Search Results for "learning"
NVIDIA Advances ML in Manufacturing with CUDA-X Data Science
NVIDIA leverages CUDA-X data science to optimize chip manufacturing workflows, addressing challenges like dataset imbalance and enhancing model performance.
Exploring Open Source Reinforcement Learning Libraries for LLMs
An in-depth analysis of leading open-source reinforcement learning libraries for large language models, comparing frameworks like TRL, Verl, and RAGEN.
DeepSWE: Revolutionizing Coding Agents with Open-Source Reinforcement Learning
DeepSWE-Preview, an advanced coding agent, sets new benchmarks in open-source AI with a 59% success rate on SWE-Bench-Verified, showcasing state-of-the-art performance using reinforcement learning.
RAPIDS Introduces GPU Polars Streaming and Unified GNN API Enhancements
NVIDIA's RAPIDS suite version 25.06 unveils new features including GPU Polars streaming, a unified GNN API, and zero-code ML speedups, enhancing Python data science capabilities.
NVIDIA Unveils Data Flywheel Blueprint to Optimize AI Agents
NVIDIA introduces the Data Flywheel Blueprint, a workflow aimed at enhancing AI agents by reducing costs and improving efficiency using automated experimentation and self-improving loops.
NVIDIA NeMo-RL Utilizes GRPO for Advanced Reinforcement Learning
NVIDIA introduces NeMo-RL, an open-source library for reinforcement learning, enabling scalable training with GRPO and integration with Hugging Face models.
NVIDIA's CUTLASS 4.0: Advancing GPU Performance with New Python Interface
NVIDIA unveils CUTLASS 4.0, introducing a Python interface to enhance GPU performance for deep learning and high-performance computing, utilizing CUDA Tensors and Spatial Microkernels.
Enhancing ML Models in Semiconductor Manufacturing with NVIDIA CUDA-X
NVIDIA's CUDA-X Data Science libraries optimize feature engineering in semiconductor manufacturing, enhancing ML model performance and reducing ETL processing time by up to 40%.
OpenAI and NVIDIA Collaborate to Enhance AI with New Open Models
OpenAI and NVIDIA have launched new AI models optimized for NVIDIA's infrastructure, promising advancements in AI development and application across various industries.
Dynamo 0.4 Enhances AI Model Deployment with Faster Performance and Advanced Autoscaling
Dynamo 0.4 introduces significant advancements in AI model deployment, offering 4x faster performance, SLO-based autoscaling, and real-time observability, enhancing efficiency and scalability.
NVIDIA's Grace Hopper Superchip Revolutionizes XGBoost 3.0 for Terabyte-Scale Datasets
NVIDIA's latest Grace Hopper Superchip enhances XGBoost 3.0, enabling efficient processing of terabyte-scale datasets with improved speed and cost-effectiveness.
NVIDIA's ProRL v2 Advances LLM Reinforcement Learning with Extended Training
NVIDIA unveils ProRL v2, a significant leap in reinforcement learning for large language models (LLMs), enhancing performance through extended training and innovative algorithms.