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Razer has shown off a long list of new hardware and apps at CES 2025, and one of the coolest is the new PC Remote Play feature coming to its free Razer Nexus mobile app. As the name implies, the new feature lets users stream gameplay directly from their PC to various mobile devices, including Android phones, iOS devices, and Razer's Edge gaming tablet.According to Razer's press release, the PC Remote Play feature is a free update for the Nexus App. You can scroll through a list of all the supported games installed on your PC and launch and play them directly in the Nexus app while on the go. Razer claims the feature will allow for "full graphical fidelity" while streaming, and it uses Razer Sensa HD Haptics to add rumble and other tactile feedback while playing. Razer is demoing the PC Remote Play feature at its booth for CES attendees, and the beta is expected to roll out to the Razer Nexus app soon.Razer PC Remote Play on Kishi UltraIn the meantime, it's worth upgrading your mobile cloud gaming setup with the Razer Kishi Ultra controller to take advantage of the new PC streaming feature. You can currently grab the controller for just $130 at Amazon (was $150). The device works with select Android phones, tablets, and Apple devices with a USB-C port, including the iPhone 15, iPhone 16, and iPad Mini a17 Pro. While the Kishi Ultra offers the most feature support, you'll be able to use the feature with other Razer mobile controllers, including the Kishi V2 and V2 Pro.Continue Reading at GameSpot

With CES 2025 in full swing, one of the more intriguing exhibits at the trade show is a proof-of-concept entertainment experience from Sony. The PlayStation company is currently showing off what a future gaming room could look and smell like, as it's demoing what is essentially the closest thing possible to a Star Trek holodeck. According to Sony, the Future Immersive Entertainment Concept combines Crystal LED panels, audio, haptics, scent, and atmospherics with a PlayStation game like The Last of Us to create an interactive experience. You could compare this to a 4D version of Duck Hunt but with people horribly mutated by a fictional cordyceps fungus instead of mallards, and we don't even want to know what rotting mushroom-monsters smell like in a world bereft of personal hygiene products.Visually, it's a convincing step into that bleak world thanks to the realistic graphics. This isn't the first time that Sony has revealed conceptual gaming hardware, as back in May 2024, the company showed off a high-tech PlayStation controller in a promotional video, teasing a radical departure from the standard DualSense device.Continue Reading at GameSpot

Sega and Ryu Ga Gotoku have released footage of the upcoming Virtua Fighter project, which was first shown at CES 2025. However, they made it clear that the footage is not actual gameplay, and that it's just "in-game" concept footage before development began.The quick 35-second video presents one stage that looks like a run-down city simply called The City, which is described as a "hotbed of vice, attracts both the wicked and desperate." The camera then pans out to show two characters fighting each other. Both of them are models of Akira, Virtua Fighter's mascot.A HUD with HP bars suddenly appear at the top and the two characters trade blows with each other before one of them kicks the other into a pile of boxes in a cinematic cutscene, ending the footage.Continue Reading at GameSpot

Hyper Light Breaker's Early Access release is nearly here, providing a sequel to indie darling Hyper Light Drifter after nearly a decade. Hyper Light Breaker will differ significantly from its predecessor, evolving not only aesthetic and gameplay aspects, but story and worldbuilding elements as well.

While romance is not everything in ConcernedApe's Stardew Valley, it's at least a significant contributor to the game's heart and soul, effectively encompassing a sizable portion of the "life" part of the farm life sim genre it calls home. Not only is it a great way to get to know many of Stardew Valley's NPCs on a deeper level, it's an opportunity for players to have the comfort of someone waiting at home for them after a long day's work, and even someone who helps out around the farm. In light of that, it's good news that ConcernedApe's upcoming chocolate confectionery store sim, Haunted Chocolatier, includes romance in its gameplay as well.

Despite only being around for around 30 years now, One Piece feels like its been around forever. With thousands of chapters and episodes worth of story to tell, One Piece feels like it could run forever. However, all stories must come to an end, and despite the scope of the series, One Piece is no different.

In the fast-evolving landscape of AI, its becoming increasingly important to develop models that can accurately simulate and predict outcomes in physical, real-world environments to enable the next generation of physical AI systems.Ming-Yu Liu, vice president of research at NVIDIA and an IEEE Fellow, joined the NVIDIA AI Podcast to discuss the significance of world foundation models (WFM) powerful neural networks that can simulate physical environments. WFMs can generate detailed videos from text or image input data and predict how a scene evolves by combining its current state (image or video) with actions (such as prompts or control signals).World foundation models are important to physical AI developers, said Liu. They can imagine many different environments and can simulate the future, so we can make good decisions based on this simulation.This is particularly valuable for physical AI systems, such as robots and self-driving cars, which must interact safely and efficiently with the real world.The AI Podcast NVIDIAs Ming-Yu Liu on How World Foundation Models Will Advance Physical AI Episode 240Why Are World Foundation Models Important?Building world models often requires vast amounts of data, which can be difficult and expensive to collect. WFMs can generate synthetic data, providing a rich, varied dataset that enhances the training process.In addition, training and testing physical AI systems in the real world can be resource-intensive. WFMs provide virtual, 3D environments where developers can simulate and test these systems in a controlled setting without the risks and costs associated with real-world trials.Open Access to World Foundation ModelsAt the CES trade show, NVIDIA announced NVIDIA Cosmos, a platform of generative WFMs that accelerate the development of physical AI systems such as robots and self-driving cars.The platform is designed to be open and accessible, and includes pretrained WFMs based on diffusion and auto-regressive architectures, along with tokenizers that can compress videos into tokens for transformer models.Liu explained that with these open models, enterprises and developers have all the ingredients they need to build large-scale models. The open platform also provides teams with the flexibility to explore various options for training and fine-tuning models, or build their own based on specific needs.Enhancing AI Workflows Across IndustriesWFMs are expected to enhance AI workflows and development in various industries. Liu sees particularly significant impacts in two areas:The self-driving car industry and the humanoid [robot] industry will benefit a lot from world model development, said Liu. [WFMs] can simulate different environments that will be difficult to have in the real world, to make sure the agent behaves respectively.For self-driving cars, these models can simulate environments that allow for comprehensive testing and optimization. For example, a self-driving car can be tested in various simulated weather conditions and traffic scenarios to help ensure it performs safely and efficiently before deployment on roads.In robotics, WFMs can simulate and verify the behavior of robotic systems in different environments to make sure they perform tasks safely and efficiently before deployment.NVIDIA is collaborating with companies like 1X, Huobi and XPENG to help address challenges in physical AI development and advance their systems.We are still in the infancy of world foundation model development its useful, but we need to make it more useful, Liu said. We also need to study how to best integrate these world models into the physical AI systems in a way that can really benefit them.Listen to the podcast with Ming-Yu Liu, or read the transcript.Learn more about NVIDIA Cosmos and the latest announcements in generative AI and robotics by watching the CES opening keynote by NVIDIA founder and CEO Jensen Huang, as well as joining NVIDIA sessions at the show.

