2026-07-15 17:37
NVIDIA CUDA 13.3 introduces native support for carryless multiplication with the new clmad PTX instruction, benefiting NVIDIA Ampere and newer GPUs. This enhancement significantly boosts cryptographic workloads. For instance, GHASH achieves a throughput of ~6.3 TB/s, making it up to 18.8x faster than previous methods. These advancements support critical applications like AES-GCM for secure communications and zero-knowledge proofs. 🔒💻⚡️ #NVIDIA #CUDA #Cryptography #TechInnovation #GPUs
Source: Nvidia Developer Blog
Michelle Horton
2026-07-14 18:20
🌟 The NVIDIA Nemotron Model Reasoning Challenge engaged over 5,000 participants to explore techniques for enhancing AI reasoning accuracy. Teams utilized LoRA adapters and created synthetic datasets while sharing insights through discussions. Key strategies included validating training traces and developing targeted solvers. The challenge's structure emphasized practical workflows and efficient use of resources, revealing valuable lessons for improving reasoning performance. #AI #Kaggle...
Source: Nvidia Developer Blog
Elizabeth Goodman
2026-07-14 16:00
🚀 AI agents are transforming machine learning workflows by autonomously managing tasks like code inspection, experiment launches, and result analysis. In autoresearch, led by Andrej Karpathy, these agents automate AI model training. They translate goals into code, test hypotheses, and provide insights to researchers. This new approach utilizes NVIDIA NeMo and showcases capabilities like full-stack autonomy and goal-driven experimentation. #MachineLearning #AI #ReinforcementLearning #NVIDIA...
Source: Nvidia Developer Blog
Tanya Lenz
2026-07-14 16:00
Unlock the power of AI with NVIDIA Cosmos 3! 🚀 This article explores how autonomous coding agents can enhance vision reasoning models beyond 90% accuracy with minimal manual input. By integrating NVIDIA Cosmos 3 with TAO agent skills, developers can streamline tasks like data formatting and hyperparameter tuning. The results are impressive: using Low-Rank Adaptation, accuracy improved from 54.41% to 87.14% in one run! With TAO AutoML, peak accuracy reached 93.35%, completing what once took...
Source: Nvidia Developer Blog
Tanya Lenz
2026-07-13 19:00
🔍 Researchers are advancing quantum error correction (QEC) codes for fault-tolerant logical operations in quantum computers. Color Codes, though previously overlooked due to decoding challenges, are now back in focus. NVIDIA's Ising Decoder has improved logical error rates by over 347x, making these codes more viable for practical use. The Ising Decoding pipeline enhances efficiency and accuracy for QPU developers, paving the way for better quantum computing capabilities. #QuantumComputing...
Source: Nvidia Developer Blog
Elizabeth Goodman
2026-07-13 15:00
🌍 Understanding low-likelihood, high-impact events is crucial in fields like science, engineering, and finance. Traditional methods like Monte Carlo sampling can be inefficient for estimating these risks. 🔍 A new paper explores using guided diffusion models to improve probability estimates for rare climate events, specifically tropical storms. This approach addresses the challenge of oversampling in guided models. ⚙️ By using tools like NVIDIA cBottle, researchers can compute odds ratios that...
Source: Nvidia Developer Blog
Elizabeth Goodman
2026-07-12 01:08
Robotics foundation models are advancing rapidly, enabling tasks like picking and sorting through natural language instructions. 🤖 However, evaluating these models for real-world performance remains challenging. Current benchmarks often rely on similar visual data for training and testing, which can lead to misleading results. While simulation offers a testing ground, discrepancies between simulated and real-world environments complicate assessments. Techniques like Real2sim are being...
Source: Nvidia Developer Blog
Brad Nemire
2026-07-10 18:17
🚀 Large language model (LLM) training faces GPU memory limits that hinder compute efficiency. Key components like model weights and gradients compete for high-bandwidth memory (HBM). 📊 The article discusses host offloading in JAX, which alleviates HBM pressure by moving activations to pinned host memory during training. This method is particularly effective on NVIDIA Grace Blackwell systems, thanks to their high-speed connectivity. 🔍 Performance tests using MaxText workloads demonstrate the...
