NVIDIA introduces new RTX technology for AI assistants and digital humans on GeForce RTX laptops, including Project G-Assist for personalized in-game assistance, microservices for the ACE platform, and a toolkit for developers to customize and optimize AI models on RTX PCs.
- Revolutionary technology that will enhance AI assistants and digital humans on PCs
- Project G-Assist provides personalized assistance for gaming and in-app experiences
- Collaboration with Microsoft to bring new generative AI capabilities to Windows apps
nVidia has made an exciting announcement in the world of AI assistants and digital humans. The company has introduced new NVIDIA RTX technology that will power AI assistants and digital humans on the latest Geforce RTX AI Laptops. One of the highlights is Project G-Assist, an AI assistant technology demo that provides context-aware help for PC games and apps.
Project G-Assist is designed to enhance gaming and in-app experiences by offering personalized assistance. It takes voice or text inputs from players, along with contextual information from the game screen, and runs the data through AI vision models. These models enhance the contextual awareness and app-specific understanding of a large language model linked to a game knowledge database, generating tailored responses delivered as text or speech.
NVIDIA partnered with Studio Wildcard to showcase Project G-Assist with ARK: Survival Ascended. The AI assistant can answer questions about creatures, items, lore, objectives, difficult bosses, and more. It personalizes its responses to the player’s game session, making it a valuable tool for gamers.
In addition to Project G-Assist, NVIDIA also introduced the first PC-based NVIDIA NIM inference microservices for the NVIDIA ACE digital human platform. These microservices enable developers to reduce deployment times from weeks to minutes. They deliver high-quality inference running locally on devices for natural language understanding, speech synthesis, facial animation, and more.
Furthermore, NVIDIA is collaborating with Microsoft to bring new generative AI capabilities to Windows native and web apps. This collaboration will provide developers with easy API access to GPU-accelerated small language models (SLMs) that enable retrieval-augmented generation (RAG) capabilities. These AI capabilities will be accelerated by NVIDIA RTX GPUs, providing fast and responsive AI experiences across the Windows ecosystem.
To assist developers in building application-specific AI models that run on PCs, NVIDIA is introducing the RTX AI Toolkit. This suite of tools and SDKs allows developers to customize, optimize, and deploy models on RTX AI PCs. Developers can use open-source QLoRa tools to customize pretrained models and the NVIDIA TensorRT model optimizer to quantize models for up to 3x less RAM consumption. The result is up to 4x faster performance compared to pretrained models.
The RTX AI Toolkit also includes the NVIDIA AI Inference Manager SDK, which simplifies the deployment of ACE to PCs. It preconfigures the PC with the necessary AI models, engines, and dependencies while orchestrating AI inference seamlessly across PCs and the cloud.
NVIDIA is also integrating RTX AI acceleration into apps for creators, modders, and video enthusiasts. The company is expanding its RTX Remix platform, which allows for remastering classic games with Ray Tracing, DLSS, and physically accurate materials. The RTX Remix Toolkit will be made open source, allowing modders to streamline asset replacement and scene relighting. Additionally, NVIDIA is making the capabilities of the RTX Remix Toolkit accessible via a REST API, enabling integration with digital content creation tools and modding tools.
In the world of video editing, NVIDIA’s RTX Video, an AI-powered super-resolution feature, is now available as an SDK to all developers. This feature helps upscale, sharpen, reduce compression artifacts, and convert standard dynamic range files into HDR. Video editing software such as Blackmagic Design’s DaVinci Resolve and Wondershare Filmora will soon integrate RTX Video, allowing video editors to enhance their projects.
Overall, NVIDIA’s latest RTX technology advancements are set to revolutionize AI assistants and digital humans on PCs. With Project G-Assist, NVIDIA ACE, and the RTX AI Toolkit, developers and users can expect improved gaming experiences, faster deployment times, and enhanced AI capabilities.
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Background Information
About Microsoft:
Microsoft, founded by Bill Gates and Paul Allen in 1975 in Redmond, Washington, USA, is a technology giant known for its wide range of software products, including the Windows operating system, Office productivity suite, and cloud services like Azure. Microsoft also manufactures hardware, such as the Surface line of laptops and tablets, Xbox gaming consoles, and accessories.Latest Articles about Microsoft
About nVidia:
NVIDIA has firmly established itself as a leader in the realm of client computing, continuously pushing the boundaries of innovation in graphics and AI technologies. With a deep commitment to enhancing user experiences, NVIDIA's client computing business focuses on delivering solutions that power everything from gaming and creative workloads to enterprise applications. for its GeForce graphics cards, the company has redefined high-performance gaming, setting industry standards for realistic visuals, fluid frame rates, and immersive experiences. Complementing its gaming expertise, NVIDIA's Quadro and NVIDIA RTX graphics cards cater to professionals in design, content creation, and scientific fields, enabling real-time ray tracing and AI-driven workflows that elevate productivity and creativity to unprecedented heights. By seamlessly integrating graphics, AI, and software, NVIDIA continues to shape the landscape of client computing, fostering innovation and immersive interactions in a rapidly evolving digital world.Latest Articles about nVidia
Technology Explained
DLSS: DLSS (Deep Learning Super Sampling) is an advanced AI-powered technology developed by NVIDIA that enhances real-time graphics rendering in video games and applications. DLSS utilizes deep learning algorithms to upscale lower-resolution images in real-time, resulting in higher-quality visuals while maintaining optimal performance. By harnessing the power of AI and deep neural networks, DLSS effectively boosts frame rates and image quality, enabling gamers to experience smoother gameplay and more immersive graphics without sacrificing computational efficiency. This technology has gained widespread recognition for its ability to deliver impressive visual fidelity and improved performance simultaneously, revolutionizing the way modern computer graphics are processed and displayed.
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Geforce: Geforce is a line of graphics processing units (GPUs) developed by Nvidia. It is the most popular GPU used in the computer industry today. Geforce GPUs are used in gaming PCs, workstations, and high-end laptops. They are also used in virtual reality systems, artificial intelligence, and deep learning applications. Geforce GPUs are designed to deliver high performance and power efficiency, making them ideal for gaming and other demanding applications. They are also capable of rendering high-resolution graphics and providing smooth, realistic visuals. Geforce GPUs are used in a variety of applications, from gaming to professional workstations, and are the preferred choice for many computer users.
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GPU: GPU stands for Graphics Processing Unit and is a specialized type of processor designed to handle graphics-intensive tasks. It is used in the computer industry to render images, videos, and 3D graphics. GPUs are used in gaming consoles, PCs, and mobile devices to provide a smooth and immersive gaming experience. They are also used in the medical field to create 3D models of organs and tissues, and in the automotive industry to create virtual prototypes of cars. GPUs are also used in the field of artificial intelligence to process large amounts of data and create complex models. GPUs are becoming increasingly important in the computer industry as they are able to process large amounts of data quickly and efficiently.
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HDR: High Dynamic Range (HDR) is a technology used to create images and videos with a greater range of luminance levels than what is possible with standard digital imaging. It allows for a greater range of colors and details to be captured in an image, resulting in a more realistic and vibrant look.
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Ray Tracing: Ray tracing is an advanced rendering technique used in computer graphics to simulate the way light interacts with objects in a virtual environment. It traces the path of light rays as they travel through a scene, calculating how they interact with surfaces, materials, and lighting sources. By simulating the complex behaviors of light, ray tracing produces highly realistic and accurate visual effects, including lifelike reflections, shadows, and refractions. This technology enhances the overall visual quality of images and animations by accurately replicating how light behaves in the real world, resulting in a more immersive and visually stunning digital experience.
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