Data is the fuel of AI applications, but the magnitude and scale of enterprise data often make it too expensive and time-consuming to use effectively.According to IDCs Global DataSphere1, enterprises will generate 317 zettabytes of data annually by 2028 including the creation of 29 zettabytes of unique data of which 78% will be unstructured data and 44% of that will be audio and video. Because of the extremely high volume and various data types, most generative AI applications use a fraction of the total amount of data being stored and generated.For enterprises to thrive in the AI era, they must find a way to make use of all of their data. This isnt possible using traditional computing and data processing techniques. Instead, enterprises need an AI query engine.What Is an AI Query Engine?Simply, an AI query engine is a system that connects AI applications, or AI agents, to data. Its a critical component of agentic AI, as it serves as a bridge between an organizations knowledge base and AI-powered applications, enabling more accurate, context-aware responses.AI agents form the basis of an AI query engine, where they can gather information and do work to assist human employees. An AI agent will gather information from many data sources, plan, reason and take action. AI agents can communicate with users, or they can work in the background, where human feedback and interaction will always be available.In practice, an AI query engine is a sophisticated system that efficiently processes large amounts of data, extracts and stores knowledge, and performs semantic search on that knowledge, which can be quickly retrieved and used by AI.An AI query engine processes, stores and retrieves data connecting AI agents to insights.AI Query Engines Unlock Intelligence in Unstructured DataAn enterprises AI query engine will have access to knowledge stored in many different formats, but being able to extract intelligence from unstructured data is one of the most significant advancements it enables.To generate insights, traditional query engines rely on structured queries and data sources, such as relational databases. Users must formulate precise queries using languages like SQL, and results are limited to predefined data formats.In contrast, AI query engines can process structured, semi-structured and unstructured data. Common unstructured data formats are PDFs, log files, images and video, and are stored on object stores, file servers and parallel file systems. AI agents communicate with users and with each other using natural language. This enables them to interpret user intent, even when its ambiguous, by accessing diverse data sources. These agents can deliver results in a conversational format, so that users can interpret results.This capability makes it possible to derive more insights and intelligence from any type of data not just data that fits neatly into rows and columns.For example, companies like DataStax and NetApp are building AI data platforms that enable their customers to have an AI query engine for their next-generation applications.Key Features of AI Query EnginesAI query engines possess several crucial capabilities:Diverse data handling: AI query engines can access and process various data types, including structured, semi-structured and unstructured data from multiple sources, including text, PDF, image, video and specialty data types.Scalability: AI query engines can efficiently handle petabyte-scale data, making all enterprise knowledge available to AI applications quickly.Accurate retrieval: AI query engines provide high-accuracy, high-performance embedding, vector search and reranking of knowledge from multiple sources.Continuous learning: AI query engines can store and incorporate feedback from AI-powered applications, creating an AI data flywheel in which the feedback is used to refine models and increase the effectiveness of the applications over time.Retrieval-augmented generation is a component of AI query engines. RAG uses the power of generative AI models to act as a natural language interface to data, allowing models to access and incorporate relevant information from large datasets during the response generation process.Using RAG, any business or other organization can turn its technical information, policy manuals, videos and other data into useful knowledge bases. An AI query engine can then rely on these sources to support such areas as customer relations, employee training and developer productivity.Additional information-retrieval techniques and ways to store knowledge are in research and development, so the capabilities of an AI query engine are expected to rapidly evolve.The Impact of AI Query EnginesUsing AI query engines, enterprises can fully harness the power of AI agents to connect their workforces to vast amounts of enterprise knowledge, improve the accuracy and relevance of AI-generated responses, process and utilize previously untapped data sources, and create data-driven AI flywheels that continuously improve their AI applications.Some examples include an AI virtual assistant that provides personalized, 24/7 customer service experiences, an AI agent for searching and summarizing video, an AI agent for analyzing software vulnerabilities or an AI research assistant.Bridging the gap between raw data and AI-powered applications, AI query engines will grow to play a crucial role in helping organizations extract value from their data.NVIDIA Blueprints can help enterprises get started connecting AI to their data. Learn more about NVIDIA Blueprints and try them in the NVIDIA API catalog.IDC, Global DataSphere Forecast, 2024.