NVIDIA brings fresh AI power to regular computers with its NIM microservices, which are available right away. Their AI Blueprints will arrive within weeks, making artificial intelligence much easier to use. These tools run smoothly on NVIDIA RTX platforms, including the latest GeForce RTX 50 Series and the brand-new Blackwell RTX PRO graphics cards. Anyone can download these AI packages without much hassle.
NVIDIA also released a test version of System Assistant under Project G-Assist today. This feature shows how AI helpers can improve apps and games. People can speak commands or type them to check system health, improve performance, and control various parts of their computer. Those who know coding can add new abilities through simple plug-ins, and there's even a tool that builds these plug-ins automatically.
We're seeing a huge boom in AI right across the computing world. Research teams keep creating amazing models, and developers everywhere are building tools that use this technology. NIM microservices, AI Blueprints, and G-Assist help bring these advances to regular computers. NVIDIA plans to share more updates through their RTX AI Garage blog series.
AI technology has moved incredibly fast, but many computer users still find it hard to adopt it. Setting up AI models requires lots of technical work—picking model versions, handling data correctly, making everything run efficiently, and connecting to special software interfaces. This takes serious effort and slows down how quickly people adopt AI.
NVIDIA designed NIM microservices to fix this problem. These ready-made AI packages come fully optimized and connect easily to standard programming interfaces. They run perfectly on RTX-powered computers and include popular community models plus NVIDIA's original creations. The services cover many AI types, such as language models, vision systems, image creators, speech processors, search tools, PDF readers, and more.
Ten different NIM microservices already exist for RTX systems. These include language processors like Deepseek and Mistral, image generators like Flux.dev, audio systems like Riva Parakeet, search tools, and computer vision programs like CLIP and YOLO. Many popular AI software platforms already work with these services, making them easy to use.
People interested in AI can try AnythingLLM and ChatRTX, which both support NIM services. These user-friendly programs let anyone chat with AI and create personal assistants. They can even include your documents and data to help automate tasks. Developers have options like FlowiseAI and Langflow that offer visual interfaces requiring minimal coding knowledge.
Professional coders can use Microsoft VS Code AI Toolkit, CrewAI, and Langchain, which all work with NIM services. NVIDIA AI Blueprints give developers complete packages to build AI workflows locally. Each Blueprint includes code, sample data, documentation, and a demo app. Developers can change these Blueprints to fit their needs or create entirely new features.
The PDF to podcast Blueprint changes documents into audio content for learning anywhere. It pulls text, pictures, and tables from PDFs to create informative podcasts. Users can ask questions afterward for interactive discussions with AI hosts. The 3D-guided AI Blueprint gives artists better control when creating images with AI.
Artists find it hard to control image composition using just words. With this Blueprint, they can place simple 3D objects in programs like Blender to guide AI image creation. They might make 3D assets by hand or let AI generate them, arrange everything, and set up the camera view. Then, FLUX NIM creates high-quality images matching the 3D scene.
Microsoft worked with NVIDIA to bring special acceleration features to the Windows Subsystem for Linux. This makes it possible to run these optimized AI services on Windows computers. The same NIM microservice works everywhere - from personal computers to big data centers and cloud systems. You can start using NVIDIA NIM on RTX AI PCs by visiting build.nvidia.com.
An experimental version of System Assistant from Project G-Assist lets GeForce RTX desktop users control many computer settings through voice or text. Users can optimize game settings, check performance stats, and even control peripherals like lighting. Laptop support will arrive soon. Unlike cloud-based AI tools that require internet access and subscriptions, G-Assist runs directly on your GeForce RTX graphics card.
This means G-Assist responds quickly, costs nothing, and works offline. Several manufacturers already use this ACE technology, including MSI's AI Robot engine, Streamlabs Intelligent AI Assistant, and upcoming features in HP's Omen Gaming hub. Anyone can expand G-Assist by creating plug-ins that add new functions using NVIDIA's GitHub repository.
