Company · updated daily
Nvidia
As the dominant supplier of AI training hardware, Nvidia sits at the center of debates over compute concentration, US export controls to China, and market power — tracked here daily.
NVIDIA Vera Rubin Maximizes Intelligence per Dollar for Post-Training Workloads — a Key Metric for Agentic AI
Lowest cost per token from extreme codesign maximizes intelligence per dollar for post-training in the agentic era.
NVIDIA Nemotron 3 Embed Ranks #1 Overall on RTEB, Advancing Agentic Retrieval
Nvidia-backed Fireworks hits $17.5 billion valuation as companies pursue cheaper AI models
Fireworks once relied heavily on revenue from coding startup Cursor, but has diversified in the past year as more companies reach for lower-cost AI models.
NVIDIA Introduces New Jetson Thor Computers to Advance Mainstream Robotics and Edge AI
General-purpose robots and autonomous machines are moving from research labs to real-world mass-market deployment, creating demand for compact, power-efficient AI supercomputers capable of running foundation models at the edge. To meet that need, NVIDIA today introduced the T3000 and T2000, new modules based on the NVIDIA Thor architecture that enable mass-market robotics and edge AI […]
NVIDIA and Japan Bring Full-Stack AI and Robotics to Every Industry
Home to leading manufacturers, robotics pioneers, infrastructure builders and iconic gaming companies, of course, Japan is one of the world’s centers of AI — building across the full stack with NVIDIA technologies. This week NVIDIA and its partners in Japan are showcasing the AI ecosystem’s latest advancements. Check back here for updates.
Prime Intellect raises $130M at $1B valuation for its AI training platform
Artificial intelligence training startup Prime Intellect Inc. has raised $130 million in funding from a group of prominent investors. The consortium included Nvidia Corp.’s NVentures, Intel Capital and Dell Technologies Capital. They were joined by more than a dozen others, including Cloudflare Inc. Chief Executive Matthew Prince. Prime Intellect stated in its Tuesday funding announcement […] The post Prime Intellect raises $130M at $1B valuation for its AI training platform appeared first on Si
NVIDIA Nemotron Achieves Benchmark-Leading Performance With LangChain Deep Agents Harness
NVIDIA Nemotron 3 Ultra is offering leading performance at lower cost than top closed models with the largest and most widely adopted AI agent orchestration platform. LangChain tuned its Deep Agents harness for NVIDIA Nemotron 3 Ultra, achieving the highest accuracy among open models, while completing more tasks at higher throughput and running at 10x […]
AI Innovators Adopt NVIDIA Vera — Why Max Single-Threaded CPU at Scale Matters
Max single-threaded CPUs at scale are a new category of CPUs built for the agentic AI era. Across the creation and deployment of an agentic system, the CPU is on the critical path for reasoning, response time and learning. CPUs are the processor which executes the work the AI model commands: the tool calling, code […]
NVIDIA and Hugging Face Bring New Models and Frameworks to LeRobot for the Open Robotics Community
Open source AI has shown how quickly developers can innovate when models, data and tools are shared. Robotics has the same opportunity, but advancements in physical AI development can still be gated by costly and fragmented resources, from large datasets and robot foundation models to simulation, compute and validation tools. NVIDIA and Hugging Face are […]
NVIDIA and Partners Build in America, for America
NVIDIA and its partners are investing in American manufacturing, supply chains, energy grids and skilled workforces so the U.S. can produce the infrastructure needed for better healthcare, breakthrough scientific discovery, stronger industrial productivity and global technology leadership.
