Posts in category: nVidia AI

Editor’s note: This post is part of our weekly In the NVIDIA Studio series, which celebrates featured artists, offers creative tips and tricks, and demonstrates how NVIDIA Studio technology improves creative workflows. We’re also deep diving on new GeForce RTX 40 Series GPU features, technologies and resources, and how they dramatically accelerate content creation.

Jacob Norris is a 3D artist and the president, co-founder and creative director of Sierra Division Studios — an outsource studio specializing in digital 3D content creation. The studio was founded with a single goal in mind: to make groundbreaking artwork at the highest level.

His team is entirely remote — giving employees added flexibility to work from anywhere in the world while increasing the pool of prospective artists who have a vast array of experiences and skill sets that the studio can draw from.

Norris envisions a future where incredible 3D content can be made regardless of location, time or even language, he said. It’s a future in which NVIDIA Omniverse, a platform for connecting and building custom 3D tools and metaverse applications, will play a critical role.

Omniverse is also a powerful tool for making SimReady assets — 3D objects with accurate physical properties. Combined with synthetic data, these assets can help solve real-world problems in simulation, including for AI-powered 3D artists. Learn more about AI and access creative resources to level up your passion projects on the NVIDIA Studio creative side hustle page.

Plus, check out the new community challenge, #StartToFinish. Use the hashtag to submit a screenshot of a favorite project featuring both its beginning and ending stages for a chance to be showcased on the @NVIDIAStudio and @NVIDIAOmniverse social channels.

Welcome to our new #StartToFinish challenge.

Join by show us a photo/video of how one of your art projects started and then one of the final result + tag #StartToFinish.

Check out these great examples from @rafianimates made with #OpenUSD in @NVIDIAOmniverse. pic.twitter.com/z9v656oQ2Q

— NVIDIA Studio (@NVIDIAStudio) July 10, 2023

Tapping Omniverse for Omnipresent Work 

“Omniverse is an incredibly powerful tool for our team in the collaboration process,” said Norris. He noted that the Universal Scene Description format, aka OpenUSD, is key to achieving efficient content creation.

“We used OpenUSD to build a massive library of all the assets from our team,” Norris said. “We accomplished this by adding every mesh and element of a single model into a large, easily viewable overview scene for kitbashing, which is the process of combining elements from several assets into an entirely new model.”

“Since everything is shared in OpenUSD, our asset library is easily accessible and reduces the time needed to access materials and make edits on the fly,” Norris added. “This helps spur inspirational and imaginational forces.”

During the review phase, the team can compare photorealistic models with incredible visual fidelity side by side in a shared space, ensuring the models are “created to the highest set of standards,” said Norris.

The Last Oil Rig on Earth 

Sierra Division’s The Oil Rig video is set on Earth’s last operational fossil fuel rig, which is visited by a playful drone named Quark. The piece’s storytelling takes the audience through an impeccably detailed environment.

A scene as complex as the one above required blockouts in Unreal Engine. The team snapped models together from a set of greybox modular pieces, ensuring the environment bits were easy to work with. Once satisfied with the environment concept and layout, the team added further detail to the models.

Norris’ Lenovo ThinkPad P73 NVIDIA Studio laptop with NVIDIA RTX A5000 graphics powered NVIDIA DLSS technology to increase the interactivity of the viewport — by using AI to upscale frames rendered at lower resolution while retaining high-fidelity detail.

Sierra Division then created tiling textures, trim sheets and materials to apply to near-finalized models. The studio used Adobe Substance 3D Painter to design custom textures with edge wear and grunge, taking advantage of RTX-accelerated light and ambient occlusion for baking and optimizing assets in seconds.

Next, lighting scenarios were tested in the Omniverse USD Composer app with the Unreal Engine Connector, which eliminates the need to upload, download and refile formats, thanks to OpenUSD.

“With OpenUSD, it’s very easy to open the same file you’re viewing in the engine and quickly make edits without having to re-import,” said Norris.

Sierra Division analyzed daytime, nighttime, rainy and cloudy scenarios to see how the scene resonated emotionally, helping to decide the mood of the story they wanted to tell with their in-progress assets. They settled on a cloudy environment with well-placed lights to evoke feelings of mystery and intrigue.

From here, the team added cameras to the scene to determine compositions for final renders.

“If we were to try to compose the entire environment without cameras or direction, it would take much longer, and we wouldn’t have perfectly laid-out camera shots nor specifically lit renders,” said Norris. “It’s just much easier and more fun to do it this way and to pick camera shots earlier on.”

Final renders were exported lightning fast with Norris’ RTX A5000 GPU into Adobe Photoshop. Over 30 GPU-accelerated features gave Norris plenty of options to play with colors and contrast, and make final image adjustments smoothly and quickly.

The Oil Rig modular set is available for purchase on Epic Games Unreal Marketplace. Sierra Division donates a portion of every sale to Ocean Conservancy — a nonprofit working to reduce trash, create sustainable fisheries and preserve wildlife.

The Explorer’s Room

For another video, called “The Explorer’s Room,” Sierra Division collaborated with 3D artist Mostafa Sohbi. An environment originally created by Sohbi was a great starting point to expand on the idea of an “explorer” that collects artifacts, gets into precarious situations and uses tools to help him out.

Norris and Sierra Division’s creative workflow for this piece closely mirrored the team’s work on The Oil Rig.

“We all know Nathan Drake, Lara Croft, Indiana Jones and other adventurous characters,” said Norris. “They were big inspirations for us to create a living environment that tells our version of the story, while also allowing others to take the same assets and work on their own versions of the story, adding or changing elements in it.”

Norris stressed the importance of GPU technology in his creative workflow. “Having the fastest-performing GPU allowed us to focus more on the creative process and telling our story, instead of trying to work around slow technology or accommodating for poor performance with lower-quality artwork,” said Norris.

“We simply made what we thought was awesome, looked awesome and felt great to share with others,” Norris said. “So it was a no-brainer for us to use NVIDIA RTX GPUs.”

Money Heist 

Norris said much of the content Sierra Division creates offers the opportunity for others to use the studio’s assets to tell their own stories. “We don’t always want to over impose our own ideas into a scene or an environment, but we do want to show what is possible,” he added.

Sierra Division created the Heist Essentials and Tools Collection set of props to share with game developers, content creators and virtual production teams.

“It’s always a thrill to recreate props inspired by movies like Ocean’s Eleven and Mission Impossible, and create assets someone might use during these types of missions and sequences,” said Norris.

Try to spot all of the hidden treasures.

