Posts in category: nVidia AI

California has a new weapon against the wildfires that have devastated the state: AI.

A freshly launched system powered by AI trained on NVIDIA GPUs promises to provide timely alerts to first responders across the Golden State every time a blaze ignites.

The ALERTCalifornia initiative, a collaboration between California’s wildfire fighting agency CAL FIRE and the University of California, San Diego, uses advanced AI developed by DigitalPath.

Harnessing the raw power of NVIDIA GPUs and aided by a network of thousands of cameras dotting the Californian landscape, DigitalPath has refined a convolutional neural network to spot signs of fire in real time.

A Mission That’s Close to Home

DigitalPath CEO Jim Higgins said it’s a mission that means a lot to the 100-strong technology partner, which is nestled in the Sierra Nevada foothills in Chico, Calif., a short drive from the town of Paradise, where the state’s deadliest wildfire killed 85 people in 2018.

“It’s one of the main reasons we’re doing this,” Higgins said of the wildfire, the deadliest and most destructive in the history of the most populous U.S. state. “We don’t want people to lose their lives.”

The ALERTCalifornia initiative is based at UC San Diego’s Jacobs School of Engineering, the Qualcomm Institute and the Scripps Institution of Oceanography.

The program manages a network of thousands of monitoring cameras and sensor arrays and collects data that provides actionable, real-time information to inform public safety.

The AI program started in June and was initially deployed in six of Cal Fire’s command centers. This month it expanded to all of CAL FIRE’s 21 command centers.

DigitalPath began by building out a management platform for a network of cameras used to confirm California wildfires after a 911 call.

The company quickly realized there would be no way to have people examine images from the thousands of cameras relaying images to the system every ten to fifteen seconds.

So Ethan Higgins, the company’s system architect, turned to AI.

The team began by training a convolutional neural network on a cloud-based system running an NVIDIA A100 Tensor Core GPU and later transitioned to a system running on eight A100 GPUs.

The AI model is crucial to examining a system that sees almost 8 million images a day streaming in from over 1,000 first-party cameras, primarily in California, and thousands more from third-party sources nationwide, he said.

Impact of Wildfires

It’s arriving just in time.

Wildfires have ravaged California over the past decade, burning millions of acres of land, destroying thousands of homes and businesses and claiming hundreds of lives.

According to CAL FIRE, in 2020 alone, the state experienced five of its six largest and seven of its 20 most destructive wildfires.

And the total dollar damage of wildfires in California from 2019 to 2021 was estimated at over $25 billion.

The new system promises to give first responders a crucial tool to prevent such conflagrations.

In fact, during a recent interview with DigitalPath, the system detected two separate fires in Northern California as they ignited.

Every day, the system detects between 50 and 300 events, offering invaluable real-time information to local first responders.

Beyond Detection: Enhancing Capabilities

But AI is just part of the story.

The system is also a case study in how innovative companies can use AI to amplify their unique capabilities.

One of DigitalPath’s breakthroughs is its system’s ability to identify the same fire captured from diverse camera angles. DigitalPath’s system efficiently filters imagery down to a human-digestible level. The system filters 8 million daily images down to just 100 alerts, or 1.25 thousandths of one percent of total images captured.

“The system was designed from the start with human processing in mind,” Higgins said, ensuring that authorities receive a single, consolidated notification for every incident.

“We’ve got to catch every fire we can,” he adds.

Expanding Horizons

DigitalPath eventually hopes to expand its detection technology to help California detect more kinds of natural disasters.

And having proven its worth in California, DigitalPath is now in talks with state and county officials and university research teams across the fire-prone Western United States under its ALERTWest subsidiary.

Their goal: to help partners replicate the success of UC San Diego and ALERTCalifornia, potentially shielding countless lives and homes from the wrath of wildfires.

Featured image credit: SLworking2, via Flickr, Creative Commons license, some rights reserved.

With the help of AI, robots, tractors and baby strollers — even skate parks — are becoming autonomous. One developer, Kabilan KB, is bringing autonomous-navigation capabilities to wheelchairs, which could help improve mobility for people with disabilities.

The undergraduate from the Karunya Institute of Technology and Sciences in Coimbatore, India, is powering his autonomous wheelchair project using the NVIDIA Jetson platform for edge AI and robotics.

The autonomous motorized wheelchair is connected to depth and lidar sensors — along with USB cameras — which allow it to perceive the environment and plan an obstacle-free path toward a user’s desired destination.