NVIDIA expands robotics hiring in China, opens roles in Beijing, Shanghai, and Shenzhen
US chipmaker NVIDIA announced a major recruitment drive for its robotics team, with openings across four core areas of embodied AI, simulation, deployment, and solution architecture. Positions are available in Beijing, Shanghai, and Shenzhen. According to NVIDIA, the embodied AI team will focus on key technologies and applications including dexterous manipulation, human body modeling using […]
NVIDIA BioNeMo Agent Toolkit Brings Accelerated AI to Life Sciences Researchers in Claude Science
Life sciences has entered an era of computational scale, and for more than a decade, NVIDIA has built the full GPU-accelerated computing stack — spanning hardware, frameworks, libraries, models, microservices and domain-specific tools — to help researchers run more sophisticated workflows and iterate faster. This week, Anthropic announced Claude Science, an AI workbench for science […]
Into the Omniverse: Three Workflows for Improving Vision AI Agent Accuracy With Synthetic Data and Fine-Tuning
Editor’s note: This post is part of Into the Omniverse, a series focused on how developers, 3D practitioners, and enterprises can transform their workflows using the latest advances in OpenUSD and NVIDIA Omniverse. Vision AI agents are becoming a practical way to automatically turn video data from the physical world into operational intelligence in factories, […]
Claude Meets Blackwell Ultra: Anthropic’s Models Now Run on NVIDIA GB300 in Azure
Anthropic’s Claude models in Microsoft Foundry — hosted on Microsoft Azure and running on NVIDIA GB300 Blackwell Ultra GPUs — are now generally available, giving Azure-native enterprises a powerful new way to build autonomous and domain-specific AI agents. As agentic AI continues to drive enterprise innovation and becomes more autonomous, organizations need access to computing […]
Open Models, Closed Environments: Palantir Brings Secure AI to US Agencies With NVIDIA Nemotron
Showcasing the importance of open source innovation in American AI, Palantir’s new intelligent engine — introduced today — uses NVIDIA Nemotron open models to serve the needs of U.S. government agencies. Open source software has long been a pillar of U.S. technology leadership. In 1969, DARPA connected four university computers — from UCLA, Stanford, UCSB […]
Subtitle-Aligned Fine-Tuning of Whisper for Swiss German ASR: Benchmark Contamination, Convention Mismatch, and an Honest Baseline at 25.6% WER (13.8% cWER)
We present a systematic study of fine-tuning OpenAI's Whisper large-v3 for Swiss German ASR, using 1,367 hours of broadcast speech paired with Standard German subtitles as weak supervision. Through 16 iterative training runs on an NVIDIA DGX Spark (Grace Blackwell, 128 GB unified memory, up to 1 PFLOP FP4), we compare LoRA and full fine-tuning of the 1.55B-parameter model, investigate hallucination root causes, and quantify the effect of data quality, subtitle alignment, and training strategy. O
DuQuant++: Fine-grained Rotation Enhances Microscaling FP4 Quantization
The MXFP4 microscaling format, which partitions tensors into blocks of 32 elements sharing an E8M0 scaling factor, has emerged as a promising substrate for efficient LLM inference, backed by native hardware support on NVIDIA Blackwell Tensor Cores. However, activation outliers pose a unique challenge under this format: a single outlier inflates the shared block scale, compressing the effective dynamic range of the remaining elements and causing significant quantization error. Existing rotation-b
Fanar 2.0: Arabic Generative AI Stack
We present Fanar 2.0, the second generation of Qatar's Arabic-centric Generative AI platform. Sovereignty is a first-class design principle: every component, from data pipelines to deployment infrastructure, was designed and operated entirely at QCRI, Hamad Bin Khalifa University. Fanar 2.0 is a story of resource-constrained excellence: the effort ran on 256 NVIDIA H100 GPUs, with Arabic having only ~0.5% of web data despite 400 million native speakers. Fanar 2.0 adopts a disciplined strategy of
Bielik-Minitron-7B: Compressing Large Language Models via Structured Pruning and Knowledge Distillation for the Polish Language
This report details the creation of Bielik-Minitron-7B, a compressed 7.35B parameter version of the Bielik-11B-v3.0 model, specifically optimized for European languages. By leveraging a two-stage compression methodology inspired by the NVIDIA Minitron approach, we combined structured hybrid pruning and knowledge distillation to reduce the model's parameter count by 33.4%, from 11.04B to 7.35B. We utilized the NVIDIA Model Optimizer for structural pruning and the NVIDIA NeMo Framework for logit-b