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Month: November 2021

NVIDIA Omniverse Enterprise Delivers the Future of 3D Design and Real-Time Collaboration

November 11, 2021 by
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For millions of professionals around the world, 3D workflows are essential.

Everything they build, from cars to products to buildings, must first be designed or simulated in a virtual world. At the same time, more organizations are tackling complex designs while adjusting to a hybrid work environment.

As a result, design teams need a solution that helps them improve remote collaboration while managing 3D production pipelines. And NVIDIA Omniverse is the answer.

NVIDIA Omniverse Enterprise, now available, helps professionals across industries transform complex 3D design workflows. The groundbreaking platform lets global teams working across multiple software suites collaborate in real time in a shared virtual space.

Designed for the Present, Built for the Future

With Omniverse Enterprise, professionals gain new capabilities to boost traditional visualization workflows. It’s a newly launched subscription that brings fully supported software to 3D organizations of any scale.

The foundation of Omniverse is Pixar’s Universal Scene Description, an open-source file format that enables users to enhance their design process with real-time interoperability across applications. Additionally, the platform is built on NVIDIA RTX technology, so creators can render faster, do multiple iterations at no opportunity cost, and quickly achieve their final designs with stunning, photorealistic detail.

Ericsson, a leading telecommunications company, is using Omniverse Enterprise to create a digital twin of a 5G radio network to simulate and visualize signal propagation and performance. Within Omniverse, Ericsson has built a true-to-reality city-scale simulation environment, bringing in scenes, models and datasets from Esri CityEngine.

A New Experience for 3D Design

Omniverse Enterprise is available worldwide through global computer makers BOXX Technologies, Dell Technologies, HP, Lenovo and Supermicro. Many companies have already experienced the advanced capabilities of the platform.

Epigraph, a leading provider for companies such as Black & Decker, Yamaha and Wayfair, creates physically accurate 3D assets and product experiences for e-commerce. BOXX Technologies helped Epigraph achieve faster rendering with Omniverse Enterprise and NVIDIA RTX A6000 graphics. The advanced RTX Renderer in Omniverse enabled Epigraph to render images at final-frame quality faster, while significantly reducing the amount of computational resources needed.

Media.Monks is exploring ways to enhance and extend their workflows in a virtual world with Omniverse Enterprise, together with HP. The combination of remote computing and collocated workstations enables the Media.Monks design, creative and solutions teams to accelerate their clients’ digital transformation toward a more decentralized future. In collaboration with NVIDIA and HP, Media.Monks is exploring new approaches and the convergence of collaboration, real-time graphics, and live broadcast for a new era of brand virtualization.

Dell Technologies is presenting at GTC to show how Omniverse is advancing the hybrid workforce with Dell Precision workstations, Dell EMC PowerEdge servers and Dell Technologies Validated Designs. The interactive panel discussion will dive into why users need Omniverse today, and how Dell is helping more professionals adopt this solution, from the desktop to the data center.

And Lenovo is showcasing how advanced technologies like Omniverse are making remote collaboration seamless. Whether it’s connecting to a powerful mobile workstation on the go, a physical workstation back in the office, or a virtual workstation in the data center, Lenovo, TGX and NVIDIA are providing remote workers with the same experience they get at the office.

These systems manufacturers have also enabled other Omniverse Enterprise customers such as Kohn Pedersen Fox, Woods Bagot and WPP to improve their efficiency and productivity with real-time collaboration.

Experience Virtual Worlds With NVIDIA Omniverse

NVIDIA Omniverse Enterprise is now generally available by subscription from BOXX Technologies, Dell Technologies, HP, Lenovo and Supermicro.

The platform is optimized and certified to run on NVIDIA RTX professional mobile workstations and NVIDIA-Certified Systems, including desktops and servers on the NVIDIA EGX platform.

With Omniverse Enterprise, creative and design teams can connect their Autodesk 3ds Max, Maya and Revit, Epic Games’ Unreal Engine, McNeel & Associates Rhino, Grasshopper and Trimble SketchUp workflows through live-edit collaboration. Learn more about NVIDIA Omniverse Enterprise and our 30-day evaluation program. For individual artists, there’s also a free beta version of the platform available for download.

Watch NVIDIA founder and CEO Jensen Huang’s GTC keynote address below:

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How Businesses Are Building Specialized AI They Can Trust

With NVIDIA Agent Toolkit — an open foundation comprising models, tools, skills and a secure runtime for AI agents — enterprises are building specialized AI tuned for domain-specific workflows.
June 23, 2026 by
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Editor’s note: This post is part of the Nemotron Labs blog series, which explores how the latest open models, datasets and training techniques help businesses build specialized AI systems and applications on NVIDIA platforms. Each post highlights practical ways to use an open stack to deliver real value in production — from transparent research copilots to scalable AI agents. 

