CompanyAnthropic3 recent entries31 Aug 2026Run NVIDIA BioNeMo NIM Microservices for Protein Structure Prediction in Claude ScienceNVIDIA’s BioNeMo Agent Toolkit integrates over a decade of life‑science models and libraries into agent-callable skills, and when combined with Claude Science and NVIDIA NIM microservices it allows AI→16 Sept 2026How to Use AI Agents to Prepare 3D Scenes for SimulationAgentic AI workflows using NVIDIA Omniverse libraries automate preparation of Blender scenes for robotics simulation by adding semantic labels, sensor definitions, physics properties and validating th
CompanyOpenAI1 recent entries14 Jul 2026Post-Train NVIDIA Cosmos 3 in One Day Using Agent SkillsNVIDIA Cosmos 3 was post‑trained in under a day using TAO agent skills and LoRA adapters, raising accuracy on the Woven Traffic Safety video QA dataset from 54.41 % to 93.35 %. The mixture‑of‑transfor
CompanyGoogle1 recent entries9 Apr 2026How to Accelerate Protein Structure Prediction at Proteome-ScaleNVIDIA, Google DeepMind, EMBL-EBI, and Seoul National University collaborated to extend the AlphaFold Protein Structure Database (AFDB) beyond monomeric structures to proteome-scale quaternary stru...
CompanyMeta5 recent entries23 Jun 2026Boost Inference Performance up to 15x on NVIDIA Blackwell Using DFlash Speculative DecodingDFlash is an open source block diffusion model for speculative decoding that significantly accelerates LLM inference on NVIDIA Blackwell GPUs by drafting entire token blocks in parallel and verifying →4 Aug 2026Generate Trajectories, Reasoning Traces, and Auto-Labels with NVIDIA Alpamayo 2 SuperNVIDIA Alpamayo 2 Super is a publicly available 34‑billion‑parameter vision–language–action model that merges a 32‑B Cosmos 3 Super Reasoner with a 2‑B action‑expert diffusion network. It produces uni→10 Aug 2026Run Local Agentic AI Workflows with Meta’s Muse Glimmer on NVIDIAMeta released Muse Glimmer, a 30‑billion‑parameter dense language model with a context window exceeding 120 K tokens, designed for local, long‑running agentic AI workloads. The model is optimized to r→1 Sept 2026How to Size GPUs for AI Inference and TCO Without OverspendingInference workloads fall into four use‑case buckets (Chatbots/Copilots, Agents, Content Generation, Translation), each with distinct token patterns that dictate the required GPU memory and compute. Si→1 Oct 2026Build Local AI Apps with C++ and NVIDIA TensorRT RTX SamplesThe Nvidia Deploy repository provides open‑source C++ samples that pair ONNX Runtime with the TensorRT RTX execution provider to accelerate local inference on Windows and Linux. It separates model exp
CompanyDeepSeek4 recent entries24 Apr 2026Build with DeepSeek V4 Using NVIDIA Blackwell and GPU-Accelerated EndpointsDevelopers can build with DeepSeek V4 through NVIDIA GPU-accelerated endpoints on build.nvidia.com, with hosted endpoints providing a fast way to prototype before moving to self-hosted deployment. Dee→21 Jul 2026Setting a World Record for MoE Pre-Training on NVIDIA GB300 NVL72The NVIDIA GB300 NVL72 platform set a world record by delivering 1,648 TFLOPs per GPU during the pre‑training of DeepSeek‑V3 671B, a mixture‑of‑experts (MoE) model. This achievement leveraged fifth‑ge→12 Aug 2026Serve Qwen3.8-2.4T-A95B, a 2.4T-Parameter Model, with Configurable Reasoning on NVIDIA GB300 NVL72Alibaba released the open‑weights Qwen3.8‑2.4T‑A95B (Qwen3.8‑Max), a fine‑grained mixture‑of‑experts model with 2.4 trillion parameters, hybrid full‑ and linear‑attention, a one‑million‑token context →14 Sept 2026Accelerating Dropless MoE Training in JAX with NVIDIA Transformer Engine**AI Knowledge‑Base Summary** NVIDIA’s Transformer Engine augments JAX for dropless Mixture‑of‑Experts (MoE) training, delivering a 10.4× throughput boost on NVIDIA GB200 GPUs and raising DeepSeek‑V3
CompanyNVIDIA8 recent entries6 Oct 2026How DOCA GPUNetIO Unifies GPU-Initiated Networking Across the NVIDIA Software StackDOCA GPUNetIO delivers a unified GPU‑directed networking (GDA‑KI) foundation that lets CUDA kernels drive Ethernet, RDMA, Verbs and DMA operations without the CPU entering the application path. It shi→6 Oct 2026Control How Your GPU Shares Work with Green ContextsIn CUDA 13.1 “green contexts” let applications explicitly partition a GPU’s execution resources—such as Streaming Multiprocessors (SMs) and work‑queue slots—within one process. By assigning dedicated →7 Oct 2026Validate AI Factory Changes with Digital Twins and AI AgentsNVIDIA DSX Air creates a node‑based digital twin that models an AI factory’s infrastructure and software interfaces, allowing agentic workflows to interrogate the virtual environment, run configuratio→7 Oct 2026The Machines that Make the MachinesNVIDIA’s Seattle Robotics Lab and Isaac engineering team created reusable robotic systems to automate GB300 tester‑tray assembly, achieving over 95 % success on busbar tasks with a 160‑second cycle ti→7 Oct 2026Scaling Decision Optimization to 100 Million Variables and Beyond with mPDLP in NVIDIA cuOptNVIDIA cuOpt’s Multi‑GPU Primal‑Dual Hybrid Gradient (mPDLP) solver distributes linear programming problems across NVLink‑connected GPUs, cutting per‑GPU peak memory by up to six times and handling up→7 Oct 2026Faster Scientific Image Analysis with NVIDIA cuPhotonNVIDIA cuPhoton is an open‑source CUDA‑X toolkit that keeps scientific image data on the GPU from ingestion through classification, providing modules such as xDataReader (direct FITS loading), xRep (a→8 Oct 2026Building Reliable Data Analytics Agents: Lessons from the KDD CupThe NVIDIA KGMON team secured second place in the KDD Cup 2026 Data Agents competition by building a constrained harness around a small fixed LLM, unifying heterogeneous data into an SQLite database w→8 Oct 20265 Steps to Create SimReady Assets for Robotics with Frontier AI ModelsNVIDIA’s SimReady Foundation provides a five‑step workflow to convert CAD models into simulation‑ready OpenUSD assets for robotics. The process imports an ABB YuMi robot from STEP files, applies visua