Check out Sierra Division on the studio’s website, ArtStation, Twitter and Instagram.

Follow NVIDIA Studio on Instagram, Twitter and Facebook. Access tutorials on the Studio YouTube channel and get updates directly in your inbox by subscribing to the Studio newsletter. 

Get started with NVIDIA Omniverse by downloading the standard license free, or learn how Omniverse Enterprise can connect your team. Developers can get started with Omniverse resources. Stay up to date on the platform by subscribing to the newsletter, and follow NVIDIA Omniverse on Instagram, Medium and Twitter. For more, join the Omniverse community and check out the Omniverse forums, Discord server, Twitch and YouTube channels.

NVIDIA RTX is spinning new cycles for designs. Trek Bicycle is using GPUs to bring design concepts to life.

The Wisconsin-based company, one of the largest bicycle manufacturers in the world, aims to create bikes with the highest-quality craftsmanship. With its new partner Lidl, an international retailer chain, Trek Bicycle also owns a cycling team, now called Lidl-Trek. The team is competing in the annual Tour de France stage race on Trek Bicycle’s flagship lineup, which includes the Emonda, Madone and Speed Concept. Many of the team’s accessories and equipment, such as the wheels and road race helmets, were also designed at Trek.

Bicycle design involves complex physics — and a key challenge is balancing aerodynamic efficiency with comfort and ride quality. To address this, the team at Trek is using NVIDIA A100 Tensor Core GPUs to run high-fidelity computational fluid dynamics (CFD) simulations, setting new benchmarks for aerodynamics in a bicycle that’s also comfortable to ride and handles smoothly.

The designers and engineers are further enhancing their workflows using NVIDIA RTX technology in Dell Precision workstations, including the NVIDIA RTX A5500 GPU, as well as a Dell Precision 7920 running dual RTX A6000 GPUs.

Visualizing Bicycle Designs in Real Time

To kick off the product design process, the team starts with user research to generate early design concepts and develop a range of ideas. Then, they build prototypes and iterate the design as needed.

To improve performance, the bikes need to feel a certain way, whether riders are taking it on the road or the trail. So Trek spends a lot of time with athletes to figure out where to make critical changes, including tweaks to geometry and the flexibility of the frame and taking the edge off of bumps.

The designers use graphics-intensive applications tools for their computer-aided design workflows, including Adobe Substance 3D, Cinema 4D, KeyShot, Redshift and SOLIDWORKS. For CFD simulations, the Trek Performance Research team uses Simcenter STAR-CCM+ from Siemens Digital Industries Software to take advantage of the GPU processing capabilities.

NVIDIA RTX GPUs provided Trek with a giant leap forward for design and engineering. The visualization team can easily tap into RTX technology to iterate quicker and show more options in designs. They can also use Cinema 4D and Redshift with RTX to produce high-quality renderings and even to visualize different designs in near real time.

Michael Hammond, the lead for digital visual communications at Trek Bicycle, explains the importance of having time for iterations. “The faster we can render an image or animation, the faster we can improve it,” he said. “But at the same time, we don’t want to lose details or spend time recreating models.”

With the help of the RTX A5500, Trek’s digital visual team can push past creative limits and reach the final design much faster. “On average, the RTX GPU performs 12x faster than our network rendering, which is on CPU cores,” said Hammond. “For a render that takes about two hours to complete on our network, it only takes around 10-12 minutes on the RTX A5500 — that means I can do 12x the iterations, which leads to better quality rendering and animation in less time.”

Accelerating CFD Simulations

Over the past decade, adoption of CFD has grown as a critical tool for engineers and equipment designers because it allows them to gain better insights into the behavior of their designs. But CFD is more than an analysis tool — it’s used to make improvements without having to resort to time-consuming and expensive physical testing for every design. This is why Trek has integrated CFD into its product development workflows.

The aerodynamics team at Trek relies on Simcenter STAR-CCM+ to optimize the performance of each bike. To provide a comfortable ride and smooth handling while achieving the best aerodynamic performance, the Trek engineers designed the latest generation Madone to use IsoFlow, a unique feature designed to increase rider comfort while reducing drag.

The Simcenter STAR-CCM+ simulations benefit from the speed of accelerated GPU computing,  and it enabled the engineers to cut down simulation runtimes by 85 days, as they could run CFD simulations 4-5x faster on NVIDIA A100 GPUs compared to their 128-core CPU-based HPC server.

The team can also analyze more complex physics in CFD to better understand how the air is moving in real-world unsteady conditions.

“Now that we can run higher fidelity and more accurate simulations and still meet deadlines, we are able to reduce wind tunnel testing time for significant cost savings,” said John Davis, the aerodynamics lead at Trek Bicycle. “Within the first two months of running CFD on our GPUs, we were able to cancel a planned wind tunnel test due to the increased confidence we had in simulation results.”

Learn more about Trek Bicycle and GPU-accelerated Simcenter STAR-CCM+.

And join us at SIGGRAPH, which runs from Aug. 6-10, to see the latest technologies shaping the future of design and simulation.

Editor’s note: This post is part of our weekly In the NVIDIA Studio series, which celebrates featured artists, offers creative tips and tricks, and demonstrates how NVIDIA Studio technology improves creative workflows. We’re also deep diving on new GeForce RTX 40 Series GPU features, technologies and resources, and how they dramatically accelerate content creation.

A diverse range of artists, fashionistas, musicians and the cinematic arts inspired the creative journey of Pedro Soares, aka Blendeered, and helped him fall in love with using 3D to create art.

Now, the Porto, Portugal-based artist uses his own life experiences and interactions with people, regardless of their artistic background, to realize his artistic vision.

Enamored by Japanese culture, Blendeered sought to make a representation of an old Japanese temple, dedicated to an animal that has consistently delivered artistic inspiration — the mighty wolf. The result is Japanese Temple Set, a short animation that is the subject of this week’s edition of In the NVIDIA Studio, built with Blender and Blackmagic Design’s DaVinci Resolve.

In addition, get a glimpse of two cloud-based AI apps, Wondershare Filmora and Trimble SketchUp Go, powered by NVIDIA RTX GPUs, and learn how they can elevate and automate content creation.

Finally, the #SetTheScene challenge has come to an end. Check out highlights from some of the many incredible submissions.

Thank you to everyone who participated in the #SetTheScene challenge!

We were blown away by your creativity and artistic skill.