“A person using the motorized wheelchair could provide the location they need to move to, which would already be programmed in the autonomous navigation system or path-planned with assigned numerical values,” KB said. “For example, they could press ‘one’ for the kitchen or ‘two’ for the bedroom, and the autonomous wheelchair will take them there.”

An NVIDIA Jetson Nano Developer Kit processes data from the cameras and sensors in real time. It then uses deep learning-based computer vision models to detect obstacles in the environment.

The developer kit acts as the brain of the autonomous system — generating a 2D map of its surroundings to plan a collision-free path to the destination — and sends updated signals to the motorized wheelchair to help ensure safe navigation along the way.

About the Maker

KB, who has a background in mechanical engineering, became fascinated with AI and robotics during the pandemic, when he spent his free time searching up educational YouTube videos on the topics.

He’s now working toward a bachelor’s degree in robotics and automation at the Karunya Institute of Technology and Sciences and aspires to one day launch a robotics startup.

KB, a self-described supporter of self-education, has also received several certifications from the NVIDIA Deep Learning Institute, including “Building Video AI Applications at the Edge on Jetson Nano” and “Develop, Customize and Publish in Omniverse With Extensions.”

Once he learned the basics of robotics, he began experimenting with simulation in NVIDIA Omniverse, a platform for building and operating 3D tools and applications based on the OpenUSD framework.

“Using Omniverse for simulation, I don’t need to invest heavily in prototyping models for my robots, because I can use synthetic data generation instead,” he said. “It’s the software of the future.”

His Inspiration

With this latest NVIDIA Jetson project, KB aimed to create a device that could be helpful for his cousin, who has a mobility disorder, and other people with disabilities who might not be able to control a manual or motorized wheelchair.

“Sometimes, people don’t have the money to buy an electric wheelchair,” KB said. “In India, only upper- and middle-class people can afford them, so I decided to use the most basic type of motorized wheelchair available and connect it to the Jetson to make it autonomous.”

The personal project was funded by the Program in Global Surgery and Social Change, which is jointly positioned under the Boston Children’s Hospital and Harvard Medical School.

His Jetson Project

After purchasing the basic motorized wheelchair, KB connected its motor hub with the NVIDIA Jetson Nano and lidar and depth cameras.

He trained the AI algorithms for the autonomous wheelchair using YOLO object detection on the Jetson Nano, as well as the Robot Operating System, or ROS, a popular software for building robotics applications.

The wheelchair can tap these algorithms to perceive and map its environment and plan a collision-free path.

“The NVIDIA Jetson Nano’s real-time processing speed prevents delays or lags for the user,” said KB, who’s been working on the project’s prototype since June. The developer dives into the technical components of the autonomous wheelchair on his blog. A demo of the autonomous wheelchair has also been featured on the Karunya Innovation and Design Studio YouTube channel.

Looking forward, he envisions his project could be expanded to allow users to control a wheelchair using brain signals from electroencephalograms, or EEGs, that are connected to machine learning algorithms.

“I want to make a product that would let a person with a full mobility disorder control their wheelchair by simply thinking, ‘I want to go there,’” KB said.

Learn more about the NVIDIA Jetson platform.

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.

Releasing a 3D tutorial dubbed The Easiest VFX Tutorial Ever takes supreme confidence and the skills to back it up.

Steve Lund a.k.a. CG Geek — the featured artist of this week’s In the NVIDIA Studio installment — has both in spades. It’s no surprise that over 1 million people have subscribed to his YouTube channel, which features tutorials on animation and visual effects (VFX) as well as select tech reviews.

CG Geek has been a content creator for over 13 years, starting with videos on stop-motion animation before moving on to 3D software. Films and movies are his primary sources of inspiration. He grew up creating short films with his family — experimenting with and implementing video effects and 3D characters — which became a critical foundation for his current work.

Artists can strengthen their creative arsenal with the new Microsoft Surface Laptop Studio 2, available for pickup today. It’s powered by GeForce RTX 4060, GeForce RTX 4050 or NVIDIA RTX 2000 Ada Generation Laptop GPUs with 13th Gen Intel Core processors, up to 64GB of RAM and a 2TB SSD. It features a bright, vibrant 14.4-inch PixelSense Flow touchscreen, a 120Hz refresh rate, and Dolby Vision IQ and HDR to deliver sharper colors.