Companies are asking how to build specialized AI that fits with the way their workflows actually run. 

The first wave of enterprise AI was about access. Companies experimented with new frontier and open models, ran pilots and explored how AI can help. 

Now, specialized agents — systems of models that can reason, use tools and take action even for the most complex workflows — put more useful AI within reach of the people who already know the work best.

Agents are already helping life sciences researchers accelerate medicine discovery, security teams investigate vulnerabilities with more context and operations teams seamlessly coordinate supply chains. 

To tap into these specialized agents, businesses are using a foundation they can adapt and own: one built on models they can customize, tools that connect to systems they already use and infrastructure that lets agents operate safely at scale.

NVIDIA Agent Toolkit — comprising models, tools, skills and a secure runtime — provides an open, modular foundation for building safer, faster, lower-cost digital AI coworkers that enterprises and developers can customize, specialize, control and trust.

The Building Blocks for Specialized AI Coworkers

Enterprises and developers building secure, specialized AI agents require:

  • Models, which provide the reasoning foundation. 
  • Tools and skills, which connect agents to the actions and domain expertise needed to get work done. 
  • Runtime support, which helps agents execute workflows. 

NVIDIA Agent Toolkit includes all three:

  • NVIDIA Nemotron open models give teams flexibility to customize, evaluate and deploy agents for their own needs. 
  • NVIDIA NemoClaw blueprints provide patterns for safer agent behavior, delivering accurate results at lower costs, with tools and skills connecting agents to concrete actions.
  • The NVIDIA OpenShell runtime helps agents operate safely inside the systems where work gets done. 

NVIDIA technologies accelerate all the pieces needed to turn a powerful frontier model into a fully functional digital coworker. The toolkit’s users can work with third-party agent harnesses — or agent orchestration frameworks — of their choice, including Hermes Agents and OpenClaw.

This unlocks enterprise AI momentum with control. And that matters because the most valuable agents across industries will be specialized. 

Agents Take Shape Across Industries

The specialized AI foundation is already at work.

In life sciences, agents can help researchers call domain models for protein design, virtual screening, genomics analysis and biomarker discovery. The new NVIDIA BioNeMo Toolkit enables work that previously took months to be completed in days. 

In healthcare, agents support clinical documentation, clinical decision support and care coordination. Plus, physical agents in robotics systems trained in digital twins of hospitals can scale surgical assistance and hospital automation to meet care demands.

In software, cybersecurity, industrial operations and customer workflows, agents can connect to the tools and data teams already use, helping people move faster through complex workflows.

For example, Cadence and Synopsys are building autonomous agents for chip design and engineering workflows. CrowdStrike is running specialized security agents that triage alerts with 98.5% accuracy. Palantir, SAP, ServiceNow, Siemens and Dassault Systèmes are embedding agent capabilities into the enterprise platforms where critical decisions get made. 

It all points to the same larger shift: Agents become more useful when they can combine models, tools, skills, runtime and infrastructure in ways companies can adapt to their own workflows. NVIDIA Agent Toolkit provides an open, modular foundation that enables this combination.

Learn more about NVIDIA Agent Toolkit and NVIDIA BioNeMo Agent Toolkit.

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Eco Wave Power Turns Waves Into Watts With NVIDIA AI Infrastructure and Digital Twins

June 22, 2026 by
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The next era of AI will not be defined by compute alone. Its growth will be determined by energy.

 As accelerated computing scales across AI factories, agentic AI, industrial AI, edge computing and physical AI — including robotics and autonomous systems — global electricity demand is rising at unprecedented speed. 

In many regions, expanding grid infrastructure to meet that need requires years of permitting, transmission upgrades, land acquisition and capital investment.

This challenge is reshaping how the world thinks about energy infrastructure for AI.

Eco Wave Power, a member of the NVIDIA Inception startup program’s Sustainable Futures initiative, is developing technology — powered by NVIDIA AI infrastructure and digital twins — that converts energy from ocean waves into clean electricity using existing marine infrastructure. By using already-built coastal structures, wave energy generation can be deployed closer to areas with growing power demand — including ports, industrial zones and future AI infrastructure hubs.

“Wave energy is one of the largest renewable energy sources that exists,” said Inna Braverman, cofounder and CEO of Eco Wave Power. “Everybody wants it, but nobody can do it, so I looked at the current problems with harnessing wave power and I asked: How do we simplify it?”

