Deploy AI Models to Production with NVIDIA NIM

In this video, we will look at NVIDIA Inference Microservice (NIM). NIM offers pre-configured AI models optimized for NVIDIA hardware, streamlining the transition from prototype to production. The key benefits, including cost efficiency, improved latency, and scalability. Learn how to get started with NIM for both serverless and local deployments, and see live demonstrations of models like Llama 3 and Google’s Polygama in action. Don’t miss out on this powerful tool that can transform your enterprise applications.
LINKS:
Nvidia NIM: nvda.ws/44u5KYH
Notebook: tinyurl.com/uhv73ryu
#deployment #nvidia #llms
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TIMESTAMP:
00:00 Deploying LLMs is hard!
00:30 Challenges in Productionizing AI Models
01:20 Introducing NVIDIA Inference Microservice (NIM)
02:17 Features and Benefits of NVIDIA NIM
03:33 Getting Started with NVIDIA NIM
05:25 Hands-On with NVIDIA NIM
07:15 Integrating NVIDIA NIM into Your Projects
09:50 Local Deployment of NVIDIA NIM
11:04 Advanced Features and Customization
11:39 Conclusion and Future Content
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[@henkhbit5748]

It would be nice to compare different hosting offerings, based on price, inference speed, flexibility, open-source LLM, rag, agent's support etc. Thanks for the video👍

[@kunalsoni7681]

fantastic demonstration

[@samketola919]

price details??

[@aa-xn5hc]

Super useful thanks. Your videos are the most useful, and super high quality

[@engineerprompt]

Thank you 😊

[@DarioLopezPadial]

What about the pricing?

[@sumitbindra]

If each NIM is a specific model, why do we need to specify the model again?

[@unclecode]

Great content. I wonder who could compete with them in AI infrastructure if they really invest in it. Btw, u gotta check out their speech-to-text model. It's real-time, super fast! It starts with a partial result, then uses context to fix it. Sadly, it's not available for development :(

[@engineerprompt]

I agree, interestingly enough they are taking both proprietary and open weight inference market. I havne't looked at their STT, are the weights available anywhere or its their API?

[@unclecode]

@@engineerprompt Well, as of now, I couldn't find any, neither api or weights.

[@MrDenisJoshua]

Can you tell us witch have a better price... Nvidia NIM or Massedcompute please ? Thanks for the video

[@engineerprompt]

For NIM, you will need to get an enterprise license for the whole year, and then you can run that on any cloud provider. Since massedcompute can be rented for hour/days it will be more economical

[@MrDenisJoshua]

@@engineerprompt Thanks a lot.

[@010O]

so running local without enterprise license is out of the question?

[@engineerprompt]

I think you do get a trial period.

[@JanBadertscher]

I'm pretty sure, the OSS community isn't happy to use a proprietary "open" format with "Nvidia" in it's name. A truly open alternative contanerized format will surely surface, with agnostic backends, with more than just nvidia's triton and tensor acceleration.