Developers define functions in simple formats and place files in specific folders for automatic loading. They can submit plug-ins to NVIDIA for review and possible inclusion. Current sample plug-ins include Spotify for music control and Google Gemini for complex conversations using free API keys. Users can follow GitHub instructions to make G-Assist plug-ins with a ChatGPT-based Plug-in Builder."
NVIDIA also released a test version of System Assistant under Project G-Assist today. This feature shows how AI helpers can improve apps and games. People can speak commands or type them to check system health, improve performance, and control various parts of their computer. Those who know coding can add new abilities through simple plug-ins, and there's even a tool that builds these plug-ins automatically.
We're seeing a huge boom in AI right across the computing world. Research teams keep creating amazing models, and developers everywhere are building tools that use this technology. NIM microservices, AI Blueprints, and G-Assist help bring these advances to regular computers. NVIDIA plans to share more updates through their RTX AI Garage blog series.
AI technology has moved incredibly fast, but many computer users still find it hard to adopt it. Setting up AI models requires lots of technical work—picking model versions, handling data correctly, making everything run efficiently, and connecting to special software interfaces. This takes serious effort and slows down how quickly people adopt AI.
NVIDIA designed NIM microservices to fix this problem. These ready-made AI packages come fully optimized and connect easily to standard programming interfaces. They run perfectly on RTX-powered computers and include popular community models plus NVIDIA's original creations. The services cover many AI types, such as language models, vision systems, image creators, speech processors, search tools, PDF readers, and more.
Ten different NIM microservices already exist for RTX systems. These include language processors like Deepseek and Mistral, image generators like Flux.dev, audio systems like Riva Parakeet, search tools, and computer vision programs like CLIP and YOLO. Many popular AI software platforms already work with these services, making them easy to use.
People interested in AI can try AnythingLLM and ChatRTX, which both support NIM services. These user-friendly programs let anyone chat with AI and create personal assistants. They can even include your documents and data to help automate tasks. Developers have options like FlowiseAI and Langflow that offer visual interfaces requiring minimal coding knowledge.
Professional coders can use Microsoft VS Code AI Toolkit, CrewAI, and Langchain, which all work with NIM services. NVIDIA AI Blueprints give developers complete packages to build AI workflows locally. Each Blueprint includes code, sample data, documentation, and a demo app. Developers can change these Blueprints to fit their needs or create entirely new features.
The PDF to podcast Blueprint changes documents into audio content for learning anywhere. It pulls text, pictures, and tables from PDFs to create informative podcasts. Users can ask questions afterward for interactive discussions with AI hosts. The 3D-guided AI Blueprint gives artists better control when creating images with AI.
Artists find it hard to control image composition using just words. With this Blueprint, they can place simple 3D objects in programs like Blender to guide AI image creation. They might make 3D assets by hand or let AI generate them, arrange everything, and set up the camera view. Then, FLUX NIM creates high-quality images matching the 3D scene.
Microsoft worked with NVIDIA to bring special acceleration features to the Windows Subsystem for Linux. This makes it possible to run these optimized AI services on Windows computers. The same NIM microservice works everywhere - from personal computers to big data centers and cloud systems. You can start using NVIDIA NIM on RTX AI PCs by visiting build.nvidia.com.
An experimental version of System Assistant from Project G-Assist lets GeForce RTX desktop users control many computer settings through voice or text. Users can optimize game settings, check performance stats, and even control peripherals like lighting. Laptop support will arrive soon. Unlike cloud-based AI tools that require internet access and subscriptions, G-Assist runs directly on your GeForce RTX graphics card.
This means G-Assist responds quickly, costs nothing, and works offline. Several manufacturers already use this ACE technology, including MSI's AI Robot engine, Streamlabs Intelligent AI Assistant, and upcoming features in HP's Omen Gaming hub. Anyone can expand G-Assist by creating plug-ins that add new functions using NVIDIA's GitHub repository.
Developers define functions in simple formats and place files in specific folders for automatic loading. They can submit plug-ins to NVIDIA for review and possible inclusion. Current sample plug-ins include Spotify for music control and Google Gemini for complex conversations using free API keys. Users can follow GitHub instructions to make G-Assist plug-ins with a ChatGPT-based Plug-in Builder."