Stay tuned next Monday for the launch of our next community challenge. pic.twitter.com/hARW2Z8glQ

— NVIDIA Studio (@NVIDIAStudio) July 3, 2023

An AI on the Future

Week by week, AI becomes more ubiquitous within the content creation workflows of aspiring artists and creative professionals. Those who own NVIDIA or GeForce RTX GPUs can take advantage of Tensor Cores that utilize AI to accelerate over 100 apps. For others yet to upgrade and seeking more versatility, NVIDIA is working with the top creative app publishers to accelerate their apps on RTX GPUs from the cloud.

Take the Wondershare Filmora app, which creators can use to capture and touch up video on their mobile devices. They can, for example, add photos and transform them into an animated video with the app’s AI Image feature. Those with a PC powered by RTX GPUs can send files to the Filmora desktop app and continue to edit with local RTX acceleration, such as by exporting video at double the speed with dual encoders on RTX 4070 Ti or above GPUs.

With the Trimble SketchUp Go app, architects can design structures on any device — such as an iPad —  without loss in performance thanks to RTX acceleration in the cloud. Projects can be synced in the cloud using Trimble Connect, allowing users to refine projects on their RTX-powered PC using the SketchUp Pro app. There’s even an Omniverse Connector for Trimble, enabling SketchUp Pro compatibility with all apps on NVIDIA Omniverse, a development platform for connecting and building 3D tools and applications.

Hungry Like the Wolf 

To gather inspiration, and reference materials, to fuel his Japanese temple project, Blendeered browsed Google, Pinterest and PureRef, a stand-alone app for creating mood boards. He sought wolf-inspired and Japanese open-source 3D assets to enrich the scene he envisions before modeling.

“Little details in the scene are a celebration of wolves, for example, the paintings on the ceiling and the statues,” said Blendeered. “I did this scene with the goal of invoking calm and relaxing emotions, giving people a moment to breathe and catch their breath.”

Work began in Blender with the block-out phase — creating a rough-draft level built using simple 3D shapes, without details or polished art assets. This helped to keep base meshes clean, eliminating the need to create new meshes in the next round, which required only minor edits.

Blender is the most popular open-source 3D app in the world as it supports the entirety of the 3D pipeline. Blendeered uses it to apply textures, adjust lighting and animate the scene with ease.

“Blender, my ultimate 3D app, captivates with its friendly interface, speed, power, real-time rendering, diverse addons, vibrant community, and the best part — it’s free!” said Blendeered, whose moniker underscores his enthusiasm.

Aided by his NVIDIA Studio laptop powered by GeForce RTX graphics, Blendeered used RTX-accelerated OptiX ray tracing in the viewport for interactive, photoreal rendering for his modeling and animation needs.

“GPU acceleration for real-time rendering in Blender helps a lot by allowing instant feedback on how scenes look and what needs to be changed and improved,” said the artist.

With final renders ready, Blendeered accessed the Blender Cycles renderer and OptiX ray tracing to export final frames quickly, importing the project into DaVinci Resolve for post-production.

Here, his RTX card was put to work again, refining the scene with GPU-accelerated color grading, video editing and color scopes.

The GPU-accelerated decoder (NVDEC) unlocked smoother playback and scrubbing of high-resolution and multistream videos, saving Blendeered massive amounts of time.

Blendeered had numerous RTX-accelerated AI-effects at his disposal, including Cut Scene Detection for automatically tagging clips and tracking of effects, SpeedWarp for smooth slow motion, and seamless video Super Resolution. Even non-GPU-powered effects such as Neural Engine text-based editing can prove to be tremendously useful.

Once satisfied with the animation, Blendeered used the GPU-accelerated encoder (NVENC) to speed up the exporting of his video.

Reflecting on the role his GPU had to play, Blendeered was matter-of-fact: “I chose a GeForce RTX-powered system because of the processing power and compatibility with the software I use.”

View Blendeered’s portfolio on blendeered.com.

Follow NVIDIA Studio on Instagram, Twitter and Facebook. Access tutorials on the Studio YouTube channel and get updates directly in your inbox by subscribing to the Studio newsletter. 

GFN Thursday arrives alongside the sweet Steam Summer Sale — with hundreds of PC games playable on GeForce NOW available during Valve’s special event for PC gamers.

Also on sale, OCTOPATH TRAVELER and OCTOPATH TRAVELER II join the GeForce NOW library as a part of five new games coming to the service this week.

Saved by the Sale

Get great games at great deals to stream across your devices during the Steam Summer Sale. In total, more than 1,000 titles can be found at discounts of up to 90% through July 13.

Grow your game collection with some top picks.

Enjoy iconic Xbox Game Studios hits from the Age of Empires series — even on Mac — thanks to the cloud. Control an empire with the goal of expanding to become a flourishing civilization. Age of Empires II arrives to the GeForce NOW library this week, joining Age of Empires, Age of Empires III and Age of Empires IV.

Stream Square Enix games at beautiful quality on underpowered PCs with heart-wrenching single-player stories like Life is Strange 2 and Life is Strange: True Colors, or battle it out with a squad in the dark sci-fi universe of Outriders.

Become a Viking, sail the open sea and fight monsters in the world of Valheim, or play a spooky game of hide-and-seek as a Ghost or a Hunter in Midnight Ghost Hunt. Take these titles from publisher Coffee Stain Studios on the go playing on nearly any Android or iOS mobile device.

Tune in on the big screen with NVIDIA SHIELD TVs for THQ Nordic favorites. Return to an apocalyptic Earth in the hack-n-slash adventure Darksiders III, or terrorize the people of 1950s Earth as an evil alien in Destroy All Humans!

Experience these titles and 1,600+ other games on GeForce NOW with all of the perks of an Ultimate membership, including RTX 4080 quality, support for 4K 120 frames per second gameplay and ultrawide resolutions, and the longest gaming sessions on the cloud.

Priority and Ultimate members can also experience DLSS 3 and RTX ON for real-time cinematic lighting in supported games.

Choose Your Path

Visit faraway realms playing OCTOPATH TRAVELER and OCTOPATH TRAVELER II from Square Enix — also on sale on Steam. Members can even start their traveler journey with the OCTOPATH TRAVELER II Prologue demo.

Explore the story of eight travelers hailing from different regions who are set on vastly different ventures. Step into their shoes and use their unique talents to make decisions that will shape your path and aid you along your journey in these two award-winning role-playing games.

In OCTOPATH TRAVELER, engage in side quests and thrilling battles where every choice made by players shapes the storylines and destinies of these remarkable characters. Continue the adventure with OCTOPATH TRAVELER II and a fresh new set of eight travelers in the land of Solistia, a land comprising eastern and western continents divided by the sea.

