Questions on the Value of Speaking Robotish

What is the meaning behind declaring something a language?    We have many computing and many human languages.  How much does their form influence the nature of communication between people and people, people and devices?  What kinds of efficiencies occur?   Risks of error?  Learning of context?  Improvement of innovations?   Working with many 'agents'?   So many questions.

Do you speak robot-ish? Interpreters may soon be in the house
by Nancy Owano , Tech Xplore

(Tech Xplore)—OpenAI is a non-profit artificial intelligence research company. In describing their work, they state that they are "working towards the next set of breakthroughs." That is no exaggeration.


What if you are told machine learning is so yesterday in language processing. "By capturing statistical patterns in large corpora, machine learning has enabled significant advances in natural language processing," wrote Igor Mordatch, Pieter Abbeel in their paper "Emergence of Grounded Compositional Language in Multi-Agent Populations," now on arXiv.

However, they stated, just capturing statistical patterns is not enough for agents to intelligently interact with humans. With that in mind, they investigated if and how, "grounded compositional language can emerge as a means to achieve goals in multi-agent populations."

The authors noted that "Development of agents that are capable of communication and flexible language use is one of the long-standing challenges facing the field of artificial intelligence." Looks as if they are taking up that challenge 

In a recent blog post, Igor Mordatch, Pieter Abbeel, Ryan Lowe, Jon Gauthier and Jack Clark, wrote about their new research where agents develop their own language..... " 

More information: * Learning to communicate: openai.com/blog/learning-to-communicate/
* Emergence of Grounded Compositional Language in Multi-Agent Populations, arXiv:1703.04908 [cs.AI] arxiv.org/abs/1703.04908

Abstract
By capturing statistical patterns in large corpora, machine learning has enabled significant advances in natural language processing, including in machine translation, question answering, and sentiment analysis. However, for agents to intelligently interact with humans, simply capturing the statistical patterns is insufficient. In this paper we investigate if, and how, grounded compositional language can emerge as a means to achieve goals in multi-agent populations. Towards this end, we propose a multi-agent learning environment and learning methods that bring about emergence of a basic compositional language. This language is represented as streams of abstract discrete symbols uttered by agents over time, but nonetheless has a coherent structure that possesses a defined vocabulary and syntax. We also observe emergence of non-verbal communication such as pointing and guiding when language communication is unavailable. .... "