Turning the Sea Into a Power Source 

Harnessing Earth’s natural cycles for power generation isn’t a new concept. Wind and solar energy have been well established industries for decades. 

Waves are on the way to completing this trifecta of power-producing elements. 

In the U.S. alone, wave energy could produce over 60% of annual energy consumption, according to the Energy Information Administration. 

It all starts with floaters — noninvasive floating infrastructure attached to breakwaters or sea walls to capture the power generated by waves breaking against the shoreline. 

The density of seawater is roughly 800x the density of air, allowing larger amounts of energy to be generated using much smaller devices than wind turbines. 

The next step is managing and distributing that power. While previous companies faced a bottleneck at this stage — due to having their computer hardware in the floater, leading to potential damages during rough currents — Eco Wave Power puts its computers, sensors, hydraulic conversion and electric parts on land at centers, keeping expensive hardware dry and safe from storms. 

“Wave energy is the least intermittent source of renewable energy,” Braverman said. “Solar energy — for example — is great, but you have night, winter, cloud coverage and pollution that all impact production. With wave energy, you can generate around the clock.” 

AI Wave Energy Layer Using NVIDIA Omniverse Libraries and Accelerated Compute

As AI infrastructure expands, energy systems themselves are becoming increasingly intelligent.

Digital twins of wave patterns and floating infrastructure — built with NVIDIA Omniverse libraries — can simulate wave conditions, structural behavior, deployment configurations and operational scenarios before physical installation begins. These virtual environments can help optimize engineering decisions, reduce deployment risk and accelerate infrastructure planning.

At the operational layer, NVIDIA accelerated computing and AI technologies enable real-time optimization of wave energy systems through predictive analytics, anomaly detection, environmental forecasting and predictive maintenance. AI models can continuously analyze ocean conditions, equipment performance and energy generation patterns to improve efficiency and operational resilience.

AI can also orchestrate energy-aware computing infrastructure by aligning energy-intensive workloads with periods of stronger renewable generation and dynamically optimizing power utilization across distributed systems. 

Ocean Powered Data Centers on the Horizon 

Eco Wave Power operates projects in Jaffa Port, Israel, created in collaboration with EDF Power Solutions and the Israeli Energy Ministry, and in the Port of Los Angeles, developed in collaboration with AltaSea and Shell. Eco Wave Power is also developing new projects in Portugal at the Port of Leixões, Suao Port in Taiwan, and Mumbai, India, with Bharat Petroleum. 

Wave power has already demonstrated its ability to handle consumer energy needs — and is now showing potential to support data centers. 

“We have a possibility to link AI factories directly to wave energy, because a lot of data centers are moving toward the coast,” Braverman said. “They need cooling and water, so they’re now located in ports.” 

Pilots are already underway at the port of Los Angeles to showcase how wave energy can be the sole power source for a data center without tapping into the existing grid energy.

AI software serves as the control layer for this data center pilot, planning compute tasks based on the available power supply. For example, the software can monitor and predict when waves will be stronger throughout the week based on weather patterns — and accordingly allocate more intensive compute tasks for these periods. 

“We exist, we work, we’re grid connected and we have so much of this resource,” Braverman  said. “The energy is needed now, so I think we’re in the right place at the right time and we’re innovative, but we’re not futuristic, and that’s what sets us apart.” 

Explore how NVIDIA is driving the future of energy.

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At Cannes Lions, NVIDIA Partners Reshape Advertising and Marketing With AI

June 18, 2026 by
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The digital era gave the advertising and marketing industry speed; the AI era is giving it autonomous operations. 

For companies building next-generation technologies for advertising and marketing, the question is no longer whether to adopt AI but whether their infrastructure can support it at the speed and scale the industry demands. 

At Cannes Lions, running June 22-26 in France, industry leaders including Alembic, Amazon Web Services (AWS), Criteo, Higgsfield, KERV.ai and Taboola are showcasing how NVIDIA technologies help unlock greater creativity and enable faster, autonomous operations at enterprise scale.

Decision Intelligence at Enterprise Scale

Causal AI platform Alembic helps solve one of enterprises’ biggest challenges: proving what marketing initiatives actually drive growth, not just reporting on what happened. Modeling true causation simultaneously across every channel, market and audience requires AI infrastructure that can process enormous, fast-changing datasets without reducing them to correlation-based assumptions.

NVIDIA DGX Vera Rubin NVL72 systems enable Alembic to scale its Causal AI models to analyze more variables, run larger simulations and quantify the true drivers of growth across marketing investments. Alembic will be the first Causal AI company to use NVIDIA DGX Vera Rubin SuperPODs for enterprise-scale causal modeling, giving executives a single source of unbiased truth on what drove business outcomes and where capital is being wasted, so they can act with confidence on future decisions.