It’s Good to Be the King

And that’s not all — five new games are joining the GeForce NOW library this week.

Age of Empires II: Definitive Edition celebrates the 20th anniversary of one of the world’s most popular real-time strategy games. Explore all the original campaigns like never before, spanning over 200 hours of gameplay and 1,000 years of human history. Rise to the challenge of leading four new civilizations, exclusive to the Definitive Edition, and head online to challenge other players in a bid for world domination throughout the ages.

Catch the full list of new titles available to find your next adventure:

• The Legend of Heroes: Trails into Reverie (New release on Steam, July 7)
• OCTOPATH TRAVELER (Steam)
• OCTOPATH TRAVELER II (Steam)
• OCTOPATH TRAVELER II Prologue Demo (Steam)
• Age of Empires II: Definitive Edition (Steam)

Members can also experience Major League Baseball’s new Virtual Ballpark and be a part of MLB’s interactive All-Star Celebrity Softball Watch Party on Saturday, July 8. Supported by NVIDIA’s global cloud streaming infrastructure, fans will have frictionless access to high-fidelity interactive experiences. Register for the event.

What are you planning to play this weekend? Let us know on Twitter or in the comments below.

If you could 𝒕𝒓𝒂𝒗𝒆𝒍 to any video game land, where would it be?

— NVIDIA GeForce NOW (@NVIDIAGFN) July 5, 2023

Three leading European generative AI startups joined NVIDIA founder and CEO Jensen Huang this week to talk about the new era of computing.

More than 500 developers, researchers, entrepreneurs and executives from across Europe and further afield packed into the Spindler and Klatt, a sleek, riverside gathering spot in Berlin.

Huang started the reception by touching on the message he delivered Monday at the Berlin Summit for Earth Virtualization Engines (EVE), an international collaboration focused on climate science. He shared details of NVIDIA’s Earth-2 initiative and how accelerated computing, AI-augmented simulation and interactive digital twins drive climate science research.

Before sitting down for a fireside chat with the founders of the three startups, Huang introduced some “special guests” to the audience — four of the world’s leading climate modeling scientists, who he called the “unsung heroes” of saving the planet.

“These scientists have dedicated their careers to advancing climate science,” said Huang. “With the vision of EVE, they are the architects of the new era of climate science.”

Taking on Formidable Forces

“There is an enormous amount of AI startups in Germany, and I’m delighted to see it,” Huang said. “You’re in a brand-new computing era, and when that happens, everybody’s on square one.”

Huang welcomed to the stage the founders from Blackshark.ai, Magic and DeepL. Planetary management, artificial general intelligence, or AGI, and language translation are some ways the startups use generative AI.

• Blackshark.ai uses AI and hyperscaling distributed spatial computing to turn 2D images into data-rich 3D worlds.
• Magic is building an AGI software engineer, enabling small teams to write code significantly faster and more cheaply.
• DeepL aims to help everything communicate with everybody else with its AI-powered translation tool.

All three companies make solutions that could be seen as going up against products from established companies.

“Why did you take on such formidable forces?” Huang asked the founders.

Blackshark co-founder and CEO Michael Putz shared that the startup’s product is similar to what you might see in Google Earth.

But Blackshark claimed its coverage of the planet is 100%, compared to Google Earth’s 20%. And while Google might take a few months to update parts of its map, Blackshark only needs three days, Putz said.

Magic co-founder, CEO and AI lead Eric Steinberger explained how his company is trying to build an AGI AI software engineer that will work as though it were a team of humans.

He said it’ll remember conversations from months ago and can be messaged via an app like any other engineer. Rather than creating an alternative to existing solutions, Magic sees itself as trying to build something categorically different.

“It’s hard to build, but if we can get it right, we’re in an even playing field, even up against the giants,” said Steinberger.

DeepL founder and CEO Jaroslav Kutylowski said his company’s work was initially an intellectual challenge. “Could they do better than Google?” the team asked themselves. To Kutylowski, that sounded like fun.

Intuition, Efficiency and Resilience

Steinberger got a chuckle from the audience as he asked Huang about his decision-making process in driving NVIDIA forward. “You’re right, either always or almost always. How do you make those decisions before it’s obvious?”

“That’s a hard question,” Huang responded.

Huang talked about the intuition that comes from decision-making, saying, in his case, it comes from life and industrial experience. In NVIDIA’s case, he said it comes from having a lot of ideas “cooking” simultaneously.

He explained that with the invention of the GPU, the intention was never to replace the CPU but to make the GPU part of the next great computer by taking a full-stack approach.

With data centers and the cloud, Putz asked for advice on the best approach for startups when it comes to computing.

NVIDIA joined the “fabless semiconductor” industry, where there was very little capital required for a factory to funnel resources into R&D teams of 30-50 engineers instead of 500 like a more traditional semiconductor company.

Today, Huang explained, with the software 2.0 generation, startups can’t spend all their money on engineers — they need to save some to prototype and refine their software.

And it’s important to use the right tools to do the work for cost-efficient workloads. A CPU might be cheaper than a GPU per instance, but running a workload on a GPU will take “10x less time,” he said.

Kutylowski asked about the most significant challenges NVIDIA and Huang have faced along the company’s 30-year journey.

“I go into things with the attitude of, ‘How hard can it be? Well, it turns out it’s super hard,” Huang answered. “But if somebody else can do it, why can’t I?”

The answer includes the right attitude, self-confidence, the willingness to learn, and not setting an expectation of perfection from day one, he said. “Being resilient as you fail to the point where you eventually succeed — that’s when you learn,” Huang said.

China electric vehicle maker XPENG Motors has announced its new G6 coupe SUV — featuring an NVIDIA-powered intelligent advanced driver assistance system — is now available to the China market.

The G6 is XPENG’s first model featuring the company’s proprietary Smart Electric Platform Architecture (SEPA) 2.0, which aims to reduce development and manufacturing costs and shorten R&D cycles since the modular architecture will be compatible with future models.

The electric SUV also features the XPENG Navigation Guided Pilot (XNGP), a full scenario-based intelligent assisted driving system. It’s powered by the cutting-edge NVIDIA DRIVE Orin compute and XPENG’s full-stack software developed in-house.

The XNGP system first made its debut in the EV maker’s flagship G9 SUV, touting a safe, reliable, advanced driving experience behind the wheel.

Next-Level Driving Experience for All

The G6 comes in five trim levels, ranging in price from $29,021-$38,285 (RMB 209,900-276,900), making it accessible for the mainstream market.

