[R] From DeepMind: Grounded Language Learning in a Simulated 3D World • r/MachineLearning


Abstract: We are increasingly surrounded by artificially intelligent technology that takes decisions and executes actions on our behalf. This creates a pressing need for general means to communicate with, instruct and guide artificial agents, with human language the most compelling means for such communication. To achieve this in a scalable fashion, agents must be able to relate language to the world and to actions; that is, their understanding of language must be grounded and embodied. However, learning grounded language is a notoriously challenging problem in artificial intelligence research. Here we present an agent that learns to interpret language in a simulated 3D environment where it is rewarded for the successful execution of written instructions.

Google Translate is tapping into neural networks for smarter language learning


Google Translate is rolling out a major upgrade that promises more human-like language translations. Google is bullish on its Neural Machine Translation technology, claiming that it's a bigger upgrade to the service than everything that's been accomplished in the last ten years combined. The company is rolling out the improvements to eight language pairs in Google search, the Translate apps, and the website. You'll find the new technology behind translations between English and French, German, Spanish, Portuguese, Chinese, Japanese, Korean and Turkish. Google says that makes up more than 35 percent of all language queries.

Sifu: Interactive Crowd-Assisted Language Learning

AAAI Conferences

This paper introduces SIFU, a system that recruits in real time native speakers as online volunteer tutors to help answer questions from Chinese language learners in reading news articles. SIFU integrates the strengths of two effective online language learning methods: reading online news and communicating with online native speakers. SIFU recruits volunteers from an online social network rather than recruits workers from Amazon Mechanical Turk.Initial experiments showed that the proposed approach is able to effectively recruit online volunteer tutors, adequately answer the learners' questions, and efficiently obtain an answer for the learner. Our field deployment illustrates that SIFU is very useful in assisting Chinese learners in reading Chinese news articles and online volunteer tutors are willing to help Chinese learners when they are on social network service.