Results for “Develop Autonomous Robots”

Develop robots that perceive, plan and act in changing surroundings by training and testing their behavior in simulation, then running perception and control on an onboard edge computer.

Combine a physically accurate digital twin of the plant, vision AI on the line and simulation-trained robots to plan layouts, catch defects and test changes before they reach the real factory floor.

Run AI models on devices close to where data is created, such as cameras, machines, robots and medical equipment, for low latency, limited connectivity or data that should not leave the site.

A simulation of a warehouse's layout, robots, people and flows used to test slotting, fleet sizes and safety rules, and to train and check the AI that runs on site, before anything changes in the real building.

Plan, build and run a dedicated GPU cluster for training, fine-tuning and inference, treating compute, network, storage, power, cooling, scheduling and day-two operations as one system rather than separate purchases.

An assistant that answers staff questions from internal documents and shows its sources, while prompts and data stay under company control. The usual pattern is retrieval over your own content, a served language model, guardrails and permission-aware access.

Build AI agents that plan multi-step tasks, call tools and company systems and report back, with evaluation, guardrails and tracing so their behavior can be measured, limited and improved over time.

Apply AI to medical imaging, genomics, drug discovery and medical devices with open frameworks and GPU tools, while keeping patient data governed and treating clinical validation and regulatory approval as part of the project.

The stack for robots that perceive and act: Isaac Sim and Isaac Lab for simulation and robot learning, Isaac GR00T for humanoids, Isaac ROS for ROS 2, Cosmos world foundation models and Jetson computers on the robot.

NVIDIA's automotive stack: DRIVE AGX in-vehicle computers, DriveOS, the Hyperion reference architecture, the Halos safety framework, Alpamayo open driving models, and Cosmos and Omniverse for simulation and validation.

Tools for building physically accurate virtual copies of factories, warehouses, data centers and products: Omniverse libraries, the OpenUSD open standard, DSX simulation for AI factories, Isaac Sim for robots and Cosmos models for synthetic data.

AI and simulation for weather, climate, engineering and AI data center energy: Earth-2 open weather models and Earth2Studio, PhysicsNeMo (formerly Modulus) for physics AI, and DSX MaxLPS and DSX Flex for power use in AI factories.

Computers and software for AI outside the data center: Jetson modules for robots and devices, IGX for industrial and medical systems with functional safety, Holoscan for real-time sensor processing, and JetPack.

Systems and software for building and running large GPU clusters: DGX systems and SuperPOD designs, Mission Control for operations, Run:ai for GPU scheduling, AI Enterprise for the software layer and the DSX platform for designing and powering AI factories.

Software that serves trained models at a target latency and cost: Dynamo for distributed generative AI serving, Dynamo-Triton (formerly Triton Inference Server), TensorRT LLM for model optimization, NIM packaging and AIPerf benchmarking.

The networks that let many GPUs act together: NVLink inside the rack, Spectrum-X Ethernet and Quantum InfiniBand between racks, BlueField DPUs and ConnectX SuperNICs in each server, and DSX Air for testing a network design in simulation.

Controls for isolating and observing AI workloads on NVIDIA platforms: BlueField DPUs with DOCA and DOCA Argus, GPU confidential computing with attestation, and the OpenShell runtime for containing AI agents.

The base layer for programming NVIDIA GPUs: the CUDA Toolkit, CUDA-X libraries, Nsight profilers and debuggers, the NGC software catalog and AI Workbench for managing project environments.

Software for building, customizing, deploying and governing AI assistants and agents in a company: Nemotron open models, NIM microservices, the NeMo libraries, AI Blueprints reference code, the OpenShell agent runtime and the AI Enterprise support layer.

The processors behind NVIDIA systems: the Blackwell and Vera Rubin GPU architectures, Grace and Vera CPUs, RTX PRO GPUs for mixed AI and graphics work, and the NVLink interconnect that joins GPUs into larger systems.

Consumer and creator technology on GeForce RTX: DLSS neural rendering, RTX Remix for remastering classic games, NVIDIA ACE for Games for AI characters, the Broadcast app and Studio Drivers.

Accelerated tools for genomics, drug discovery, medical imaging and medical devices: Parabricks, BioNeMo, the community MONAI framework, Holoscan for real-time device data and Nemotron models for digital health.

Accelerated computing for science and engineering: the HPC SDK compilers and libraries, CUDA-X, CUDA-Q for quantum research, PhysicsNeMo for physics AI, and Grace CPUs with HGX and DGX systems.

