to describe digital experience as a different feel that could be positive because meanings of sadomasochism are now viewed with positive tilt (Wismeijer& Van Assen 2013) implications for future digital development also discussed.</p>

Learning to Compare for Better Training and Evaluation of Open Domain Natural Language Generation Models

Automated evaluation of open domain natural language generation (NLG) models remains a challenge and widely used metrics such as BLEU and Perplexity can be misleading in some cases. In our paper, we propose to evaluate natural language generation models by learning to compare a pair of generated sentences by fine-tuning BERT, which has been shown to have good natural language understanding ability. We also propose to evaluate the model-level quality of NLG models with sample-level comparison results with skill rating system. While able to be trained in a fully self-supervised fashion, our model can be further fine-tuned with a little amount of human preference annotation to better imitate human judgment. In addition to evaluating trained models, we propose to apply our model as a performance indicator during training for better hyperparameter tuning and early-stopping. We evaluate our approach on both story generation and chit-chat dialogue response generation. Experimental results show that our model correlates better with human preference compared with previous automated evaluation approaches. Training with the proposed metric yields better performance in human evaluation, which further demonstrates the effectiveness of the proposed model.