Featuring a high-voltage 800V silicon-carbide platform and 3C battery, the G6 is built to go up to 469 miles on one charge and can reach speeds up to 125 miles per hour (202 kph). With XPENG’s DC fast charger, drivers can get up to 186 miles of charge in just 10 minutes.

The G6 model comes with two NVIDIA DRIVE Orin systems-on-a-chip (SOCs), which deliver 508 trillion operations per second (TOPS) of high-peformance compute for real-time processing of data streaming in from the vehicle’s 31 driving sensors.

Upping the Ante

The XNGP driving system makes the G6 a standout among today’s EV landscape as automakers jockey for position in the highly competitive China market. In fact, XPENG predicts this latest model will become the top-selling electric SUV in the country.

With the XNGP’s point-to-point automated cruise assistance, drivers need only set the destination and monitor the traffic conditions with hands resting on the steering wheel, while the vehicle takes the wheel, performing a host of scenario-based actions. These include cruising on main urban roads, autonomously changing lanes, congestion avoidance, emergency braking, on- and off-ramp driving, highway driving, parking, and more.

The G6’s ability to safely navigate all these driving scenarios is enabled by its comprehensive sensor suite, which includes multiple lidars, cameras, mmWave and ultrasonic radars for a 360-degree surround view of the car’s environment. As a result, this redundant and diverse multi-sensor fusion set helps enable safe, intelligent driving decisions under a variety of urban driving conditions.

With plans for the G6 to roll out to key European markets by next year, XPENG designed this state-of-the-art coupe SUV to meet both C-NCAP and E-NCAP safety standards.

Based on the more than 35,000 preorders reported for the G6 after its reveal at Auto Shanghai earlier this year, drivers are eager to get moving in this latest offering from XPENG’s software-defined fleet.

The increased frequency and severity of extreme weather and climate events could take a million lives and cost $1.7 trillion annually by 2050, according to the Munich Reinsurance Company.

This underscores a critical need for accurate weather forecasting, especially with the rise in severe weather occurrences such as blizzards, hurricanes and heatwaves. AI and accelerated computing are poised to help.

More than 180 weather modeling centers employ robust high performance computing (HPC) infrastructure to crunch traditional numerical weather prediction (NWP) models. These include the European Center for Medium-Range Weather Forecasts (ECMWF), which operates on 983,040 CPU cores, and the U.K. Met Office’s supercomputer, which uses more than 1.5 million CPU cores and consumes 2.7 megawatts of power.

Rethinking HPC Design

The global push toward energy efficiency is urging a rethink of HPC system design. Accelerated computing, harnessing the power of GPUs, offers a promising, energy-efficient alternative that speeds up computations.

NVIDIA GPUs have made a significant impact on globally adopted weather models, including those from ECMWF, the Max Planck Institute for Meteorology, the German Meteorological Service and the National Center for Atmospheric Research.

GPUs enhance performance up to 24x, improve energy efficiency, and reduce costs and space requirements.

“To make reliable weather predictions and climate projections a reality within power budget limits, we rely on algorithmic improvements and hardware where NVIDIA GPUs are an alternative to CPUs,” said Oliver Fuhrer, head of numerical prediction at MeteoSwiss, the Swiss national office of meteorology and climatology.

AI Model Boosts Speed, Efficiency

NVIDIA’s AI-based weather-prediction model FourCastNet offers competitive accuracy with orders of magnitude greater speed and energy efficiency compared with traditional methods. FourCastNet rapidly produces week-long forecasts and allows for the generation of large ensembles — or groups of models with slight variations in starting conditions — for high-confidence, extreme weather predictions.

For example, based on historical data, FourCastNet accurately predicted the temperatures on July 5, 2018, in Ouargla, Algeria — Africa’s hottest recorded day.

Using NVIDIA GPUs, FourCastNet quickly and accurately generated 1,000 ensemble members, outpacing traditional models. A dozen of the members accurately predicted the high temperatures in Algeria based on data from three weeks before it occurred.

This marked the first time the FourCastNet team predicted a high-impact event weeks in advance, demonstrating AI’s potential for reliable weather forecasting with lower energy consumption than traditional weather models.

FourCastNet uses the latest AI advances, such as transformer models, to bridge AI and physics for groundbreaking results. It’s about 45,000x faster than traditional NWP models. And when trained, FourCastNet consumes 12,000x less energy to produce a forecast than the Europe-based Integrated Forecast System, a gold-standard NWP model.

“NVIDIA FourCastNet opens the door to the use of AI for a wide variety of applications that will change the shape of the NWP enterprise,” said Bjorn Stevens, director of the Max Planck Institute for Meteorology.

Expanding What’s Possible

In an NVIDIA GTC session, Stevens described what’s possible now with the ICON climate research tool. The Levante supercomputer, using 3,200 CPUs, can simulate 10 days of weather in 24 hours, Stevens said. In contrast, the JUWELS Booster supercomputer, using 1,200 NVIDIA A100 Tensor Core GPUs, can run 50 simulated days in the same amount of time.

Scientists are looking to study climate effects 300 years into the future, which means systems need to be 20x faster, Stevens added. Embracing faster technology like NVIDIA H100 Tensor Core GPUs and simpler code could get us there, he said.

Researchers now face the challenge of striking the optimal balance between physical modeling and machine learning to produce faster, more accurate climate forecasts. A ECMWF blog published last month describes this hybrid approach, which relies on machine learning for initial predictions and physical models for data generation, verification and system refinement.

Such an integration — delivered with accelerated computing — could lead to significant advancements in weather forecasting and climate science, ushering in a new era of efficient, reliable and energy-conscious predictions.

Learn more about how accelerated computing and AI boost climate science through these resources:

• NVIDIA one-pager: Predicting the Weather With AI
• NVIDIA one-pager: Faster Weather Predictions
• NVIDIA resource page: Sustainable Computing
• NVIDIA technical blog: AI for a Scientific Computing Revolution

AI and accelerated computing will help climate researchers achieve the miracles they need to achieve breakthroughs in climate research, NVIDIA founder and CEO Jensen Huang said during a keynote Monday at the Berlin Summit for the Earth Virtualization Engines initiative.

“Richard Feynman once said that “what I can’t create, I don’t understand” and that’s the reason why climate modeling is so important,” Huang told 180 attendees at the Harnack House in Berlin, a storied gathering place for the region’s scientific and research community.

“And so the work that you do is vitally important to policymakers to researchers to the industry,” he added.

To advance this work, the Berlin Summit brings together participants from around the globe to harness AI and high-performance computing for climate prediction.

