Of around 7,000 languages in the world, a tiny fraction are supported by AI language models. NVIDIA is tackling the problem with a new dataset and models that support the development of high-quality speech recognition and translation AI for 25 European languages — including languages with limited available data like Croatian, Estonian and Maltese. These
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Join us on Aug. 21 to see how NVIDIA NeMo Agent toolkit boosts multi-agent workflows with deep MCP integration.
Join us on Aug. 21 to see how NVIDIA NeMo Agent toolkit boosts multi-agent workflows with deep MCP integration.
Warhammer 40,000: Dawn of War – Definitive Edition is marching onto GeForce NOW, expanding the cloud gaming platform’s library to over 2,300 supported titles. Battle is just a click away, as the iconic real-time strategy game joins seven new releases this week. Commanders can prepare their squads and steel their nerves on any device —
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NVIDIA is partnering with the U.S. National Science Foundation (NSF) to create an AI system that supports the development of multimodal language models for advancing scientific research in the United States. The partnership supports the NSF Mid-Scale Research Infrastructure project, called Open Multimodal AI Infrastructure to Accelerate Science (OMAI). “Bringing AI into scientific research has
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If you’ve ever installed an NVIDIA GPU-accelerated Python package, you’ve likely encountered a familiar dance: navigating to pytorch.org, jax.dev,…
If you’ve ever installed an NVIDIA GPU-accelerated Python package, you’ve likely encountered a familiar dance: navigating to pytorch.org, jax.dev, rapids.ai, or a similar site to find the artifact built for your NVIDIA CUDA version. You then copy a custom pip, uv, or other installer command with a special index URL or special package name such as . This isn’t just an inconvenience…
Currently, one of the most compelling questions in AI is whether large language models (LLMs) can continue to improve through sustained reinforcement learning…
Currently, one of the most compelling questions in AI is whether large language models (LLMs) can continue to improve through sustained reinforcement learning (RL), or if their capabilities will eventually plateau. Developed by NVIDIA Research, ProRL v2 is the latest evolution of Prolonged Reinforcement Learning (ProRL), specifically designed to test the effects of extended RL training on…
As quantum processor unit (QPU) builders and algorithm developers work to create large-scale, commercially viable quantum supercomputers, they are increasingly…
As quantum processor unit (QPU) builders and algorithm developers work to create large-scale, commercially viable quantum supercomputers, they are increasingly concentrating on quantum error correction (QEC). It represents the greatest opportunity and the biggest challenge in current quantum computing research. CUDA-Q QEC aims to speed up researchers’ QEC experiments through the rapid…
Bringing together the world’s brightest minds and the latest accelerated computing technology leads to powerful breakthroughs that help tackle some of the biggest research problems. To foster such innovation, the NVIDIA Graduate Fellowship Program provides grants, mentors and technical support to doctoral students doing outstanding research relevant to NVIDIA technologies. The program, in its 25th
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The emergence of several new-frontier, open source models in recent weeks, including OpenAI’s gpt-oss and Moonshot AI’s Kimi K2, signals a wave of rapid LLM…
The emergence of several new-frontier, open source models in recent weeks, including OpenAI’s gpt-oss and Moonshot AI’s Kimi K2, signals a wave of rapid LLM innovation. Dynamo 0.4, available today, delivers new capabilities aimed at deploying such models at scale and with low cost. It focuses on performance, observability, and autoscaling based on service-level objectives (SLO). Key Dynamo 0.
Black Forest Labs’ FLUX.1 Kontext [dev] image editing model is now available as an NVIDIA NIM microservice. FLUX.1 models allow users to edit existing images with simple language, without the need for fine-tuning or complex workflows. Deploying powerful AI requires curation of model variants, adaptation to manage all input and output data, and quantization to
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