Alembic’s inference runs on private supercomputing infrastructure inside Equinix data centers where the enterprise data already lives, keeping AI workloads local. World Wide Technology extends this to secure and regulated environments. Together, the companies offer a complete enterprise AI stack purpose-built for executives and data leaders accountable for capital decisions. 

Smarter Bidding at Auction Speed

For advertisers, serving ads and relevant recommendations across billions of daily transactions requires AI that’s accurate, fast and affordable enough to run at scale.

Amazon Web Services (AWS) is bringing cloud infrastructure, foundation models and NVIDIA GPU-accelerated computing together into a cohesive stack for the adtech industry that can scale for the era of AI agents. AWS is giving advertisers and demand-side platforms, supply-side platforms and independent software vendors a production-ready reference implementation to run AI-powered bidding directly inside auctions — powered by NVIDIA Triton Inference Server, which delivers deep learning inference fast enough to fit within real-time auction windows. 

That means adtech companies can move from rules-based decisioning to AI-powered models for bid price optimization, audience activation and deal scoring directly within the live auction pipeline.

Advertising company Criteo helps retailers show the right product to the right shopper at the right moment, across one of the largest recommendation networks in digital advertising. Keeping those recommendations relevant means continuously retraining its AI on billions of shopper timelines, a process where speed directly translates to quality. 

Collaborating with NVIDIA, Criteo achieved a roughly 2x speedup in model training on NVIDIA Blackwell GPUs, driven by the NVIDIA cuEmbed open library. That efficiency already frees roughly 17,000 GPU hours a year, and the companies are now scaling the work further.

Infographic that depicts Criteo trains its AI on billions of shopper timelines, achieving a 2x speedup in model training on NVIDIA Blackwell GPUs, which frees roughly 17,000 GPU hours a year.

Taboola is applying the same infrastructure logic to conversational AI, using NVIDIA GPUs to power DeeperDive, its AI answer engine, and extending that infrastructure to AI platforms and chatbots so they can generate revenue from advertising.

Agentic AI Across the Marketing Workflow

In marketing and other industries, AI agents are increasingly acting as digital coworkers, taking on long-running tasks across planning, execution and optimization. But these agents are only deployable for enterprises when they come with proper controls, including safety guardrails, auditability and role-based permissioning. 

The NVIDIA Agent Toolkit, which includes NVIDIA NemoClaw blueprints and the NVIDIA OpenShell secure runtime, provides these controls.

For example, Higgsfield AI, an AI video and image generator production platform, offers Higgsfield Supercomputer agents that manage the full marketing automation lifecycle: from campaign ideation, planning, creative production to posting and autonomous campaign optimization — in a single interface. It orchestrates leading large language models alongside 35+ image, audio and video models, including Higgsfield’s proprietary Soul and Soul 2.0 models built on NVIDIA Blackwell architecture. 

As part of the collaboration, NVIDIA Agent Toolkit software, including NVIDIA Nemotron open models, powers specialized subagents within the Higgsfield Supercomputer, running continuously inside every campaign. NemoClaw and OpenShell are being integrated to provide the enterprise trust layer.  

The result: the full marketing lifecycle, from ideation and creative production through posting, performance analysis and optimization, is available in a single interface. Marketing campaigns for nearly 400 of the Fortune 500 companies are created on the platform. 

 

Video courtesy of Higgsfield.

Contextual and Content Intelligence at Scale

AI understanding content at the level of meaning requires advanced infrastructure. NVIDIA’s multimodal stack provides the vector search, data processing and video understanding capabilities that make this kind of intelligence viable at production scale.

AI-powered media leader KERV’s Moment Match Engine evaluates a multitude of signals across every video frame and media asset to understand individual scenes, objects and products, providing content recommendations based on ad creative — the visual and textual elements of an advertisement — to drive improved engagement.

 

Video courtesy of KERV.ai.

KERV.ai recently optimized its processing pipeline, achieving over 10x improvements in speed and efficiency when using the NVIDIA Nemotron 3 Nano Omni open model in the platform. KERV’s solution analyzes what each ad or media brief contains, who it resonates with and which exact moment within content environments to target. 

On MediaPerf, an open benchmark for AI video understanding, Nemotron 3 Nano Omni — adopted by ecosystem partners including PYLER, which uses NVIDIA DGX B200 systems — delivered the highest throughput and lowest inference cost of any model evaluated, open or closed source.

Learn more about how NVIDIA powers advertising and marketing technologies.

Featured video courtesy of Higgsfield.

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