Posts in category: nVidia AI

A watershed moment on Nov. 22, 2022, was mostly virtual, yet it shook the foundations of nearly every industry on the planet.

On that day, OpenAI released ChatGPT, the most advanced artificial intelligence chatbot ever developed. This set off demand for generative AI applications that help businesses become more efficient, from providing consumers with answers to their questions to accelerating the work of researchers as they seek scientific breakthroughs, and much, much more.

Businesses that previously dabbled in AI are now rushing to adopt and deploy the latest applications. Generative AI — the ability of algorithms to create new text, images, sounds, animations, 3D models and even computer code — is moving at warp speed, transforming the way people work and play.

By employing large language models (LLMs) to handle queries, the technology can dramatically reduce the time people devote to manual tasks like searching for and compiling information.

The stakes are high. AI could contribute more than $15 trillion to the global economy by 2030, according to PwC. And the impact of AI adoption could be greater than the inventions of the internet, mobile broadband and the smartphone — combined.

The engine driving generative AI is accelerated computing. It uses GPUs, DPUs and networking along with CPUs to accelerate applications across science, analytics, engineering, as well as consumer and enterprise use cases.

Early adopters across industries — from drug discovery, financial services, retail and telecommunications to energy, higher education and the public sector — are combining accelerated computing with generative AI to transform business operations, service offerings and productivity.

Generative AI for Drug Discovery

Today, radiologists use AI to detect abnormalities in medical images, doctors use it to scan electronic health records to uncover patient insights, and researchers use it to accelerate the discovery of novel drugs.

Traditional drug discovery is a resource-intensive process that can require the synthesis of over 5,000 chemical compounds and yields an average success rate of just 10%. And it takes more than a decade for most new drug candidates to reach the market.

Researchers are now using generative AI models to read a protein’s amino acid sequence and accurately predict the structure of target proteins in seconds, rather than weeks or months.

Using NVIDIA BioNeMo models, Amgen, a global leader in biotechnology, has slashed the time it takes to customize models for molecule screening and optimization from three months to just a few weeks. This type of trainable foundation model enables scientists to create variants for research into specific diseases, allowing them to develop target treatments for rare conditions.

Whether predicting protein structures or securely training algorithms on large real-world and synthetic datasets, generative AI and accelerated computing are opening new areas of research that can help mitigate the spread of disease, enable personalized medical treatments and boost patient survival rates.

Generative AI for Financial Services

According to a recent NVIDIA survey, the top AI use cases in the financial services industry are customer services and deep analytics, where natural language processing and LLMs are used to better respond to customer inquiries and uncover investment insights. Another common application is in recommender systems that power personalized banking experiences, marketing optimization and investment guidance.

Advanced AI applications have the potential to help the industry better prevent fraud and transform every aspect of banking, from portfolio planning and risk management to compliance and automation.

Eighty percent of business-relevant information is in an unstructured format — primarily text — which makes it a prime candidate for generative AI. Bloomberg News produces 5,000 stories a day related to the financial and investment community. These stories represent a vast trove of unstructured market data that can be used to make timely investment decisions.

NVIDIA, Deutsche Bank, Bloomberg and others are creating LLMs trained on domain-specific and proprietary data to power finance applications.

Financial Transformers, or “FinFormers,” can learn context and understand the meaning of unstructured financial data. They can power Q&A chatbots, summarize and translate financial texts, provide early warning signs of counterparty risk, quickly retrieve data and identify data-quality issues.

These generative AI tools rely on frameworks that can integrate proprietary data into model training and fine-tuning, integrate data curation to prevent bias and use guardrails to keep conversations finance-specific.

Expect fintech startups and large international banks to expand their use of LLMs and generative AI to develop sophisticated virtual assistants to serve internal and external stakeholders, create hyper-personalized customer content, automate document summarization to reduce manual work, and analyze terabytes of public and private data to generate investment insights.

Generative AI for Retail

With 60% of all shopping journeys starting online and consumers more connected and knowledgeable than ever, AI has become a vital tool to help retailers match shifting expectations and differentiate from a rising tide of competition.

Retailers are using AI to improve customer experiences, power dynamic pricing, create customer segmentation, design personalized recommendations and perform visual search.

Generative AI can support customers and employees at every step through the buyer journey.

With AI models trained on specific brand and product data, they can generate robust product descriptions that improve search engine optimization rankings and help shoppers find the exact product they’re looking for. For example, generative AI can use metatags containing product attributes to generate more comprehensive product descriptions that include various terms like “low sugar” or “gluten free.”

