How NVIDIA NIM Microservices Are Revolutionizing AI Development on PCs
With emerging use cases such as digital humans, agents, podcasts, images, and video generation, generative AI is changing the way we interact with PCs. This paradigm shift calls for new ways of interfacing with and programming generative AI models. However, getting started can be daunting for PC developers and AI enthusiasts.
How NVIDIA NIM Works
Bringing AI to the PC poses unique challenges. The AI software stack is evolving rapidly from libraries and frameworks to SDKs and models. The number of combinations of this software stack is enormous, and any incompatibility with a single layer of this stack causes entire workflows to break. The unique constraints of making AI performant on the PC also require intricate resource management, stringent latency, and throughput requirements.
NIM helps address these challenges. NIM provides prepackaged, state-of-the-art AI models that are optimized for deployment across NVIDIA GPUs. The NIM microservice is packaged as a container to self-host accelerated microservices for pretrained and customized AI models. It is built with pre-optimized inference engines for NVIDIA GPUs, including NVIDIA TensorRT and TensorRT-LLM.
Get Started with NIM Microservices on the NVIDIA RTX AI PC
The new suite of NIM microservices for NVIDIA RTX AI PCs spans use cases such as LLMs, VLMs, image generation, speech, embedding models for RAG, PDF extraction, and computer vision.
There are several ways to get started with NIM microservices on the PC today:
- Download from the NVIDIA API Catalog
- Integrate with other frameworks
- Use NVIDIA RTX AI PC interfaces
NVIDIA API Catalog
Download, install, and run NIM microservices. Select your microservice, and choose Deploy. For Target environment, choose Windows on RTX AI PCs (Beta).
Integrate with Other Frameworks
Integrate with application development tools and frameworks, including low-code and no-code tools. With these native integrations, you can connect your workflows built on these frameworks to AI models running in NIM through industry-standard endpoints, enabling you to use the latest technology with a unified interface across cloud, datacenter, workstation, and PC.
Use NVIDIA RTX AI PC Interfaces
Experience NIM on NVIDIA RTX AI PCs through user-friendly interfaces. As an example, here’s how to use NIM with AnythingLLM:
Summary
For building and experimentation, get started with NVIDIA NIM on the NVIDIA RTX AI PC. Stay connected and up to date by joining the NVIDIA Developer Discord community. For technical support, visit the NVIDIA Developer Forums to get your questions answered.
FAQs
Q: What is NIM?
A: NIM is a suite of microservices for building and experimenting with generative AI models on PCs.
Q: What are the benefits of using NIM?
A: NIM provides prepackaged, state-of-the-art AI models optimized for deployment across NVIDIA GPUs, making it easier to build and experiment with generative AI models on PCs.
Q: How do I get started with NIM microservices on the NVIDIA RTX AI PC?
A: You can download NIM microservices from the NVIDIA API Catalog, integrate with other frameworks, or use NVIDIA RTX AI PC interfaces to get started.
Q: What are some examples of use cases for NIM microservices?
A: NIM microservices span use cases such as LLMs, VLMs, image generation, speech, embedding models for RAG, PDF extraction, and computer vision.