GPU workflows for film, TV, live media and advertising: RTX PRO GPUs for rendering and virtual production, Omniverse for 3D pipelines, the Video Codec SDK for encoding and decoding, and AI references for localization and custom studio models.

Programs and resources rather than products: NVIDIA Inception for startups, the Deep Learning Institute for training and certificates, the free NVIDIA Developer Program, the NGC catalog and AI Blueprints reference code.

Video analytics for cities, factories, stores and warehouses: the Metropolis platform, DeepStream pipelines, the video search and summarization blueprint, TAO model customization, and Jetson or RTX PRO hardware for deployment.

NVIDIA Isaac is an open robotics development platform: simulation and robot learning frameworks (Isaac Sim, Isaac Lab), CUDA-accelerated ROS 2 packages (Isaac ROS), robot foundation models (Isaac GR00T) and reference workflows for building mobile robots, robot arms and humanoids.

NVIDIA Cosmos is an open platform of world foundation models and tools for physical AI. Cosmos 3 reasons over images and video and generates video, sound and robot actions; Curator, Evaluator and Cosmos Framework cover data, scoring and post-training. Licenses differ by model (OpenMDW 1.1 for Cosmos 3).

NVIDIA Jetson is a family of compact computer modules and developer kits with NVIDIA GPUs for running AI inside robots, drones, cameras and other edge devices. It spans entry modules up to the Blackwell-based Jetson Thor series and runs the JetPack software stack.

NVIDIA AI Enterprise is a commercial, supported software suite that bundles NVIDIA's AI frameworks, NIM microservices and SDKs with GPU drivers, Kubernetes operators and Run:ai orchestration, adding release branches, security patching and SLA-backed support for production AI.

AI Workbench is NVIDIA's free tool for running containerized, Git-managed AI projects on a laptop, a GPU workstation, a remote server or a cloud instance with the same interface. It handles containers, GPU drivers and remote connections; the latest release, 2026.06.5, shipped in July 2026.

BioNeMo is NVIDIA's development platform for AI in biology and drug discovery: open models, training recipes, libraries, NIM microservices and, since June 2026, an agent toolkit. The older BioNeMo Framework container is archived; NVIDIA now points users to BioNeMo Recipes on GitHub.

NVIDIA Blueprints are open reference workflows for agentic and generative AI use cases such as retrieval-augmented generation, video search and summarization, and research agents. Each provides sample code, deployment files and documentation built on NIM microservices and other NVIDIA libraries, meant to be adapted.

NVIDIA DGX is NVIDIA's own line of AI systems, from the DGX Spark desktop to rack-scale DGX SuperPOD clusters, delivered together with NVIDIA operations software, reference architectures and support, so an organization can build AI infrastructure on one validated stack.

NVIDIA DSX is a platform, not a single product: a set of reference designs, simulation tools, open-source operations software, power management and data-exchange schemas for designing, building and running AI factories, with each part usable by different partners in the build.

Deutsche Telekom opened its Industrial AI Cloud in Munich on 4 February 2026, with nearly 10,000 NVIDIA Blackwell GPUs in DGX B200 systems and RTX PRO Servers. Telekom says it was over a third utilized at opening, with Agile Robots and PhysicsX among early users.

Foxconn uses NVIDIA Omniverse digital twins to plan production lines, Isaac to simulate robots and Metropolis for camera-based monitoring, from Hsinchu to new server plants in Mexico and the US. Most published results are expectations, such as a forecast energy cut of over 30 percent in Mexico.

Moon Surgical's ScoPilot feature lets the laparoscope on its Maestro surgical robot follow a chosen instrument tip, running locally on NVIDIA Holoscan. It received FDA clearance in March 2025; Moon Surgical says Maestro had been used in more than 1,100 patients.

Gefion, operated by the Danish Centre for AI Innovation, is an NVIDIA DGX SuperPOD with 1,528 H100 GPUs, funded by the Novo Nordisk Foundation and Denmark's export and investment fund. It went live in October 2024, placed 21st on the November 2024 TOP500 list, and now serves researchers and companies.

A planned 30-minute conversation at NVIDIA GTC Berlin 2026 on how we rehearse the physical world before we build it: OpenUSD, digital twins of factories and AI factories, physical AI and twins beyond the factory. The recording slot is not yet confirmed.