AI virtual assistants can check enterprise resource planning systems and generate customer service messages to inform shoppers about which items are available and when orders will ship, and even assist customers with order change requests.

Fashable, a member of NVIDIA Inception’s global network of technology startups, is using generative AI to create virtual clothing designs, eliminating the need for physical fabric during product development. With the models trained on both proprietary and market data, this reduces the environmental impact of fashion design and helps retailers design clothes according to current market trends and tastes.

Expect retailers to use AI to capture and retain customer attention, deliver superior shopping experiences, and drive revenue by matching shoppers with the right products at the right time.

Generative AI for Telecommunications

In an NVIDIA survey covering the telecommunications industry, 95% of respondents reported that they were engaged with AI, while two-thirds believed that AI would be important to their company’s future success.

Whether improving customer service, streamlining network operations and design, supporting field technicians or creating new monetization opportunities, generative AI has the potential to reinvent the telecom industry.

Telcos can train diagnostic AI models with proprietary data on network equipment and services, performance, ticket issues, site surveys and more. These models can accelerate troubleshooting of technical performance issues, recommend network designs, check network configurations for compliance, predict equipment failures, and identify and respond to security threats.

Generative AI applications on handheld devices can support field technicians by scanning equipment and generating virtual tutorials to guide them through repairs. Virtual guides can then be enhanced with augmented reality, enabling technicians to analyze equipment in a 3D immersive environment or call on a remote expert for support.

New revenue opportunities will also open for telcos. With large edge infrastructure and access to vast datasets, telcos around the world are now offering generative AI as a service to enterprise and government customers.

As generative AI advances, expect telecommunications providers to use the technology to optimize network performance, improve customer support, detect security intrusions and enhance maintenance operations.

Generative AI for Energy

In the energy industry, AI is powering predictive maintenance and asset optimization, smart grid management, renewable energy forecasting, grid security and more.

To meet growing data needs across aging infrastructure and new government compliance regulations, energy operators are looking to generative AI.

In the U.S., electric utility companies spend billions of dollars every year to inspect, maintain and upgrade power generation and transmission infrastructure.

Until recently, using vision AI to support inspection required algorithms to be trained on thousands of manually collected and tagged photos of grid assets, with training data constantly updated for new components. Now, generative AI can do the heavy lifting.

With a small set of image training data, algorithms can generate thousands of physically accurate images to train computer vision models that help field technicians identify grid equipment corrosion, breakage, obstructions and even detect wildfires. This type of proactive maintenance enhances grid reliability and resiliency by reducing downtime, while diminishing the need to dispatch teams to the field.

Generative AI can also reduce the need for manual research and analysis. According to McKinsey, employees spend up to 1.8 hours per day searching for information — nearly 20% of the work week. To increase productivity, energy companies can train LLMs on proprietary data, including meeting notes, SAP records, emails, field best practices and public data such as standard material data sheets.

With this type of knowledge repository connected to an AI chatbot, engineers and data scientists can get instant answers to highly technical questions. For example, a maintenance engineer troubleshooting pitch control issues on a turbine’s hydraulic system could ask a bot: “How should I adjust the hydraulic pressure or flow to rectify pitch control issues on a model turbine from company X?” A properly trained model would deliver specific instructions to the user, who wouldn’t have to look through a bulky manual to find answers.

With AI applications for new system design, customer service and automation, expect generative AI to enhance safety and energy efficiency, as well as reduce operational expenses in the energy industry.

Generative AI for Higher Education and Research

From intelligent tutoring systems to automated essay grading, AI has been employed in education for decades. As universities use AI to improve teacher and student experiences, they’re increasingly dedicating resources to build AI-focused research initiatives.

For example, researchers at the University of Florida have access to one of the world’s fastest supercomputers in academia. They’ve used it to develop GatorTron — a natural language processing model that enables computers to read and interpret medical language in clinical notes that are stored in electronic health records. With a model that understands medical context, AI developers can create numerous medical applications, such as speech-to-text apps that support doctors with automated medical charting.

In Europe, an industry-university collaboration involving the Technical University of Munich is demonstrating that LLMs trained on genomics data can generalize across a plethora of genomic tasks, unlike previous approaches that required specialized models. The genomics LLM is expected to help scientists understand the dynamics of how DNA is translated into RNA and proteins, unlocking new clinical applications that will benefit drug discovery and health.

To conduct this type of groundbreaking research and attract the most motivated students and qualified academic professionals, higher education institutes should consider a whole-university approach to pool budget, plan AI initiatives, and distribute AI resources and benefits across disciplines.

Generative AI for the Public Sector

Today, the biggest opportunity for AI in the public sector is helping public servants to perform their jobs more efficiently and save resources.