Source: Nvidia Developer Blog
Tanya Lenz
2026-07-10 16:41
Discover how kernel fusion can optimize GPU performance in NVIDIA CUDA! 🚀 This technique improves memory bandwidth and reduces kernel launch overhead by combining multiple GPU operations into a single kernel. This means less time wasted on memory transfers and faster execution. CUDA Graphs also play a role, capturing sequences of operations for efficient execution, though they don't fuse kernel bodies. Both methods can work together for enhanced performance. Learn more about applying these...
Source: Nvidia Developer Blog
Michelle Horton
2026-07-10 16:36
AI performance is determined by three key dimensions: 🔍 **Accuracy**: How well a model reasons and produces outputs. ⚡ **Throughput**: The number of tokens generated per second. ⏳ **Interactivity**: The responsiveness of the model, influenced by latency. Successful deployments must balance these dimensions. High accuracy is ineffective if responses are slow, and throughput without a good user experience falls short. This article explores how design choices impact throughput and interactivity...
Source: Nvidia Developer Blog
Elizabeth Goodman
2026-07-10 13:00
Unlock the potential of biomolecular structure prediction with the NVIDIA BioNeMo Agent Toolkit! 🌟 This toolkit enhances workflows for drug discovery and protein design by speeding up key processes like Multiple Sequence Alignment and co-folding inference. 🧬 With advanced acceleration on NVIDIA B300 and H100 GPUs, researchers can now efficiently handle large compound libraries and predict complex molecular assemblies. Discover how these innovations are transforming the field! #Biotechnology...
Source: Nvidia Developer Blog
Elizabeth Goodman
2026-07-09 19:40
Unlocking the potential of financial NLP, a new approach addresses the limitations of existing data. 📈 By leveraging synthetic data generation, researchers created 502,536 unique financial news headlines across 13 categories. This iterative pipeline utilized NVIDIA NeMo tools for structured generation and semantic deduplication. The process involved generating, filtering, and deduplicating headlines, ensuring diversity and relevance for trading research and risk modeling. Learn how to adapt...
Source: Nvidia Developer Blog
Elizabeth Goodman
2026-07-09 18:17
Unlock the potential of agentic systems with LangChain! 🤖 This article explores how to create a harness profile for the NVIDIA Nemotron 3 Ultra to enhance performance. It highlights the balance between accuracy and cost in agentic systems. Fine-tuning smaller models can improve efficiency, but requires expertise. Key developments include evaluation benchmarks and LangChain’s customizable agent harness profiles. Learn how to set up and validate your harness profile for optimal results! 📊💻...
Source: Nvidia Developer Blog
Michelle Horton
2026-07-09 18:10
NVIDIA has introduced the Vera CPU, enhancing AI factory throughput for agentic systems. These systems utilize multi-step workflows that integrate inference, tool use, and more. The Vera CPU plays a crucial role in optimizing performance by managing CPU tasks between model steps. Key metrics like sustained per-core performance under full load are vital for efficient operation. If CPU performance declines, it can impact reinforcement learning by increasing training times and slowing user...
Source: Nvidia Developer Blog
Michelle Horton
2026-07-09 17:15
Unlocking the power of molecular dynamics (MD) simulations is crucial for advancements in areas like drug discovery and material science. 🔬✨ The article discusses how GROMACS, a leading MD package, faces challenges with GPU-to-GPU communication, particularly due to CPU orchestration, which limits scalability. By adopting GPU-native communication through NVIDIA NVSHMEM, researchers can reduce CPU involvement, allowing for improved data transfer and better performance. This shift could...
Source: Nvidia Developer Blog
Michelle Horton
2026-07-08 16:05
Unlock the power of analytical workloads with GPU-accelerated Presto! 🚀 Presto is an open-source SQL engine that runs fast queries on large datasets. By utilizing NVIDIA GPUs, it offers low latency, enhancing user experience and productivity. This post showcases multi-GPU execution on NVIDIA's DGX B200 and GB200 NVL72, highlighting the impact of NVIDIA GPUDirect Storage for high I/O throughput. 📊 Learn how GPU-accelerated Presto achieves peak performance using NVIDIA cuDF algorithms and...