The Easiest VFX Tutorial Ever

CG Geek also happens to be a geek for Blender, free for 3D enthusiasts, who regularly create impressive, individualistic art.

“I love the amazing Blender 3D community,” he said. “Whenever you need inspiration or creative feedback, they’re the most helpful, kind and talented collective of ever-growing artists.”

CG Geek wanted to make a tutorial that could prove that virtually anyone could get started in VFX with relative ease, from anywhere, at any time.

The first step, he instructs, is to capture video footage. To keep things simple, CG Geek recommends mounting a camera or mobile device to a tripod. Note that the camera lens determines the focal length and sensor size — critical details to input in Blender later in the process.

Keep a close eye on the video footage lighting for shadows and light intensity — it helps to snap a straight-down photo of the environment the 3D element will populate, namely for light bounces, to help create more realistic shadows.

Next, secure a 3D model. Create one with guidance from an NVIDIA Studio blog or watch detailed tutorials on the Studio YouTube channel. Alternatively, look online for a 3D model equipped with basic physically based rendering materials, as well as a roughness and normal map.

Next, combine the video footage and 3D materials. Open Blender, import the video footage and line up the 3D grid floor to the surface where the model will be presented. The 3D grid doubles as a shadow catcher that will grab the shadows being cast from the 3D elements. With an added texture, lighting will bounce back against the object, resulting in heightened realism.

Then, light the 3D model to match the video footage. Most commonly, this is achieved by acquiring a high-dynamic range image (HDRI), a panorama with lighting data. CG Geek recommends Poly Haven for free, high-quality HDRIs. The key is picking one that resembles the lighting, color, shadow and intensity of the video footage.

Use the HDRI lighting to align the sun’s rotation with the shadows of the footage, adding further realism.

From there, import camera information into Blender and render out passes for the 3D model over a transparent background in Cycles. Create as many render layers as possible for added post-render editing flexibility, especially in compositing. Shadowcatcher, glossy passes, Z depth and ambient occlusion layers are recommended for advanced users.

These layers can then be combined in popular creative apps like Adobe Premiere Pro, After Effects, Blackmagic Design’s DaVinci Resolve or any of the over 100 NVIDIA RTX GPU-accelerated apps. This workflow, in particular, will be completed in Blender’s custom compositor.

Add shadows to the live footage with a multiple overlay. Then, carry over the 3D elements render layer to adjust the intensity of the shadows, helping them mesh better with the video capture. Individual layers can be edited to match the desired tone.

CG Geek made use of Blender Cycles’ RTX-accelerated OptiX ray tracing in the viewport. “Rendering in Cycles with multiple render layers and passes, along with the NVIDIA OptiX Denoiser, made animations and early tests a breeze,” he said.

Finally, perform simple masking on areas where the 3D model passes in front of or behind objects. CG Geek’s one-minute YouTube tutorial can help guide this process. DaVinci Resolve or Premiere Pro’s AI-powered magic mask features can further speed the process by automatically masking background elements, saving the effort of painstakingly editing videos frame by frame.

These AI features are all accelerated by the GeForce RTX 4070 GPU equipped in CG Geek’s ASUS Zenbook 14 NVIDIA Studio laptop.

For CG Geek, getting reps in, making mistakes and strengthening weaknesses are the keys to evolving as an artist. “Don’t get hung up on the details!” he stressed. “Give yourself a deadline and then get started on another project.”

For more on the basics of 3D VFX and CGI with Blender, accelerated by the NVIDIA Studio platform and RTX GPUs, watch his featured five-minute tutorial.

Check out CG Geek on YouTube.

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In a talk, now available online, NVIDIA Chief Scientist Bill Dally describes a tectonic shift in how computer performance gets delivered in a post-Moore’s law era.

Each new processor requires ingenuity and effort inventing and validating fresh ingredients, he said in a recent keynote address at Hot Chips, an annual gathering of chip and systems engineers. That’s radically different from a generation ago, when engineers essentially relied on the physics of ever smaller, faster chips.

The team of more than 300 that Dally leads at NVIDIA Research helped deliver a whopping 1,000x improvement in single GPU performance on AI inference over the past decade (see chart below).

It’s an astounding increase that IEEE Spectrum was the first to dub “Huang’s Law” after NVIDIA founder and CEO Jensen Huang. The label was later popularized by a column in the Wall Street Journal.

The advance was a response to the equally phenomenal rise of large language models used for generative AI that are growing by an order of magnitude every year.

