Developing 3D games requires specialized expertise across multiple domains, including programming, 3D modeling, and engine configuration, which limits access to millions of potential creators. Recently, researchers have begun to explore automated game development. However, existing approaches face three primary challenges: (1) limited scope to 2D content generation or isolated code snippets; (2) requirement for manual integration of generated components into game engines; and (3) poor performance on handling interactive game logic and state management. While Multimodal Large Language Models (MLLMs) demonstrate potential capabilities to ease the game generation task, a critical gap still remains in translating these outputs into production-ready, executable game projects based on game engines such as Unity and Unreal Engine. To bridge the gap, this paper introduces UniGen, the first end-to-end coordinated multi-agent framework that automates zero-coding development of runnable 3D games from natural language requirements. Specifically, UniGen uses a Planning Agent that interprets user requirements into structured blueprints and engineered logic descriptions; after which a Generation Agent produces executable C# scripts; then an Automation Agent handles engine-specific component binding and scene construction; and lastly a Debugging Agent provides real-time error correction through conversational interaction. We evaluated UniGen on three distinct game prototypes. Results demonstrate that UniGen not only democratizes game creation by requiring no coding from the user, but also reduces development time by 91.4%. We release UniGen at https://github.com/yxwan123/UniGen. A video demonstration is available at https://www.youtube.com/watch?v=xyJjFfnxUx0.

Flexible Vision, an AI vision systems provider, is disrupting the machine vision space with the launch of a new online platform. Users can now start creating Deep Learning (DL) vision models instantly, with zero programming skills and minimal experience in DL. It is the product of years of research and development to build a machine vision solution with intuitive machine learning at its heart. This is an important step forward, as artificial intelligence solutions are now in high demand, providing a competitive edge to savvy organizations. The users of the Flexible Vision platform benefit from the end-to-end toolchain, that provides data management, image annotation, model training, and deployment to the final application.

Voice is the new interface driving ambient computing. This statement has never been more true than it is today. Speech recognition is transforming our daily lives from digital assistants, dictation of emails and documents, to transcriptions of lectures and meetings. These scenarios are possible today thanks to years of research in speech recognition and technological jumps enabled by neural networks. Microsoft is at the forefront of Speech Recognition with its research results, reaching human parity on the Switchboard research benchmark.

Artificial Intelligence (AI) has emerged as one of the most disruptive forces behind the digital transformation of business. Our mission is to bring AI to every developer and every organization on the planet, and help businesses augment human ingenuity in unique and differentiated ways. Developers and data scientists are at the heart of driving this innovation force and we are committed to providing them the best tools to make them successful. These include tools for automating machine learning through the pre-built AI capabilities we offer for vision, speech, language, knowledge and search in Microsoft Cognitive Services. In November, at Microsoft Connect () 2017, I announced expanding AI tools and resources for developers and data scientists on Azure and described how the Microsoft AI platform enables a rich variety of application scenarios.