Generative AI-powered laptops and PCs are unlocking advancements in gaming, content creation, productivity, and development. Today, over 600 Windows apps and games are already running AI locally on more than 100 million GeForce RTX AI PCs worldwide, delivering fast, reliable, and low-latency performance.
At Microsoft Ignite, NVIDIA and Microsoft announced tools to help Windows developers quickly build and optimize AI-powered apps on RTX AI PCs, making local AI more accessible. These new tools enable application and game developers to harness powerful RTX GPUs to accelerate complex AI workflows for applications such as AI agents, app assistants, and digital humans.
### RTX AI PCs Power Digital Humans With Multimodal Small Language Models
Meet James, an interactive digital human knowledgeable about NVIDIA and its products. James uses a collection of NVIDIA NIM microservices, NVIDIA ACE, and ElevenLabs digital human technologies to provide natural and immersive responses.
NVIDIA ACE is a suite of digital human technologies that brings life to agents, assistants, and avatars. To achieve a higher level of understanding so that they can respond with greater context-awareness, digital humans must be able to visually perceive the world like humans do.
### Enhancing Digital Human Interactions
Enhancing digital human interactions with greater realism demands technology that enables perception and understanding of their surroundings with greater nuance. To achieve this, NVIDIA developed multimodal small language models that can process both text and imagery, excel in role-playing, and are optimized for rapid response times.
The NVIDIA Nemovision-4B-Instruct model, soon to be available, uses the latest NVIDIA VILA and NVIDIA NeMo framework for distilling, pruning, and quantizing to become small enough to perform on RTX GPUs with the accuracy developers need.
### Turbocharge Gen AI With NVIDIA TensorRT Model Optimizer for Windows
When bringing models to PC environments, developers face the challenge of limited memory and compute resources for running AI locally. And they want to make models available to as many people as possible, with minimal accuracy loss.
Today, NVIDIA announced updates to NVIDIA TensorRT Model Optimizer (ModelOpt) to offer Windows developers an improved way to optimize models for ONNX Runtime deployment.
### Conclusion
Generative AI-powered laptops and PCs are unlocking advancements in gaming, content creation, productivity, and development. With the introduction of new tools and technologies, developers can now harness the power of RTX AI PCs to accelerate complex AI workflows and create more realistic digital humans.