Source: Nvidia Developer Blog
Tanya Lenz
2026-07-08 15:00
Unlock the potential of agentic systems with LangChain! 🤖 This article explores how to create a harness profile for the NVIDIA Nemotron 3 Ultra to enhance performance. It highlights the balance between accuracy and cost in agentic systems. Fine-tuning smaller models can improve efficiency, but requires expertise. Key developments include evaluation benchmarks and LangChain’s customizable agent harness profiles. Learn how to set up and validate your harness profile for optimal results! 📊💻...
Source: Nvidia Developer Blog
Michelle Horton
2026-07-07 17:05
As humanoid robots advance, the demand for efficient development workflows is increasing. Building these robots is complex, often hindered by fragmented pipelines and manual integrations. 🤖 NVIDIA introduces the Isaac GR00T Development Platform, an open-source solution that connects all stages of the robotic development process. This platform aims to streamline tasks from data collection to deployment. 🔄 Explore how GR00T can accelerate humanoid robot development! 🚀 #NVIDIA #HumanoidRobots...
Source: Nvidia Developer Blog
Elizabeth Goodman
2026-07-07 17:00
🔧 Industrial machinery generates numerous alarms, often overwhelming technicians. Each alarm requires careful analysis, pulling historical context and determining proper procedures. This article explores an AI agent developed using NVIDIA NeMo libraries and Nemotron models. The agent analyzes alarms by gathering context, running checks, and issuing structured evidence packages for recommended actions. The challenge lies in the vast data from interconnected machines, making it difficult for...
Source: Nvidia Developer Blog
Tanya Lenz
2026-07-07 17:00
Unlocking the full potential of wireless spectrum is crucial for telecom operators. Over 30 years, over $240B has been invested in this resource in the US. 📶💰 NVIDIA's AI Aerial technology aims to enhance spectral efficiency through advanced algorithms, overcoming traditional compute constraints. Massive MIMO technology can now reach its full potential by effectively tracking users and managing interference. 🚀 This innovative approach focuses on GPU acceleration to optimize RAN performance...
Source: Nvidia Developer Blog
Michelle Horton
2026-07-07 15:10
NVIDIA has introduced the Vera CPU, enhancing AI factory throughput for agentic systems. These systems utilize multi-step workflows that integrate inference, tool use, and more. The Vera CPU plays a crucial role in optimizing performance by managing CPU tasks between model steps. Key metrics like sustained per-core performance under full load are vital for efficient operation. If CPU performance declines, it can impact reinforcement learning by increasing training times and slowing user...
Source: Nvidia Developer Blog
Michelle Horton
2026-07-06 21:44
Training large-scale LLMs presents significant infrastructure challenges, particularly with thousands of GPUs involved. Unscheduled interruptions can slow down processes, impacting Goodput, which measures the effective work completed. Elastic adaptation methods like dropping data replicas and fast checkpointing help manage GPU availability but may incur throughput losses. A recent paper introduces Nonuniform Tensor Parallelism (NTP) as a solution to minimize these losses, ensuring consistent...
Source: Nvidia Developer Blog
Michelle Horton
2026-07-02 21:25
AI is reshaping organizations, boosting productivity and innovation. Yet, concerns about data privacy and security can hinder adoption. 🤖🔒 NVIDIA Confidential Computing (CC) offers a solution, protecting enterprise data and model integrity during active use. Benchmark results show CC's performance is nearly identical to traditional methods, achieving up to 98% efficiency. 📊💡 #AISecurity #DataPrivacy #NVIDIA #Innovation #TechTrends
Source: Nvidia Developer Blog
Elizabeth Goodman
2026-07-01 17:04
Reinforcement learning (RL) is crucial for aligning language models, enhancing AI assistants through methods like RLHF and RLVR. Organizations are leveraging RL to create specialized agents for tasks such as customer support and data analysis. Open models like Nemotron allow for better control over data and deployment. This guide aids developers in implementing RL effectively, helping define success and improve agent performance. 🤖📊🔍 #ReinforcementLearning #AI #MachineLearning #LanguageModels...
