This paper presents a novel extension to the existing Multi-Agent Interoperability specifications of the Open Voice Interoperability Initiative (originally also known as OVON from the Open Voice Network). This extension enables AI agents developed with different technologies to communicate using a universal, natural language-based API or NLP-based standard APIs. Focusing on the management of multiparty AI conversations, this work introduces new concepts such as the Convener Agent, Floor-Shared Conversational Space, Floor Manager, Multi-Conversant Support, and mechanisms for handling Interruptions and Uninvited Agents. Additionally, it explores the Convener's role as a message relay and controller of participant interactions, enhancing both scalability and security. These advancements are crucial for ensuring smooth, efficient, and secure interactions in scenarios where multiple AI agents need to collaborate, debate, or contribute to a discussion. The paper elaborates on these concepts and provides practical examples, illustrating their implementation within the conversation envelope structure.

On a recent afternoon Jonas Thiel, a socioeconomics major at a college in northern Germany, spent more than an hour chatting online with some of the left-wing political philosophers he had been studying. These were not the actual philosophers but virtual recreations, brought to conversation, if not quite life, by sophisticated chatbots on a website called Character.AI. Mr. Thiel's favorite was a bot that imitated Karl Kautsky, a Czech-Austrian socialist who died before World War Two. When Mr. Thiel asked Kautsky's digital avatar to provide some advice for modern-day socialists struggling to rebuild the worker's movement in Germany, Kautsky-bot suggested that they launch a newspaper. "They can use it not only as a means of spreading socialist propaganda, which is in short supply in Germany for the time being, but also to organize working class people," the bot said. Kautsky-bot went on to argue that the working classes would eventually "come to their senses" and embrace a modern-day Marxist revolution.

Contrary to popular Anglocentric belief, English isn't the world's most-spoken language by the total number of native speakers -- nor is it the second. In fact, the West Germanic tongues rank third on the list, followed by Hindi, Arabic, Portuguese, Bengali, and Russian. Surprisingly, Google Assistant, Apple's Siri, Amazon's Alexa, and Microsoft's Cortana recognize a relatively narrow slice of those. It wasn't until this fall that Samsung's Bixby gained support for German, French, Italian, and Spanish -- dialects collectively spoken by 616 million people worldwide. And it took years for Cortana to become conversant in Spanish, French, and Portuguese.

DBS Bank is in the midst of an enormous digital transformation effort, one that includes an aggressive plan to implement artificial intelligence and machine learning. Part of the near-term effort is to build an enterprise AI competency. "We want to train the top 250 executives in the firm to become AI conversant," said David Gledhill, group CIO and head of group technology and operations at DBS Bank. "We want to train 200 people to be what we call AI translators." By conversant, Gledhill means training executives to understand machine learning techniques at a high level, as well as knowing enough to "intelligently question what a model is and what it can do," he said.

This article is part of CMO.com's March/April series about emerging technology. Don't confuse the replacement of duties with the replacement of jobs: It's an important point when it comes to the impact of artificial intelligence on the workforce. Not only does the emerging technology promise to free employees of their more mundane responsibilities, it also signals new opportunities for them to learn new skills. Accenture's delivery-centre operation in India–where thousands of employees have not only kept their jobs, but have been reskilled as part of an AI-driven transformation–is a true example. "We don't see it replacing jobs–we see it replacing tasks," said Amit Bansal, Accenture's APAC analytics and artificial intelligence delivery lead.

SimDialog: A Visual Game Dialog Editor 1 Running head: SIMDIALOG SIMDIALOG: A VISUAL GAME DIALOG EDITOR Charles B. Owen, Frank Biocca, Corey Bohil, Jason Conley Michigan State University East Lansing MI SimDialog: A Visual Game Dialog Editor 2 Abstract SimDialog is a visual editor for dialog in computer games. This paper presents the design of SimDialog, illustrating how script writers and non-programmers can easily create dialog for video games with complex branching structures and dynamic response characteristics. The system creates dialog as a directed graph. This allows for play using the dialog with a statebased cause and effect system that controls selection of non-player character responses and can provide a basic scoring mechanism for games. SimDialog: A Visual Game Dialog Editor 3 Introduction A challenge in the design of computer games is writing, organizing, and testing nonlinear dialog involving multiple user options and branches to many different possible character responses. One form of these are dialog trees (Bateman 2007) -- scripts that allow for multiple user inputs and character responses. We have developed SimDialog, a visual editor for complex nonlinear game dialog. The SimDialog system consists of an editor program that allows authors to design complex conversations with multiple options and a runtime component that manages the progression through the conversation during game play. SimDialog makes it easy for game writers and non-programmers to create dialog for computer games directly without having to edit complex file formats or pass their work to programmers who must then embed the dialog in the game program.