“That’s been setting the pace for us in the hardware industry because we feel we have to provide for this demand,” Dally said.

In his talk, Dally detailed the elements that drove the 1,000x gain.

The largest of all, a sixteen-fold gain, came from finding simpler ways to represent the numbers computers use to make their calculations.

The New Math

The latest NVIDIA Hopper architecture with its Transformer Engine uses a dynamic mix of eight- and 16-bit floating point and integer math. It’s tailored to the needs of today’s generative AI models. Dally detailed both the performance gains and the energy savings the new math delivers.

Separately, his team helped achieve a 12.5x leap by crafting advanced instructions that tell the GPU how to organize its work. These complex commands help execute more work with less energy.

As a result, computers can be “as efficient as dedicated accelerators, but retain all the programmability of GPUs,” he said.

In addition, the NVIDIA Ampere architecture added structural sparsity, an innovative way to simplify the weights in AI models without compromising the model’s accuracy. The technique brought another 2x performance increase and promises future advances, too, he said.

Dally described how NVLink interconnects between GPUs in a system and NVIDIA networking among systems compound the 1,000x gains in single GPU performance.

No Free Lunch  

Though NVIDIA migrated GPUs from 28nm to 5nm semiconductor nodes over the decade, that technology only accounted for 2.5x of the total gains, Dally noted.

That’s a huge change from computer design a generation ago under Moore’s law, an observation that performance should double every two years as chips become ever smaller and faster.

Those gains were described in part by Denard scaling, essentially a physics formula defined in a 1974 paper co-authored by IBM scientist Robert Denard. Unfortunately, the physics of shrinking hit natural limits such as the amount of heat the ever smaller and faster devices could tolerate.

An Upbeat Outlook

Dally expressed confidence that Huang’s law will continue despite diminishing gains from Moore’s law.

For example, he outlined several opportunities for future advances in further simplifying how numbers are represented, creating more sparsity in AI models and designing better memory and communications circuits.

Because each new chip and system generation demands new innovations, “it’s a fun time to be a computer engineer,” he said.

Dally believes the new dynamic in computer design is giving NVIDIA’s engineers the three opportunities they desire most: to be part of a winning team, to work with smart people and to work on designs that have impact.

Pixellot is scoring with vision AI — making it easier for organizations to deliver real-time sports broadcasting and analytics to viewers across the globe.

A member of the NVIDIA Metropolis vision AI partner ecosystem, the company based near Tel Aviv offers an AI-powered platform that automates the capturing, streaming and analysis of sporting events.

It’s changing the game for fans, coaches and players of nearly 20 different sports — not just basketball and soccer but also rugby and handball — as it broadcasts events and provides analytics from more than 30,000 venues across 70+ countries. In the U.S., Pixellot powers the broadcasting of over a million games every year through its partnership with the NFHS Network, a leader in streaming live and on-demand high school sports.

Through its broadcasting partners like the NFHS Network, MLB and others, Pixellot provides professional analytics, post-match breakdowns and highlights based on jersey numbers with shot charts and heat maps — which can be especially useful for coaches and players of school and pro sports alike as they study their moves to up their game. It also enables interactive experiences for users, who can manipulate viewframes and cut their own highlights for a game.

Recently, SuperSport Schools, a company based in Cape Town, South Africa, deployed the Pixellot platform to power an app that broadcasts student athletics across the nation, where more than 1,500 high schools are active in sports.

“Our goal is to democratize the coverage of sports with the help of AI and automation,” said Yossi Tarablus, who leads marketing at Pixellot, a member of the NVIDIA Inception program for cutting-edge startups. “Using the NVIDIA Jetson platform for edge AI, Pixellot brings powerful technology for sports broadcasting and analytics to some of the world’s most remote areas.”

How Pixellot Works

During peak sports seasons, about 200,000 games a month are broadcasted across the globe using the Pixellot platform, according to Tarablus.

Lightweight Pixellot cameras powered by NVIDIA Jetson capture high-quality video of games, matches and even practices — and livestream them in high definition to users through an app in real time with an overlaid scoreboard, live stats, commentary and more.

The platform creates an automatic viewframe that simulates a camera operator, optimizes videos and corrects scene lighting using NVIDIA RTX ray-tracing technology.

In addition, the platform helps organizations and companies monetize sports while making them more accessible to viewers, as it enables over-the-top, or OTT, streaming — direct streaming over the internet without the need for a traditional cable or satellite TV provider.