Source: Nvidia Developer Blog
Elizabeth Goodman
2026-06-30 17:36
Unlock the potential of GPU-accelerated query engines with NVIDIA GQE! 🚀 NVIDIA's advancements, like high bandwidth memory and NVLink-C2C, address memory and I/O bandwidth limitations. This enables efficient data movement between CPUs and GPUs, enhancing query performance. Learn how GQE leverages NVIDIA technologies to optimize SQL execution on large datasets, focusing on data movement, compression, and performance improvement. #NVIDIA #GPU #DataQuery #TechInnovation #BigData
Source: Nvidia Developer Blog
Michelle Horton
2026-06-30 16:00
🚀 NVIDIA Ominverse NuRec transforms multisensor data into high-fidelity 3D environments for AV and robotics. These reconstructions enhance physical AI development, enabling engineers to analyze real-world scenarios efficiently. However, high fidelity comes with a heavy computational cost. NVIDIA Nsight Developer Tools are key to optimizing the NuRec pipeline, aiming for faster reconstruction times—ultimately targeting real-time performance. #NVIDIA #NuRec #3DReconstruction #AI #Optimization
Source: Nvidia Developer Blog
Tanya Lenz
2026-06-29 15:50
🚀 AI agents are evolving, moving beyond simple chat functions to perform tasks like inspecting code and querying internal systems. With this advancement, ensuring a secure and governed environment is crucial, as these agents can access sensitive enterprise data. The NVIDIA Secure Agent Workspace Reference Design emphasizes a new structure, where execution happens in a managed workspace, enhancing security and oversight. #AI #EnterpriseSecurity #NVIDIA #Automation #TechTrends
Source: Nvidia Developer Blog
Michelle Horton
2026-06-26 19:00
🚀 AI agents have evolved significantly over the past two years, transitioning from single-question responses to complex, multi-turn interactions and long-horizon planning. The NVIDIA AI-Q Blueprint serves as an open-source reference for developers, utilizing LangChain Deep Agents and the NVIDIA NeMo Agent Toolkit. It allows for both quick answers and detailed research reports. This guide details how to deploy AI-Q 2.0 on Oracle Cloud Infrastructure using Terraform and Helm, providing step-by-...
Source: Nvidia Developer Blog
Anurag Kuppala
2026-06-26 16:00
🚀 The new Nemotron 3 Ultra NVFP4 checkpoint is now optimized using NVIDIA Model Optimizer! As context windows expand, efficient movement of large model weights is crucial. Quantization, specifically NVFP4, compresses weights into a smaller format. This 4-bit floating point system offers significant performance gains. The Nemotron 3 Ultra achieves up to 5.9x higher inference throughput compared to GLM-5.1 while maintaining BF16 accuracy across nearly all benchmarks. This article details how to...
Source: Nvidia Developer Blog
Michelle Horton
2026-06-25 22:25
Unlock efficient resource binding with Vulkan's new descriptor heap feature! 🎮 This innovation simplifies how shaders access GPU resources, enhancing performance and aligning better with modern hardware. It’s especially beneficial for complex rendering tasks and dynamic texture indexing. Khronos offers comprehensive guides on using the descriptor heap API, and NVIDIA drivers support this feature to streamline development. Check out the descriptor heap sample in Nsight Graphics to start...
Source: Nvidia Developer Blog
Tanya Lenz
2026-06-25 18:56
🚀 Developers focused on real-time AI can benefit from DiffusionGemma, a new text generation model from Google DeepMind. This model generates tokens in parallel, increasing speed and efficiency. It can produce up to 1,000 tokens/sec on NVIDIA H100 GPUs, which enhances user experience while lowering costs. DiffusionGemma supports text and image modalities, with a total of 25.2B parameters. It's optimized for various NVIDIA platforms, making it versatile for different AI applications. #AI...
Source: Nvidia Developer Blog
Anu Srivastava
2026-06-25 18:11
🚀 NVIDIA has achieved a significant milestone in MLPerf Training v6.0, dominating all benchmarks submitted by the MLCommons consortium. The NVIDIA platform excelled with the fastest training times and highest performance across various tests, including new pretraining benchmarks like DeepSeek-V3 and GPT-OSS-20B. With up to 8,192 Blackwell GPUs working together, NVIDIA showcased the power of its GB300 NVL72 system, setting new records for time-to-train in complex workloads. #NVIDIA #MLPerf #AI...
