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Leveraging the NVIDIA CUDA compute platform, CUDA-X libraries will be able to expedite data processing across diverse data types #AI #GenAI https://lnkd.in/gCjCHJjd

B200 blows the H100 out of the water. B200 boasts 20 petaflops of AI compute compared to H100's 4 petaflops (at FP4 precision). That's a 4x improvement.

Have you ever heard of #Quantization? ⚡ Quantization can be compared to compressing a large file. When you have a large file, it takes longer to load and access because it has more data to process. Similarly, larger machine-learning models take longer to query because GPUs have to load more parameters from memory and perform more computations. Compressing the file reduces its size and makes it faster to load and access. Similarly, by applying quantization to machine learning models, we reduce their memory footprint and make them faster to run without compromising on their quality. 💡 This powerful technique can produce equivalent-quality models that generate 2.2 times more tokens per second than when running at full 16-bit precision while rigorously testing and evaluating the model quality. Check out this blog to explore two different quantization setups and the benefits of using both👇 #databricks #AI #LLM #machinelearning #genai

NVIDIA NIM Now Available on Hugging Face with Inference-as-a-Service https://lnkd.in/d2h6EypN Hugging Face has announced the launch of an inference-as-a-service capability powered by NVIDIA NIM. This new service will provide developers easy access to NVIDIA-accelerated inference for popular AI models......

Great news for data scientists! HP and NVIDIA are teaming up to supercharge your workflows! This collaboration brings NVIDIA's powerful CUDA-X libraries to HP AI workstations. This means significantly faster data processing for tasks like generative AI development. A key component is the NVIDIA RAPIDS cuDF library, which can dramatically speed up pandas, a widely used data manipulation tool. This translates to huge time savings without needing to rewrite any code! #HP #NVIDIA #AI #DataScience #GenerativeAI https://lnkd.in/epiikKAi

Even the best algorithm without a capable hardware is just a collection of text lines. That's why the arrival of the NVIDIA Blackwell platform is so exciting. This new and powerful tool enables even more cutting-edge industrial applications of AI. With potential for powering many exciting AI-based solutions 🤖, it's definitely worth keeping an eye on. Check out the NVIDIA Blackwell platform here: https://lnkd.in/d9jWgizs #nvida #blackwellplatform #aihardware

For a couple of reasons, but let's focus on CUDA. NVIDIA has invested heavily in the CUDA ecosystem, which includes a great set of development tools, libraries, and resources for developers. NSight and CUDNN (CUDA Deep Neural Network library) provide debugging, performance profiling, and machine learning capabilities, for this new world of AI. Their mature ecosystem makes CUDA a go-to choice for developers working on GPU-accelerated applications. #NVIDIA #CUDA #GPUS #AI #GENAI

🌐 Discover how NVIDIA Blackwell is revolutionising real-time Large Language Models (LLMs)! This cutting-edge technology enhances AI computations, paving the way for advancements across various industries. Learn about the impact and potential of Blackwell in this detailed article: https://lnkd.in/gAAWiAYk #TechInnovation #NVIDIA #FutureOfAI

Check out this post which shows how to utilize an Nvidia GPU in Red Hat OpenShift AI.

Good analysis of the Nvidia Blackwell 200 and Grace Blackwell 200 super chip , more flops more performance!! Getting ready for the next generation of AI services !