In all of its camera setups, the Metropolis member runs the NVIDIA DeepStream software development kit for AI-powered video streaming analytics. And the company relies on the NVIDIA TensorRT SDK for high-performance deep learning inference.

“NVIDIA Jetson made it possible for Pixellot to create the most accurate and affordable AI-powered camera solution for broadcasting live sporting events,” said Gal Oz, chief technology officer and cofounder of Pixellot. “The versatility of Jetson modules in terms of camera pipeline, encoders and AI capabilities enabled Pixellot to develop multiple products based on the same hardware and software platform.”

Broadcasting South African School Sports

High-quality, real-time broadcasts of athletics are difficult to produce without access to a slew of graphics and data.

As the NVIDIA Jetson Orin NX module enables AI-powered video processing and GPU-accelerated computing right at the edge — on the field or at courtside — Pixellot lets organizations broadcast sports from anywhere.

“It’s amazing how many people have told us stories about a moment they were empowered to share with their children thanks to SuperSport Schools and Pixellot, because they couldn’t be there physically but were present through live or on-demand video,” said Kelvin Watt, managing director of Capitalize Media and SuperSport Schools, on the Pixellot deployment in South Africa.

The SuperSport Schools app, which is free and recently reached 600,000 subscribers, was the first to broadcast a junior nationals track race in the country.

At the event last year, a student named Viwe Jingqi broke 50-plus-year national records for both the 100- and 200-meter races for South African girls under 18 years old. People all over the world could easily witness these historic victories through the SuperSport Schools app, powered by Pixellot.

Building a Smart Sports City in China

In China, tech giant Baidu and the Chengdu Sports Authority are using Pixellot technology in an initiative to develop a smart sports city, with an initial focus on broadcasting community soccer.

Chengdu, the capital of southwestern China’s Sichuan province, is a sports-oriented city and was the host of this year’s World University Games, an event sanctioned by the International University Sports Federation.

“Pixellot’s AI-driven sports production solutions are a perfect fit for our strategic vision of delivering innovative technology solutions to communities,” said Liu Chuan, solution director of the intelligent cloud sports industry at Baidu.

“Broadcasting community soccer with vision AI is part of the Chengdu initiative’s efforts to emphasize the health benefits of engaging in sports recreationally,” said Tarablus. “It moves the spotlight from pro or Olympic sports to the importance of athletics for all.”

Learn more about the NVIDIA Metropolis application framework, developer tools and partner ecosystem.

The wait is over. GeForce NOW Ultimate members can experience Cyberpunk 2077: Phantom Liberty on GOG.com at full GeForce RTX 4080 quality, with support for NVIDIA DLSS 3.5 technology.

It’s part of an action-packed GFN Thursday, with 26 more games joining the cloud gaming platform’s library, including Quake II from id Software.

A New Look for Night City

Take on a thrilling challenge with Phantom Liberty, an all-new adventure for Cyberpunk 2077. When the orbital shuttle of the President of the New United States of America is shot down over the deadliest district of Night City, there’s only one person who can save her. Become V, a cyberpunk for hire, and dive into a tangled web of espionage and political intrigue, unraveling a story that connects the highest echelons of power with the brutal world of black-market mercenaries.

Ultimate members can return to the neon lights of Night City and experience the benefits of NVIDIA DLSS 3.5 and its new Ray Reconstruction technology. These updates enhance the quality of full ray tracing in Cyberpunk 2077’s Ray Tracing: Overdrive Mode, as part of the game’s 2.0 update available for the base game for free and included with the Phantom Liberty expansion. Upgrade to a GeForce NOW Ultimate membership today to see Night City at its best.

Prepare for War

Experience the authentic, enhanced and complete version of id Software’s critically acclaimed first-person shooter, Quake II, now streaming from the cloud.

Humankind is at war with the Strogg, a hostile alien race that’s attacked Earth. In response, humanity launched a strike on the Strogg homeworld — which failed. Outnumbered and outgunned, battle through fortified military installations to shut down the enemy’s war machine. Only then will the fate of humanity be decided.

Quake II includes a new, enhanced version of id Software’s classic, along with both original mission packs: “The Reckoning” and “Ground Zero.” Plus, battle through 28 campaign levels in MachineGames’ all-new “Call of the Machine” expansion and play through the exclusive levels from Quake II 64 for the first time on PC. Blast the Stroggs or friends in classic multiplayer modes at up to 4K and 120 frames per second or with ultrawide resolutions for GeForce NOW Ultimate members.