Source: Nvidia Developer Blog
Farshad Ghodsian
2026-06-25 16:43
🚀 Generative AI workloads are expanding beyond single GPU capabilities. NVIDIA's TensorRT 11.0 introduces multi-device inference support, allowing developers to efficiently scale across multiple GPUs while maintaining key optimizations like kernel fusions and quantization. This feature enables high-performance deployments for edge devices and works seamlessly with Torch-TensorRT for massive model deployment. For optimal performance, TensorRT integrates with NVIDIA NCCL, enhancing distributed...
Source: Nvidia Developer Blog
Peter Kisfaludi
2026-06-25 16:38
KRAFTON has unveiled PUBG Ally, an innovative AI companion for PUBG: BATTLEGROUNDS. Unlike traditional NPCs, this co-playable character (CPC) uses NVIDIA ACE technology to interact dynamically with players. 🤖🎮 Powered by advanced language models, PUBG Ally can understand voice commands and adapt to game scenarios in real time. It entered public beta on June 17 and will be available in Arcade Mode until June 30. This new approach aims to enhance player experience with more responsive gameplay....
Source: Nvidia Developer Blog
Elizabeth Goodman
2026-06-24 16:30
🚗💡 BEV perception is gaining traction in autonomous vehicles and robotics. It simplifies multi-camera data into a unified top-down view, aiding in navigation and planning. BEV pooling is crucial for converting depth-aware features into a compact BEV tensor, but it can introduce latency issues. The article discusses BEVPoolV3, which optimizes this process on NVIDIA GPUs, detailing strategies for improving performance. #BEVPerception #NVIDIA #AI #AutonomousVehicles #Robotics
Source: Nvidia Developer Blog
John Yang
2026-06-23 16:30
Power costs significantly impact AI factory operations, accounting for 40% of overall expenses. Optimizing performance per watt is crucial for reducing token costs and enhancing revenue. ⚡️ NVIDIA leads in offering the lowest costs for AI inference and training through collaboration and innovative designs. Techniques like Mixture-of-Experts (MoE) models enhance energy efficiency without sacrificing performance. 🔍 Operators can leverage these insights to maximize efficiency and profit. 📈...
Source: Nvidia Developer Blog
Sachin Idgunji
2026-06-23 15:00
🚀 AI systems are evolving from single-turn interactions to complex multiagent workflows, making low-latency inference crucial. DFlash, an open-source lightweight model, enhances this process through speculative decoding. It enables block-parallel GPU work, improving inference performance by up to 15x on NVIDIA Blackwell. 📈 The research team has released 20 DFlash checkpoints on Hugging Face, facilitating developer workflows. DFlash is also being integrated into various NVIDIA GPU inference...
Source: Nvidia Developer Blog
Amr Elmeleegy
2026-06-23 13:30
🚀 AI scientists are transforming scientific computing by reading papers, writing code, and generating hypotheses. However, effective discovery in life sciences requires reliable tools. NVIDIA BioNeMo bridges this gap, offering an accelerated tool layer for biomolecular research. It provides agent-ready interfaces for seamless integration, ensuring AI scientists can utilize advanced models effectively. Learn more about how this technology is shaping research! 🔬💻 #NVIDIA #BioNeMo #LifeSciences...
Source: Nvidia Developer Blog
Kyle Tretina
2026-06-23 06:00
Telecom operators are increasingly integrating AI into their network operations, customer care, and back-office processes. However, many are still at the beginning stages of achieving full autonomy. 📈 Currently, automation in network operations mainly falls within Level 2–3 of TM Forum’s taxonomy, focusing on predefined solutions. To reach Levels 4–5, telecoms need autonomous agents that can interpret operator intent and make real-time decisions. 🤖 A strong autonomy platform is essential,...
Source: Nvidia Developer Blog
Amogh Dendukuri
2026-06-22 16:00
🚀 Exciting news for CUDA developers! The NVIDIA CUDA Core Compute Libraries (CCCL) now offer modern C++ abstractions, enhancing both C++ and Python development. Key features include parallel algorithms for common operations, cooperative algorithms for custom kernel development, and idiomatic abstractions for CUDA tasks. The new CCCL runtime introduces user-friendly C++ APIs for core functionalities like stream management and memory allocation, providing a safer and more convenient programming...
Source: Nvidia Developer Blog
Piotr Ciolkosz