In his talk, Huang outlined three miracles that will have to happen for climate researchers to achieve their goals, and touched on NVIDIA’s own efforts to collaborate with climate researchers and policymakers with its Earth-2 efforts.

The first miracle required will be to simulate the climate fast enough, and with a high enough resolution – on the order of just a couple of square kilometers.

The second miracle needed will be the ability to pre-compute vast quantities of data.

The third miracle needed is the ability to visualize all this data interactively with NVIDIA Omniverse to “put it in the hands of policymakers, businesses, companies, and researchers.”

The Next Wave of Climate and Weather Innovation

The Earth Virtualization Engines initiative, known as EVE, is an international collaboration that brings together digital infrastructure focused on climate science, HPC and AI aiming to provide, for the first time, easily accessible kilometer-scale climate information to sustainably manage the planet.

“The reason why Earth-2 and EVE found each other at the perfect time is because Earth-2 was based on 3 fundamental breakthroughs,” Huang said.

The initiative promises to accelerate the pace of advances, advocating coordinated climate projections at 2.5-km resolution. It’s an enormous challenge, but it’s one that builds on a huge base of advancements over the past 25 years.

A sprawling suite of applications already benefits from accelerated computing, including ICON, IFS, NEMO, MPAS, WRF-G and more — and much more computing power for such applications is coming.

The NVIDIA GH200 Grace Hopper Superchip is a breakthrough accelerated CPU designed from the ground up for giant-scale AI and high-performance computing applications.  It delivers up to 10x higher performance for applications running terabytes of data.

It’s built to scale, and by connecting large numbers of these chips together, NVIDIA can offer systems with the power efficiency to accelerate the work of researchers at the cutting edge of climate research. “To the software it looks like one giant processor,” Huang said.

To help researchers put vast quantities of data to work, quickly, to unlock understanding, Huang spoke about NVIDIA Modulus, an open-source framework for building training and fine-tuning physics-based machine learning model, and FourCastNet, a global, data-driven weather forecasting model, and how the latest AI-driven models can learn physics from real-world data.

Using raw data alone, FourCastNet is able to learn the principles governing complex weather patterns. Huang showed how FourCastNet was able to accurately predict the path of Hurricane Harvey by modeling the Coriolis force, the effect of the Earth’s rotation, on the storm.

Such models, when tethered to regular “checkpoints” created by traditional simulation, allow for more detailed, long-range forecasts. Huang then demonstrated how some of the FourCastNet ensemble’s models, running on NVIDIA GPUs, anticipated an unprecedented North African heatwave.

By running FourCastNet in Modulus, NVIDIA was able to generate 21-day weather trajectories of 1,000 ensemble members in one-tenth the time it previously took to do a single ensemble — and with 1,000x less energy consumption.

Lastly, NVIDIA technologies promise to help all this knowledge become more accessible with digital twins able to create interactive models of increasingly complex systems – from Amazon warehouses to the way 5G signals propagate in dense urban environments.

Huang then showed a stunning, high-resolution interactive visualization of global-scale climate data in the cloud, zooming in from a view of the globe to a detailed view of Berlin. This approach can work to predict climate and weather in locations as diverse as Berlin, Tokyo and Buenos Aires, Huang said.

Earth: The Final Frontier

To help meet challenges such as these, Huang outlined how NVIDIA is building more powerful systems for training AI models, simulating physical problems and interactive visualization.

“These new types of supercomputers are just coming online,” Huang said. “This is as fresh a computing technology as you can imagine.”

Huang ended his talk by thanking key researchers from across the field and playfully suggesting a mission statement for EVE.

“Earth, the final frontier, these are the voyages of EVE,” Huang said. Its “mission is to push the limits of computing in service of climate modeling, to seek out new methods and technologies to study the global-to-local state of the climate to inform today the impact of mitigation and adaptation to Earth’s tomorrow, to boldly go where no one has gone before.”

For more on Earth-2, visit https://www.nvidia.com/en-us/high-performance-computing/earth-2/

Robots are moving goods in warehouses, packaging foods and helping assemble vehicles  — when they’re not flipping burgers or serving lattes.

How did they get so skilled so fast? Robotics simulation.

Making leaps in progress, it’s transforming industries all around us.

Robotics Simulation Summarized

A robotics simulator places a virtual robot in virtual environments to test the robot’s software without requiring the physical robot. And the latest simulators can generate datasets to be used to train machine learning models that will run on the physical robots.

In this virtual world, developers create digital versions of robots, environments and other assets robots might encounter. These environments can obey the laws of physics and mimic real-world gravity, friction, materials and lighting conditions.

Who Uses Robotics Simulation? 

Robots boost operations at massive scale today. Some of the biggest and most innovative names in robots rely on robotics simulation.

Fulfillment centers handle tens of millions of packages a day, thanks to the operational efficiencies uncovered in simulation.

Amazon Robotics uses it to support its fulfillment centers. BMW Group taps into it to accelerate planning for its automotive assembly plants. Soft Robotics applies it to perfecting gripping for picking and placing foods for packaging.

Automakers worldwide are supporting their operations with robotics.

“Car companies employ nearly 14 million people. Digitalization will enhance the industry’s efficiency, productivity and speed,” said NVIDIA CEO Jensen Huang during his latest GTC keynote.

How Robotics Simulation Works, in Brief

An advanced robotics simulator begins by applying fundamental equations of physics. For example, it can use Newton’s laws of motion to determine how objects move over a small increment of time, or a timestep. It can also incorporate physical constraints of a robot, such as being composed of hinge-like joints, or being unable to pass through other objects.

Simulators use various methods to detect potential collisions between objects, identify contact points between colliding objects, and compute forces or impulses to prevent objects from passing through one another. Simulators can also compute sensor signals sought by a user, such as torques at robot joints or forces between a robot’s gripper and an object.

The simulator will then repeat this process for as many timesteps as the user requires. Some simulators — such as NVIDIA Isaac Sim, an application built on NVIDIA Omniverse — can also provide physically accurate visualizations of the simulator output at each timestep.

Using a Robotics Simulator for Outcomes

A robotics simulator user will typically import computer-aided design models of the robot and either import or generate objects of interest to build a virtual scene. A developer can use a set of algorithms to perform task planning and motion planning, and then prescribe control signals to carry out those plans. This enables the robot to perform a task and move in a particular way, such as picking up an object and placing it at a target location.

