CommAI: Evaluating the first steps towards a useful general AI

By Marco Baroni, Armand Joulin, Allan Jabri, Germán Kruszewski, Angeliki Lazaridou, Klemen Simonic, Tomas Mikolov. 2017

19 citations recorded by the source corpus.

With machine learning successfully applied to new daunting problems almost every day, general AI starts looking like an attainable goal. However, most current research focuses instead on important but narrow applications, such as image classification or machine translation. We believe this to be largely due to the lack of objective ways to measure progress towards broad machine intelligence. In order to fill this gap, we propose here a set of concrete desiderata for general AI, together with a platform to test machines on how well they satisfy such desiderata, while keeping all further complexities to a minimum.

Subfields: Artificial Intelligence, Health Informatics

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Citations in the corpus

Gradient Episodic Memory for Continual Learning (2017, background): “The CommAI project [Mikolov et al., 2015, Baroni et al., 2017] shares our same motivations, but focuses on highly structured task descriptors, such as strings of text.”
Efficient Lifelong Learning with A-GEM (2018, methodology): “More generally, tasks descriptors have been used in Reinforcement Learning with similar motivations by several others (Sutton et al., 2011; Schaul et al., 2015; Baroni et al., 2017), and it is also a key ingredient in all the zero/few-shot learning algorithms (Lampert et al.”
TextWorld: A Learning Environment for Text-based Games (2018, methodology): “The CommAI framework [Baroni et al., 2017] emphasizes the ability to generate curricula [Bengio et al.”
Efficient Lifelong Learning with A-GEM (2018, methodology): “More generally, tasks descriptors have been used in Reinforcement Learning with similar motivations by several others (Sutton et al., 2011; Schaul et al., 2015; Baroni et al., 2017), and it is also a key ingredient in all the zero/few-shot learning algorithms (Lampert et al.”
Language Tasks and Language Games: On Methodology in Current Natural Language Processing Research (2019, background): “…counterpart it is intended to model, and how.4 3See for example (Savva et al., 2019; Adams et al., 2012; Johnson et al., 2016; Urbanek et al., 2019; Baroni et al., 2017a; Xia et al., 2018; Yan et al., 2018; Misra et al., 2018; Côté et al., 2018; Bennett and Shatkhin, 2018; Anderson et al., 2018;…”