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CUDA-Q Enabled Resource Reduction for Quantum Clustering Algorithms

10 coreset representation of a 1K dataset with coresets as smaller and larger stars according to weight.Quantum computers can use the quantum properties of superposition, entanglement, and interference to generalize learnings and insights from data. Such quantum…10 coreset representation of a 1K dataset with coresets as smaller and larger stars according to weight.

Quantum computers can use the quantum properties of superposition, entanglement, and interference to generalize learnings and insights from data. Such quantum machine learning (QML) techniques will eventually run on quantum-accelerated supercomputers that combine the processing powers of CPUs, GPUs, and QPUs to solve some of the world’s most complex problems. Many QML algorithms offer…

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NVIDIA AI Workbench Simplifies Using GPUs on Windows

The word PLAY spelled out in wooden blocks on a blue background with a real hand and finger pressing a play button on a block at the end of the word.NVIDIA AI Workbench is a free, user-friendly development environment manager that streamlines data science, ML, and AI projects on your system of choice: PC,…The word PLAY spelled out in wooden blocks on a blue background with a real hand and finger pressing a play button on a block at the end of the word.

NVIDIA AI Workbench is a free, user-friendly development environment manager that streamlines data science, ML, and AI projects on your system of choice: PC, workstation, datacenter, or cloud. You can develop, test, and prototype projects locally on Windows, macOS, and Ubuntu and easily transfer development environments and computational work between systems (local and remote) to optimize cost…

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NVIDIA to Present Innovations at Hot Chips That Boost Data Center Performance and Energy Efficiency

A deep technology conference for processor and system architects from industry and academia has become a key forum for the trillion-dollar data center computing market. At Hot Chips 2024 next week, senior NVIDIA engineers will present the latest advancements powering the NVIDIA Blackwell platform, plus research on liquid cooling for data centers and AI agents
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Jamba 1.5 LLMs Leverage Hybrid Architecture to Deliver Superior Reasoning and Long Context Handling

AI21 Labs has unveiled their latest and most advanced Jamba 1.5 model family, a cutting-edge collection of large language models (LLMs) designed to excel in a…

AI21 Labs has unveiled their latest and most advanced Jamba 1.5 model family, a cutting-edge collection of large language models (LLMs) designed to excel in a wide array of generative AI tasks. These models are capable of creating content, summarizing and comparing documents, and extracting valuable insights from vast datasets. This mixture of experts (MoE) model takes advantage of the…

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Straight Out of Gamescom and Into Xbox PC Games, GeForce NOW Newly Supports Automatic Xbox Sign-In

Straight out of Gamescom, NVIDIA introduced GeForce NOW support for Xbox automatic sign-in, as well as Black Myth: Wukong from Game Science and a demo for the PC launch of FINAL FANTASY XVI from Square Enix — all available in the cloud today. There are more triple-A games coming to the cloud this GFN Thursday:
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Unsung Heroes of the Hugging Face Hub

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Build Efficient Recommender Systems with Co-Visitation Matrices and RAPIDS cuDF

Recommender systems play a crucial role in personalizing user experiences across various platforms. These systems are designed to predict and suggest items that…

Recommender systems play a crucial role in personalizing user experiences across various platforms. These systems are designed to predict and suggest items that users are likely to interact with, based on their past behavior and preferences. Building an effective recommender system involves understanding and leveraging huge, complex datasets that capture interactions between users and items.

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Google Cloud Run Adds Support for NVIDIA L4 GPUs, NVIDIA NIM, and Serverless AI Inference Deployments at Scale

NVIDIA and Google logos on a black background.Deploying AI-enabled applications and services presents enterprises with significant challenges:  Performance is critical as it directly shapes user…NVIDIA and Google logos on a black background.

Deploying AI-enabled applications and services presents enterprises with significant challenges: Addressing these challenges requires a full-stack approach that can optimize performance, manage scalability effectively, and navigate the complexities of deployment, enabling organizations to maximize AI’s full potential while maintaining operational efficiency and cost-effectiveness.

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Practical Strategies for Optimizing LLM Inference Sizing and Performance

An illustration of a chatbot.As the use of large language models (LLMs) grows across many applications, such as chatbots and content creation, it’s important to understand the process of…An illustration of a chatbot.

As the use of large language models (LLMs) grows across many applications, such as chatbots and content creation, it’s important to understand the process of scaling and optimizing inference systems to make informed decisions about hardware and resources for LLM inference. In the following talk, Dmitry Mironov and Sergio Perez, senior deep learning solutions architects at NVIDIA…

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Mistral-NeMo-Minitron 8B Foundation Model Delivers Unparalleled Accuracy

Last month, NVIDIA and Mistral AI unveiled Mistral NeMo 12B, a leading state-of-the-art large language model (LLM). Mistral NeMo 12B consistently outperforms…

Last month, NVIDIA and Mistral AI unveiled Mistral NeMo 12B, a leading state-of-the-art large language model (LLM). Mistral NeMo 12B consistently outperforms similarly sized models on a wide range of benchmarks. Today, we announce Mistral-NeMo-Minitron 8B, one of the most advanced open-access models in its size class. This model consistently delivers leading accuracy on nine popular…

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