The developer can observe the outcome of the plans and control signals and then modify them as needed to ensure success. More recently, there’s been a shift toward machine learning-based methods. So instead of directly prescribing control signals, the user prescribes a desired behavior, like moving to a location without colliding. In this situation, a data-driven algorithm generates control signals based on the robot’s simulated sensor signals.

These algorithms can include imitation learning, in which human demonstrations can provide references, and reinforcement learning, where robots learn to achieve behaviors through intelligent trial-and-error, achieving years of learning quickly with an accelerated virtual experience.

Simulation Drives Breakthroughs

Simulation solves big problems. It is used to verify, validate and optimize robot designs and systems and their algorithms. Simulation also helps design facilities to be optimized for maximum efficiencies before construction or remodeling begins. This helps to reduce costly manufacturing change orders.

For robots to work safely among people, flawless motion planning is necessary. To handle delicate objects, robots need to be precise at making contact and grasping. These machines, as well as autonomous mobile robots and vehicle systems, are trained on vast sums of data to develop safe movement.

Drawing on synthetic data, simulations are enabling virtual advances that weren’t previously possible. Today’s robots born and raised in simulation will be used in the real world to solve all manner of problems.

Simulation Research Is Propelling Progress 

Driven by researchers, recent simulation advances are rapidly improving the capabilities and flexibility of robotics systems, which is accelerating deployments.

University researchers, often working with NVIDIA Research and technical teams, are solving problems in simulation that have real-world impact. Their work is expanding the potential for commercialization of new robotics capabilities across numerous markets.

Among them, robots are learning to cut squishy materials such as beef and chicken, fasten nuts and bolts for automotive assembly, as well as maneuver with collision-free motion planning for warehouses and manipulate hands with new levels of dexterity.

Such research has commercial promise across trillion-dollar industries.

High-Fidelity, Physics-Based Simulation Breakthroughs 

The ability to model physics, displayed in high resolution, ushered in the start of many industrial advances.

Researched for decades, simulations based on physics offer commercial breakthroughs today.

NVIDIA PhysX, part of Omniverse core technology, delivers high-fidelity physics-based simulations, enabling real-world experimentation in virtual environments.

PhysX enables development of the ability to assess grasp quality so that robots can learn to grasp unknown objects. PhysX is also highly capable for developing skills such as manipulation, locomotion and flight.

Launched into open source, PhysX 5 opens the doors for development of industrial applications everywhere. Today, roboticists can access PhysX as part of Isaac Sim, built on Omniverse.

The Nuts and Bolts of Assembly Simulation 

With effective grasping enabled, based on physics, the next step was to simulate more capable robotic maneuvering applicable to industries.

Assembly is a big one. It’s an essential part of building products for automotive, electronics, aerospace and medical industries. Assembly tasks include tightening nuts and bolts, soldering and welding, inserting electrical connections and routing cables.

Robotic assembly, however, is a long-standing work in progress. That’s because the physical manipulation complexity, part variability and high accuracy and reliability requirements make it extra tricky to complete successfully — even for humans.

That hasn’t stopped researchers and developers from trying, putting simulation to work in these interactions involving a lot of contact, and there are signs of progress.

NVIDIA robotics and simulation researchers in 2022 came up with a novel simulation approach to overcome the robotics assemble challenge using Isaac Sim. Their research paper, titled Factory: Fast Contact for Robotic Assembly, outlines a set of physics simulation methods and robot learning tools for achieving real-time and faster simulation for a wide range of interactions requiring lots of contact, including for assembly.

Solving the Sim-to-Real Gap for Assembly Scenarios 

Advancing the simulation work developed in the paper, researchers followed up with an effort to help solve what’s called the sim-to-real gap.

This gap is the difference between what a robot has learned in simulation and what it needs to learn to be ready for the real world.

In another paper, IndustReal: Transferring Contact-Rich Assembly Tasks from Simulation to Reality, researchers outlined a set of algorithms, systems and tools for solving assembly tasks in simulation and transferring these skills to real robots.

NVIDIA researchers have also developed a new, faster and more efficient method for teaching robot manipulation tasks in real life scenarios — opening drawers or dispensing soap — training significantly faster than the current standard.

The research paper RVT: Robotic View Transformer for 3D Object Manipulation uses a type of neural network called a multi-view transformer to produce virtual views from the camera input.

The work combines text prompts, video input and simulation to achieve 36x faster training time than the current state of the art — reducing the time needed to teach the robot from weeks to days —  with a 26 percent improvement in the robot’s task success rate.

Robots Hands Are Grasping Dexterity 

Researchers have taken on the challenge of creating more agile hands that can work in all kinds of settings and take on new tasks.

Developers are building robotic gripping systems to pick and place items, but creating highly capable hands with human-like dexterity has so far proven too complex. Using deep reinforcement learning can require billions of labeled images, making it impractical.

NVIDIA researchers working on a project, called DeXtreme, tapped into NVIDIA Isaac Gym and Omniverse Replicator to show that it could be used to train a robot hand to quickly manipulate a cube into a desired position. Tasks like this are challenging for robotics simulators because there is a large number of contacts involved in the manipulation and because the motion has to be fast to do the manipulation in a reasonable amount of time.

The advances in hand dexterity pave the way for robots to handle tools, making them more useful in industrial settings.

The DeXtreme project, which applies the laws of physics, is capable of training robots inside its simulated universe 10,000x faster than if trained in the real world. This equates to days of training versus years.

This simulator feat shows it has the ability to model contacts, which allows a sim-to-real transfer, a holy grail in robotics for hand dexterity.

Cutting-Edge Research on Robotic Cutting

Robots that are capable of cutting can create new market opportunities.

In 2021, a team of researchers from NVIDIA, University of Southern California, University of Washington, University of Toronto and Vector Institute, and University of Sydney won “Best Student Paper” at the Robotics: Science and Systems conference. The work, titled DiSECt: A Differentiable Simulation Engine for Autonomous Robotic Cutting, details a “differentiable simulator” for teaching robots to cut soft materials. Previously, robots trained in this area were unreliable.

The DiSECt simulator can accurately predict the forces on a knife as it presses and slices through common biological materials.

DiSECt relies on the finite element method, which is used for solving differential equations in mathematical modeling and engineering. Differential equations show how a rate of change, or derivative, in one variable relates to others. In robotics, differential equations usually describe the relationship between forces and movement.

Applying these principles, the DiSECt project holds promise for training robots in surgery and food processing, among other areas.

Teaching Collision-Free Motion for Autonomy 

So, robotic grasping, assembling, manipulating and cutting are all making leaps. But what about autonomous mobile robots that can safely navigate?

