NVIDIA Unveils AI Innovations for Developers and Enthusiasts at CES
NVIDIA has unveiled a groundbreaking development in AI technology that promises to transform the way developers and enthusiasts work with AI agents and creative workflows on personal computers. Announced at CES, this initiative involves deploying advanced foundation models on NVIDIA RTX AI PCs. These models are designed to enhance digital humans, content creation, productivity, and development.
NVIDIA introduces these models as part of the NVIDIA NIM microservices, which are powered by the latest GeForce RTX 50 Series GPUs. These GPUs boast an impressive capability of performing up to 3,352 trillion operations per second and include 32GB of Video RAM (VRAM). They are built on the NVIDIA Blackwell architecture, marking a significant leap as the first consumer GPUs to support FP4 compute. This advancement doubles AI inference performance and allows generative AI models to operate locally with a smaller memory footprint than previous hardware generations.
A Brief History of GeForce and AI
The GeForce platform has been pivotal in the evolution of AI. The journey began in 2012 with the training of the first GPU-accelerated deep learning network, AlexNet, on the GeForce GTX 580. Fast forward to last year, over 30% of AI research papers cited the utilization of GeForce RTX, highlighting the platform’s continued significance in AI research and development.
With the advent of generative AI and RTX AI PCs, the opportunity for anyone to become a developer has expanded. A new wave of low-code and no-code tools, such as AnythingLLM, ComfyUI, Langflow, and LM Studio, are now available. These tools enable enthusiasts to integrate AI models into complex workflows through user-friendly graphical interfaces.
Seamless AI Integration with NIM Microservices
NVIDIA’s NIM microservices are designed to seamlessly integrate with these graphical interfaces, making it easier than ever to access and deploy the latest generative AI models. Built on NIM microservices, NVIDIA AI Blueprints offer pre-configured reference workflows that are easy to use for applications like digital humans and content creation.
To accommodate the rising demand from AI developers and enthusiasts, leading PC manufacturers and system builders are introducing NIM-ready RTX AI PCs equipped with GeForce RTX 50 Series GPUs.
"AI is evolving rapidly, from perception AI to generative AI and now agentic AI," stated Jensen Huang, founder and CEO of NVIDIA. "NIM microservices and AI Blueprints provide the necessary tools for PC developers and enthusiasts to explore the wonders of AI."
Understanding Foundation Models and Their Impact
Foundation models are neural networks trained on vast amounts of raw data, forming the cornerstone of generative AI. NVIDIA plans to release a series of NIM microservices for RTX AI PCs from top model developers, including Black Forest Labs, Meta, Mistral, and Stability AI. These services will cover an array of applications such as large language models (LLMs), vision language models, image generation, speech, embedding models for retrieval-augmented generation (RAG), PDF extraction, and computer vision.
"GeForce RTX 50 Series GPUs with FP4 compute will unlock a vast array of models that can now run on PCs, a capability previously limited to large data centers," explained Robin Rombach, CEO of Black Forest Labs. "By making FLUX an NVIDIA NIM microservice, we increase the speed at which AI can be deployed and experienced by users while delivering exceptional performance."
NVIDIA also introduced the Llama Nemotron family of open models, which are capable of achieving high accuracy across a diverse range of agentic tasks. The Llama Nemotron Nano model will be available as a NIM microservice for RTX AI PCs and workstations, excelling in agentic AI tasks such as following instructions, function calling, chatting, coding, and performing mathematical operations.
NIM Microservices: Empowering AI on PCs
NIM microservices encompass the key components necessary for running AI on PCs and are optimized for deployment across NVIDIA GPUs, whether in RTX PCs, workstations, or the cloud.
Developers and enthusiasts can quickly download, set up, and run these NIM microservices on Windows 11 PCs using the Windows Subsystem for Linux (WSL).
"AI is driving Windows 11 PC innovation at an unprecedented rate, and the Windows Subsystem for Linux (WSL) offers an excellent cross-platform environment for AI development on Windows 11 alongside Windows Copilot Runtime," said Pavan Davuluri, corporate vice president of Windows at Microsoft. "NVIDIA NIM microservices, optimized for Windows PCs, provide developers and enthusiasts with ready-to-integrate AI models for their Windows applications, further accelerating the deployment of AI capabilities to Windows users."
NIM microservices are compatible with leading AI development and agent frameworks, including AI Toolkit for VSCode, AnythingLLM, ComfyUI, CrewAI, Flowise AI, LangChain, Langflow, and LM Studio. Developers can connect applications and workflows built on these frameworks to AI models running NIM microservices through industry-standard endpoints, enabling them to utilize the latest technology with a unified interface across the cloud, data centers, workstations, and PCs.
Enthusiasts will also have the opportunity to experience a range of NIM microservices through an upcoming release of the NVIDIA ChatRTX tech demo.
Bringing a Human Touch to Agentic AI
To showcase how enthusiasts and developers can leverage NIM to build AI agents and assistants, NVIDIA has previewed Project R2X. This initiative involves a vision-enabled PC avatar that can provide information at a user’s fingertips, assist with desktop applications and video conference calls, read and summarize documents, and more.
The avatar is brought to life using NVIDIA RTX Neural Faces, a new generative AI algorithm that augments traditional rasterization with entirely generated pixels. The face is animated by a diffusion-based NVIDIA Audio2Face-3D model, which enhances lip and tongue movement. R2X can be connected to cloud AI services such as OpenAI’s GPT4o and xAI’s Grok, as well as NIM microservices and AI Blueprints, including PDF retrievers or alternative LLMs, via developer frameworks such as CrewAI, Flowise AI, and Langflow.
AI Blueprints: Expanding the Boundaries of Creativity
NIM microservices are also accessible to PC users through AI Blueprints—reference AI workflows that can operate locally on RTX PCs. These blueprints empower developers to create podcasts from PDF documents, generate captivating images guided by 3D scenes, and more.
The PDF to podcast blueprint extracts text, images, and tables from a PDF to create a podcast script that users can edit. It can also generate a complete audio recording from the script using voices available in the blueprint or based on a user’s voice sample. Additionally, users can engage in a real-time conversation with the AI podcast host to explore specific topics further.
The blueprint leverages NIM microservices such as Mistral-Nemo-12B-Instruct for language, NVIDIA Riva for text-to-speech and automatic speech recognition, and the NeMo Retriever collection of microservices for PDF extraction.
The AI Blueprint for 3D-guided generative AI gives artists greater control over image generation. While AI can produce stunning images from simple text prompts, managing image composition using only words can be challenging. With this blueprint, creators can use basic 3D objects arranged in a 3D renderer like Blender to guide AI image generation. Artists can create 3D assets by hand or generate them using AI, place them in the scene, and set the 3D viewport camera. A prepackaged workflow powered by the FLUX NIM microservice will use the current composition to generate high-quality images that align with the 3D scene.
Availability and Future Prospects
NVIDIA NIM microservices and AI Blueprints will be available starting in February, initially supporting GeForce RTX 50 Series, GeForce RTX 4090 and 4080, and NVIDIA RTX 6000 and 5000 professional GPUs. Additional GPUs will receive support in the future.
NIM-ready RTX AI PCs will be available from renowned manufacturers such as Acer, ASUS, Dell, GIGABYTE, HP, Lenovo, MSI, Razer, and Samsung, as well as local system builders like Corsair, Falcon Northwest, LDLC, Maingear, Mifcon, Origin PC, PCS, and Scan.
For more information about how NIM microservices, AI Blueprints, and NIM-ready RTX AI PCs are accelerating generative AI, consider joining NVIDIA at CES.
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