Spotlight: SLB and NVIDIA Collaborate on Generative AI Solutions for Energy
Global energy technology company SLB has announced the next milestone in its long-standing collaboration with NVIDIA to develop and scale generative AI...
Quickly Voice Your Apps with NVIDIA NIM Microservices for Speech and Translation
NVIDIA NIM, part of NVIDIA AI Enterprise, provides containers to self-host GPU-accelerated inferencing microservices for pretrained and customized AI models...
NVIDIA Presents AI Security Expertise at Leading Cybersecurity Conferences
Each August, tens of thousands of security professionals attend the cutting-edge security conferences Black Hat USA and DEF CON. This year, NVIDIA AI security...
Accelerating Oracle Database Generative AI Workloads with NVIDIA NIM and NVIDIA cuVS
The vast majority of the world's data remains untapped, and enterprises are looking to generate value from this data by creating the next wave of generative AI...
Optimizing Data Center Performance with AI Agents and the OODA Loop Strategy
For any data center, operating large, complex GPU clusters is not for the faint of heart! There is a tremendous amount of complexity. Cooling, power,...
Generate code with Abacus AI’s Dracarys Large Language Model
Dracarys, fine-tuned from Llama 3.1 70B and available from NVIDIA NIM microservice, supports a variety of applications, including data analysis, text...
Data loading is a critical aspect of deep learning workflows, whether you're focused on training or inference. However, it often presents a paradox: the need...
Spotlight: xpander AI Equips NVIDIA NIM Applications with Agentic Tools
Equipping agentic AI applications with tools will usher in the next phase of AI. By enabling autonomous agents and other AI applications to fetch real-time...
Constant Time Launch for Straight-Line CUDA Graphs and Other Performance Enhancements
CUDA Graphs are a way to define and batch GPU operations as a graph rather than a sequence of stream launches. A CUDA Graph groups a set of CUDA kernels and...
Streamlining Data Processing for Domain Adaptive Pretraining with NVIDIA NeMo Curator
Domain-adaptive pretraining (DAPT) of large language models (LLMs) is an important step towards building domain-specific models. These models demonstrate...
Post-Training Quantization of LLMs with NVIDIA NeMo and NVIDIA TensorRT Model Optimizer
As large language models (LLMs) are becoming even bigger, it is increasingly important to provide easy-to-use and efficient deployment paths because the cost of...
Generative models have been making big waves in the past few years, from intelligent text-generating large language models (LLMs) to creative image and...
Achieving State-of-the-Art Zero-Shot Waveform Audio Generation across Audio Types
Stunning audio content is an essential component of virtual worlds. Audio generative AI plays a key role in creating this content, and NVIDIA is continuously...
Low Latency Inference Chapter 1: Up to 1.9x Higher Llama 3.1 Performance with Medusa on NVIDIA HGX H200 with NVLink Switch
As large language models (LLMs) continue to grow in size and complexity, multi-GPU compute is a must-have to deliver the low latency and high throughput that...
