Embodied decision-making enables agents to translate high-level goals into executable actions through continuous interactions within the physical world, forming a cornerstone of general-purpose embodied intelligence. Large language models (LLMs), with their general decision-making capabilities, offer a promising path to realize this potential; however, LLMs trained solely on language lack exposure to physical environments, limiting their true embodied understanding. To bridge this gap, we propose the concept of a training ground: a comprehensive infrastructure that provides task and scene simulation, embodied interaction, and feedback signals, offering a one-stop solution for LLM acquire genuine embodied decision-making skills. In this work, we present EmboMatrix, the first training ground of its kind, providing massive and diverse tasks with efficient simulation and precise rewards. EmboMatrix incorporates a series of novel techniques: a multi-agent data engine for large-scale task and scene generation, a distributed heterogeneous-hardware system for scalable simulation, and a multi-level reward architecture for precise supervision. Leveraging EmboMatrix, we cultivate EmboBrain, an LLM whose embodied decision-making abilities emerge from extensive embodied interactions. Experiments show that EmboBrain-7B surpasses the 671B DeepSeek-R1 baseline by 9.5\% on two challenging embodied decision-making benchmarks, demonstrating the power of interactive, environment-grounded learning for building truly intelligent embodied agents.

Belarus and Russia's show of firepower appears to be a message to Europe In a large field 45 miles (72km) from Belarus' capital Minsk, a battle is raging. There are giant explosions as Sukhoi-34 bombers drop guided bombs. Helicopter gunships join the attack, while surveillance drones sweep overhead to view the damage. Together with other international media we've been brought to the Borisovsky training ground where Belarusian and Russian forces are taking part in joint manoeuvres. Military attachés, too, from a variety of embassies are observing the drill from a viewing platform.

Fox News Flash top sports headlines are here. Check out what's clicking on Foxnews.com. The U.S. men's national team is vying for the coveted CONCACAF Gold Cup winners trophy. But, as the USMNT prepared for Wednesday's semifinal match against Guatemala, a flying object caused a disruption at the team's training grounds. An unidentified party was believed to have been operating what appeared to be a drone in the vicinity of the team's training facility in St. Louis, CBS Sports reported.

Minecraft is more than just a game, according to Facebook, it also makes an ideal training ground for sophisticated artificial intelligence. The company says it will use Minecraft, a popular sandbox-style building and adventure game, to train an AI assistant on one of the most important human abilities: multi-tasking. 'Instead of superhuman performance on a single difficult task, we are interested in competency across a large number of simpler tasks, specified (perhaps poorly) by humans,' researchers say in a proposal paper. The bot will be able to interact with players and then perform tasks based on requests like'come here' or'can you build a circle there?' Minecraft was created in 2009. At the start of the game, a player is put into a'virtually infinite game world.'

Virtual reality was imagined as a human simulation technology long before the most recent wave of innovation that brought us the Oculus RIFT and the wave of innovation that followed. Now, rendering high framerate graphics using multiple, stereoscopic points in virtual reality is matching the speed and accuracy of robotic sensors and cameras. By modeling physics, motion, and material interactions, virtual reality is poised to become a simulation tool for training automatons - robots, drones, and diagnostic gear - before they need to perform in the real world. Recent advancements point to a potentially disruptive combination of virtual reality and artificial intelligence which will unlock a future with safe and competent intelligent machines, able to learn exponentially through self training and intelligent, realistic simulations. Ongoing academic work in machine learning and virtual reality have been migrating to corporations and startups through open source initiatives and movement of skilled people through the academic, startup, and corporate workplaces.

StarCraft players are safe – but not for long. The machines that made short work of chess, Scrabble and Go are beginning to set their sights on the venerable video game. And while the inherent complexity of most video games makes them a much harder target for AI than board games, two new projects aim to show they are far from invulnerable. One is a training ground for artificial intelligences targeting StarCraft, opened today by the game's creator, Blizzard Entertainment, in collaboration with Google's AI company DeepMind. The other is an AI being developed by researchers in Denmark whose approach stands the first good chance of beating a human at the game.

"The Max Planck Society has created a scientific beacon of light here which beams far and wide, attracting both emerging and established scientists from all over the world," remarked Max Planck President Martin Stratmann. The new building, which houses all three of the Institute's departments, was constructed between September 2014 and March 2017. It was funded by the federal state of Baden-Württemberg's government which places great emphasis on research into intelligent systems: "With its Institute for Intelligent Systems in Tübingen and Stuttgart, the Max Planck Society has firmly established one of the key research fields in the digital transformation in Baden-Württemberg," indicated Minister-President Winfried Kretschmann. "The federal state has contributed € 41 million to the new building in Tübingen – this represents a sound investment which will help ensure that Baden-Württemberg remains a leading centre of research on artificial intelligence." The new building provides scientists with an outstanding environment in which to advance their theoretical and experimental research.

Amazon didn't acquire an iconic grocery store brand just for the quinoa: Whole Foods operates hundreds of retail data mines, and Amazon just married a world-class artificial intelligence team with one of the best sources of in-store consumer shopping data in the U.S. There are lots of reasons, to be sure, why Amazon would want to spend $13.7 billion on Whole Foods. But the quintessential online retailer has been trying to establish a physical store presence for a few years now, and with one big check, it will now control more than 400 sources of prime data on consumer behavior. Big-box grocery stores are easy sources of data on human purchasing behavior. Any modern retail outlet monitors activity such as customer flow through the aisles, brand affinity, and, of course, the customer loyalty cards that do as good a job of profiling a person as anything.

The only trouble: They didn't really know how to chat. As Facebook and so many other Silicon Valley players trumpet the benefits of software that can carry on a conversation--apps that book your plane flights or manage your bank account through SMS-like dialogue--the technology still lags behind. In recent years, using what are called deep neural networks, companies like Facebook, Google, and Microsoft have fashioned services that can reliably identify faces and objects in photos, recognize voice commands on smartphones, and translate from one language to another. But building bots that can truly carry on conversations is still proving elusive. It's an undertaking that requires a far more varied array of AI techniques; researchers are still trying to figure out how the different approaches all fit together, or whether they'll really work at all.

On Friday during the BlizzCon 2016 opening keynote, Blizzard revealed that it teamed up with Google to provide an application programming interface (API) for DeepMind to be used in StarCraft II. This will enable artificial intelligence (AI) and Machine Learning researchers from around the world to create intelligent "bots" to play the game. In return, the knowledge gained while playing will be used in real-world applications. "An agent that can play StarCraft will need to demonstrate effective use of memory, an ability to plan over a long time, and the capacity to adapt plans based on new information," said research scientist Oriol Vinyals of the DeepMind team. "Computers are capable of extremely fast control, but that doesn't necessarily demonstrate intelligence, so agents must interact with the game within limits of human dexterity in terms of'Actions Per Minute.'"