Search Results for "llm"
NVIDIA and Outerbounds Revolutionize LLM-Powered Production Systems
NVIDIA and Outerbounds collaborate to streamline the development and deployment of LLM-powered production systems with advanced microservices and MLOps platforms.
NVIDIA Unveils Llama 3.1-Nemotron-70B-Reward to Enhance AI Alignment with Human Preferences
NVIDIA introduces Llama 3.1-Nemotron-70B-Reward, a leading reward model that improves AI alignment with human preferences using RLHF, topping the RewardBench leaderboard.
Llama 3.1 405B Achieves 1.5x Throughput Boost with NVIDIA H200 GPUs and NVLink
NVIDIA's latest advancements in parallelism techniques enhance Llama 3.1 405B throughput by 1.5x, using NVIDIA H200 Tensor Core GPUs and NVLink Switch, improving AI inference performance.
Enhancing Large Language Models with NVIDIA Triton and TensorRT-LLM on Kubernetes
Explore NVIDIA's methodology for optimizing large language models using Triton and TensorRT-LLM, while deploying and scaling these models efficiently in a Kubernetes environment.
Boosting LLM Performance on RTX: Leveraging LM Studio and GPU Offloading
Explore how GPU offloading with LM Studio enables efficient local execution of large language models on RTX-powered systems, enhancing AI applications' performance.
LangChain Celebrates Two Years: Reflecting on Milestones and Future Directions
LangChain marks its second anniversary, highlighting its evolution from a Python package to a leading company in LLM applications, and introduces LangSmith and LangGraph.
Exploring Model Merging Techniques for Large Language Models (LLMs)
Discover how model merging enhances the efficiency of large language models by repurposing resources and improving task-specific performance, according to NVIDIA's insights.
The Crucial Role of Communication in AI and LLM Development
Explore the significance of communication in AI and LLM applications, highlighting the importance of prompt engineering, agent frameworks, and UI/UX innovations.
NVIDIA Develops RAG-Based LLM Workflows for Enhanced AI Solutions
NVIDIA is advancing AI capabilities by developing RAG-based question-and-answer LLM workflows, offering insights into system architecture and performance improvements.
Optimizing LLMs: Enhancing Data Preprocessing Techniques
Explore data preprocessing techniques essential for improving large language model (LLM) performance, focusing on quality enhancement, deduplication, and synthetic data generation.
Innovative SCIPE Tool Enhances LLM Chain Fault Analysis
SCIPE offers developers a powerful tool to analyze and improve performance in LLM chains by identifying problematic nodes and enhancing decision-making accuracy.
NVIDIA's TensorRT-LLM Enhances AI Efficiency with KV Cache Early Reuse
NVIDIA introduces KV cache early reuse in TensorRT-LLM, significantly speeding up inference times and optimizing memory usage for AI models.