The U.S. federal government employs over 2 million civilian employees — two-thirds of whom work in professional and administrative jobs.

These administrative roles often involve time-consuming manual tasks, including drafting, editing and summarizing documents, updating databases, recording expenditures for auditing and compliance, and responding to citizen inquiries.

To control costs and bring greater efficiency to routine job functions, government agencies can use generative AI.

Generative AI’s ability to summarize documents has great potential to boost the productivity of policymakers and staffers, civil servants, procurement officers and contractors. Consider a 756-page report recently released by the National Security Commission on Artificial Intelligence. With reports and legislation often spanning hundreds of pages of dense academic or legal text, AI-powered summaries generated in seconds can quickly break down complex content into plain language, saving the human resources otherwise needed to complete the task.

AI virtual assistants and chatbots powered by LLMs can instantly deliver relevant information to people online, taking the burden off of overstretched staff who work phone banks at agencies like the Treasury Department, IRS and DMV.

With simple text inputs, AI content generation can help public servants create and distribute publications, email correspondence, reports, press releases and public service announcements.

The analytical capabilities of AI can also help process documents to speed the delivery of vital services provided by organizations like Medicare, Medicaid, Veterans Affairs, USPS and the State Department.

Generative AI could be a pivotal tool to help government bodies work within budget constraints, deliver government services more quickly and achieve positive public sentiment.

Generative AI – A Key Ingredient for Business Success 

Across every field, organizations are transforming employee productivity, improving products and delivering higher-quality services with generative AI.

To put generative AI into practice, businesses need expansive amounts of data, deep AI expertise and sufficient compute power to deploy and maintain models quickly. Enterprises can fast-track adoption with the NeMo generative AI framework, part of NVIDIA AI Enterprise software, running on DGX Cloud. NVIDIA’s pretrained foundation models offer a simplified approach to building and running customized generative AI solutions for unique business use cases.

Learn more about powerful generative AI tools to help your business increase productivity, automate tasks, and unlock new opportunities for employees and customers. 

Arise, members! Capcom’s legendary role-playing game Dragon’s Dogma: Dark Arisen joins the GeForce NOW library today.

The RPG and THQ Nordic’s Jagged Alliance 3 are newly supported on GeForce NOW, playable on nearly any device.

From Dusk Till Pawn

Become the Arisen and take up the challenge in Capcom’s critically acclaimed RPG. Set in a huge open world, Dragon’s Dogma: Dark Arisen brings players on an epic adventure filled with challenging battles and action.

But there’s no need to go it alone: Adventure with up to three Pawns. These customizable AI companions fight independently, demonstrating prowess and ability they’ve developed based on traits learned from each player.

Players can share their Pawns online and reap rewards of treasures, tips and strategy hints for taking down terrifying enemies. Pawns can also be borrowed when specific skills are needed to complete various challenging quests.

Revisit Gransys or experience Dragon’s Dogma for the first time. Members can play the real Steam version of this RPG classic with support for stunning visuals and high-resolution graphics, even on devices like Macs, mobile devices and smart TVs. Priority members can adventure at up to 1080p 60 frames per second, or upgrade to an Ultimate membership for gameplay at up to 4K 120 fps, longer streaming sessions and RTX ON for supported games.

Game On

Another week means new games.

THQ Nordic’s tactical RPG Jagged Alliance 3 joins the cloud this week. Chaos reigns when the elected president of Grand Chien — a nation of rich natural resources and deep political divides — goes missing and a paramilitary force known as “The Legion” seizes control of the countryside. Recruit from a large cast of unique mercenaries and make choices to impact the country’s fate.

Members can look forward to the following this week:

• Jagged Alliance 3 (New release on Steam, July 14)
• Dragon’s Dogma: Dark Arisen (Steam)

On top of that, in collaboration with EE, the U.K.’s biggest and fastest mobile network, GeForce NOW launched new cloud gaming bundles featuring Priority and Ultimate memberships. To celebrate, check out how streamer Leah ‘Leahviathan’ Alexandra showcased GeForce NOW in action at the U.K.’s highest-altitude gaming den on the slopes of Ben Nevis, 1,500 feet above sea level in the clouds of the Scottish Highlands.

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

Who’s an NPC you’d want to be friends with IRL?

— NVIDIA GeForce NOW (@NVIDIAGFN) July 12, 2023

A crack NVIDIA team of five machine learning experts spread across four continents won all three tasks in a hotly contested, prestigious competition to build state-of-the-art recommendation systems.

The results reflect the group’s savvy applying the NVIDIA AI platform to real-world challenges for these engines of the digital economy. Recommenders serve up trillions of search results, ads, products, music and news stories to billions of people daily.