Currently, developers can train robots for specific settings — a factory floor, fulfillment center or manufacturing plant. Within that, simulations can solve problems for specific robots, such as palette jacks, robotic arms and walking robots. Amid these chaotic setups and robot types, there are plenty of people and obstacles to avoid. In such scenes, collision-free motion generation for unknown, cluttered environments is a core component of robotics applications.

Traditional motion planning approaches that attempt to address these challenges can come up short in unknown or dynamic environments. SLAM — or simultaneous localization and mapping —  can be used to generate 3D maps of environments with camera images from multiple viewpoints, but it requires revisions when objects move and environments are changed.

To help overcome some of these shortcomings, the NVIDIA Robotics research team has co-developed with the University of Washington a new model, dubbed Motion Policy Networks (or MπNets). MπNets is an end-to-end neural policy that generates collision-free motion in real time using a continuous stream of data coming from a single fixed camera. MπNets has been trained on more than 3 million motion planning problems using a pipeline of geometric fabrics from NVIDIA Omniverse and 700 million point clouds rendered in simulation. Training it on large datasets enables navigation of unknown environments in the real world.

Apart from directly learning a trajectory model as in MπNets, the team also recently unveiled a new point cloud-based collision model called CabiNet. With the CabiNet model, one can deploy general purpose pick-and-place policies of unknown objects beyond a tabletop setup. CabiNet was trained with over 650,000 procedurally generated simulated scenes and was evaluated in NVIDIA Isaac Gym. Training with a large synthetic dataset allowed it to generalize to even out-of-distribution scenes in a real kitchen environment, without needing any real data.

Simulation Benefits to Businesses  

Developers, engineers and researchers can quickly experiment with different kinds of robot designs in virtual environments, bypassing time-consuming and expensive physical testing methods.

Applying different kinds of robot designs, in combination with robot software, to test the robot’s programming in a virtual environment before building out the physical machine reduces risks of having quality issues to fix afterwards.

While this can vastly accelerate the development timeline, it can also drastically cut costs for building and testing robots and AI models while ensuring safety.

Additionally, robot simulation helps connect robots with business systems, such as inventory databases, so a robot knows where an item is located.

Simulation of cobots, or robots working with humans, promises to reduce injuries and make jobs easier, enabling more efficient delivery of all kinds of products.

And with packages arriving incredibly fast in homes everywhere, what’s not to like.

Learn about NVIDIA Isaac Sim, Jetson Orin, Omniverse Enterprise and Metropolis.

Learn more from this Deep Learning Institute course: Introduction to Robotic Simulations in Isaac Sim

Editor’s note: This post is part of our weekly In the NVIDIA Studio series, which celebrates featured artists, offers creative tips and tricks, and demonstrates how NVIDIA Studio technology improves creative workflows. 

MUE Studio, founded by 3D artists Minjin Kang and Mijoo Kim, specializes in art direction, photography and 3D design for campaigns and installations. It focuses on creating unique visual identities to help clients express themselves.

The creative duo behind the studio, based in New York, said they’ve always been fascinated with blurring the boundary between fantasy and reality in their work.

Together, they created the 3D video Somewhere in the World and a summer-themed series of artwork this week In the NVIDIA Studio, using Adobe After Effects, Autodesk 3ds Max and Unreal Engine 5.

GeForce RTX 4060 graphics cards are now available to order, starting at $299. The state-of-the-art NVIDIA Ada Lovelace architecture supercharges creative apps and productivity, while delivering immersive, AI-accelerated gaming with ray tracing and DLSS 3.

Plus, Chaos Vantage 2 is now available, offering new benefits for creators on RTX GPUs — like the GeForce RTX 4060 — including NVIDIA AI Denoiser for smoother image quality, as well as the direct light reservoir sampling feature powered by NVIDIA RTX Direct Illumination (RTXDI) technology.

Chaos Vantage 2 Powered by NVIDIA RTX

Chaos Vantage is a high-quality 3D visualization tool for artists who use the V-Ray rendering software. It enables users to quickly explore and present their work in a fully ray-traced environment that can handle massive scenes based on large models. Vantage 2 adds powerful new capabilities, enabling architectural-visualization and visual-effects artists to convey their designs more effectively.

Vantage 2 features the new NVIDIA AI Denoiser, which automatically removes noise from images when rendering high-quality output. Its upscaling mode increases frame rates and responsiveness in interactive rendering for a smoother, more efficient experience in the viewport.

The update also adds direct light reservoir sampling, powered by NVIDIA RTXDI technology, enabling artists to scale multiple dynamic light sources to sizable scenes — lightning fast — with no impact on performance.

Rounding out the Vantage update are new scene states to turn design-validation presentations into interactive storyboards; support for realistic vegetation movement in the wind and interaction with animated characters; and enhancements for popular render elements like back to beauty, material and object masks for compositing in image-editing apps.

Learn more about Vantage 2, available now.

Enter the Minds of MUE Studio

When designing an environment, MUE Studio aims to create a minimalistic space that invites viewers “to enter and take a break,” said Kim.

This is the foundation of Somewhere in the World, as well as the studio’s summer-themed series of artwork. By intentionally setting the time of day, placing a specific object or choosing a remote location, the artists ensure these pieces can become a viewer’s personal path to tranquility.

“Our purpose is to provide comfort and inspire people to dream of a better world,” said Kang. “We really appreciate comments we’ve received, saying things like, ‘These images are calm,’ and ‘I would like to be present in that space.’ Such words fuel us as artists.”

The visuals’ minimalist aesthetic was brought to life through the power of NVIDIA Studio laptops equipped with GeForce RTX 3090 graphics.

The duo began sculpting and modeling in Autodesk 3ds Max. RTX-accelerated AI denoising with the default Autodesk Arnold renderer made movement in the viewport highly interactive.

MUE Studio is especially interested in the human element of their art, the founders said. Kang focuses on the artistic tension between presence and absence, and Kim explores unique human cultures throughout the pieces.

The artists completed texture application, lighting and animations in Unreal Engine 5. RTX acceleration unlocked high-fidelity interactive visualization, leading to stunning photorealistic render quality.

Kim said MUE Studio’s go-to creative app for post-production is Adobe After Effects, which includes 30+ GPU-accelerated effects. The duo applied the app’s Sharpen, Brightness and Contrast and Gradient Ramp features when putting the finishing touches on their marvelous masterpieces.

“Our series of art provides an opportunity for viewers to momentarily escape reality, creating a safe, digital space where the community can relax and interact with one another,” Kang said.

Check out more of MUE Studio’s 3D creations on Instagram.

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