More than 450 teams of data scientists competed in the Amazon KDD Cup ‘23. The three-month challenge had its share of twists and turns and a nail-biter of a finish.

Shifting Into High Gear

In the first 10 weeks of the competition, the team had a comfortable lead. But in the final phase, organizers switched to new test datasets and other teams surged ahead.

The NVIDIANs shifted into high gear, working nights and weekends to catch up. They left a trail of round-the-clock Slack messages from team members living in cities from Berlin to Tokyo.

“We were working nonstop, it was pretty exciting,” said Chris Deotte, a team member in San Diego.

A Product by Any Other Name

The last of the three tasks was the hardest.

Participants had to predict which products users would buy based on data from their browsing sessions. But the training data didn’t include brand names of many possible choices.

“I knew from the beginning, this would be a very, very difficult test,” said Gilberto “Giba” Titericz.

KGMON to the Rescue

Based in Curitaba, Brazil, Titericz was one of four team members ranked as grandmasters in Kaggle competitions, the online Olympics of data science. They’re part of a team of machine learning ninjas who’ve won dozens of competitions. NVIDIA founder and CEO Jensen Huang calls them KGMON (Kaggle Grandmasters of NVIDIA), a playful takeoff on Pokémon.

In dozens of experiments, Titericz used large language models (LLMs) to build generative AIs to predict product names, but none worked.

In a creative flash, the team discovered a work-around. Predictions using their new hybrid ranking/classifier model were spot on.

Down to the Wire

In the last hours of the competition, the team raced to package all their models together for a few final submissions. They’d been running overnight experiments across as many as 40 computers.

Kazuki Onodera, a KGMON in Tokyo, was feeling jittery. “I really didn’t know if our actual scores would match what we were estimating,” he said.

Deotte, also a KGMON, remembered it as “something like 100 different models all working together to produce a single output … we submitted it to the leaderboard, and POW!”

The team inched ahead of its closest rival in the AI equivalent of a photo finish.

The Power of Transfer Learning

In another task, the team had to take lessons learned from large datasets in English, German and Japanese and apply them to meager datasets a tenth the size in French, Italian and Spanish. It’s the kind of real-world challenge many companies face as they expand their digital presence around the globe.

Jean-Francois Puget, a three-time Kaggle grandmaster based outside Paris, knew an effective approach to transfer learning. He used a pretrained multilingual model to encode product names, then fine-tuned the encodings.

“Using transfer learning improved the leaderboard scores enormously,” he said.

Blending Savvy and Smart Software

The KGMON efforts show the field known as recsys is sometimes more art than science, a practice that combines intuition and iteration.

It’s expertise that’s encoded into software products like NVIDIA Merlin, a framework to help users quickly build their own recommendation systems.

Benedikt Schifferer, a Berlin-based teammate who helps design Merlin, used the software to train transformer models that crushed the competition’s classic recsys task.

“Merlin provides great results right out of the box, and the flexible design lets me customize models for the specific challenge,” he said.

Riding the RAPIDS

Like his teammates, he also used RAPIDS, a set of open-source libraries for accelerating data science on GPUs.

For example, Deotte accessed code from NGC, NVIDIA’s hub for accelerated software. Called DASK XGBoost, the code helped spread a large, complex task across eight GPUs and their memory.

For his part, Titericz used a RAPIDS library called cuML to search through millions of product comparisons in seconds.

The team focused on session-based recommenders that don’t require data from multiple user visits. It’s a best practice these days when many users want to protect their privacy.

To learn more:

• Watch a GTC session on building session-based recommenders with Merlin.
• Take a recsys course from the NVIDIA Deep Learning Institute.
• Check out the next-item prediction workflow that’s part of NVIDIA AI Enterprise, a complete software suite with the security and support businesses require.
• And watch the video below.

Startup MosaicML is on a mission to help the AI community improve prediction accuracy, decrease costs and save time by providing tools for easy training and deployment of large AI models.

In this episode of NVIDIA’s AI Podcast, host Noah Kravitz speaks with MosaicML CEO and co-founder Naveen Rao about how the company aims to democratize access to large language models.

MosaicML, a member of NVIDIA’s Inception program, has identified two key barriers to widespread adoption: the difficulty of coordinating a large number of GPUs to train a model and the costs associated with this process.

MosaicML was in the news earlier this month when Databricks announced an agreement to acquire MosaicML for $1.3 billion.

Making training of models accessible is key for many companies that need control over model behavior, respect data privacy and iterate fast to develop new products based on AI.

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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.