Nice Shootin,’ Tex

The GeForce NOW Ultimate KovaaK’s challenge is complete, and the results are in: Ultimate power means more ultimate wins. Members worked to sharpen their skills and win amazing prizes during the challenge while experiencing the power of Ultimate for themselves. With up to 240 fps streaming at ultra-low latency, gamers are playing up to their ultimate potential, just by upgrading to an Ultimate membership.

The proof is in the data. Check out some powerful stats showing what Ultimate members accomplished:

• Nearly 15,000 people took on the challenge, playing over 120,000 sessions.
• Members saw a 2x boost in scores when playing on Ultimate over a Free membership.
• All of the leaderboard’s top 25 slots were filled with those playing on Ultimate.

But don’t just take our word for it. Here’s what it felt like for TinooQ, who placed third overall in the challenge:

“As a long-time KovaaK’s user, transitioning to this platform was seamless, as the precision and responsiveness was nothing short of extraordinary. 

“The minimal latency and the consistent 240 fps made me think that many people could rely solely on the GeForce NOW Ultimate plan and a monitor, that’s all. I found it perfect for top gaming, saving a lot of money and the PC hardware headaches I suffered when building mine.” — TinooQ

And check out what the press had to say about the Ultimate membership tier:

“GeForce NOW KovaaK’s Challenge Proves Gaming At Glorious 240 FPS Matters” – Hot Hardware

“Hot dang does GeForce Now Ultimate ever deliver.” – Tom’s Guide

“NVIDIA GeForce NOW has held the crown for cloud gaming performance for a while now, and it’s just getting better.” – 9to5Google

“Unsurprisingly, NVIDIA says 98% of the users who tried Kovaak’s Challenge on the GeForce NOW Ultimate tier have seen improvements in their test results over the free tier.” – Wccftech

“Nvidia has taken a different approach to cloud gaming: Instead of boosting their library and settling for 1080p 60fps, Nvidia’s GeForce Now service prioritizes performance, implementing faster graphics cards for players to use.” – SlashGear

“One of the distinguishing factors of GeForce Now is its superior image quality and lack of noticeable input delay. ” – Game Is Hard

“NVIDIA’s GeForce NOW is widely considered one of the best cloud gaming platforms in terms of latency, visual fidelity, and overall experience.” — TweakTown

Everyone’s a winner when they play on Ultimate. Upgrade today for the best performance in the cloud, even when streaming popular shooters like Counter Strike, Destiny 2, Tom Clancy’s Rainbow Six Siege and more, where every frame counts.

Even better, Ultimate members get a free copy of KovaaK’s – the world’s best aim trainer. Don’t miss this chance to claim the reward, starting today, only for Ultimate members. Be on the lookout for an email starting today, available only for a limited time.

Challenge Accepted

Square Enix’s Infinity Strash: DRAGON QUEST The Adventure of Dai leads 26 new titles in the GeForce NOW library this week. In this action role-playing game based on the popular anime and manga series of the same name, Dai and his friends must fight the Dark Lord Hadlar and his evil army of monsters. Fulfill Dai’s dream of becoming a hero in this game, which features fast-paced, dynamic combat, stunning anime-style graphics and a rich storyline.

Here’s the full list of what’s joining this week:

• These Doomed Isles (New release on Steam, Sept. 25)
• Paleo Pines (New release on Steam, Sept. 26)
• Infinity Strash: DRAGON QUEST The Adventure of Dai (New release on Steam, Sept. 28)
• Pizza Possum (New release on Steam, Sept. 28)
• Wildmender (New release on Steam, Sept. 28)
• Overpass 2 (New release on Steam, Sept. 28)
• Soulstice (New release on Epic Games Store, Free on Sept. 28)
• Amnesia: Rebirth (Xbox, available on PC Game Pass)
• BlazBlue: Cross Tag Battle (Xbox, available on PC Game Pass)
• Bramble: The Mountain King (Xbox, available on PC Game Pass)
• Broforce (Steam)
• Don Duality (Steam)
• Doom Eternal (Xbox, available on PC Game Pass)
• Dordogne (Xbox, available on PC Game Pass)
• Dust Fleet (Steam)
• Eastern Exorcist (Xbox, available on PC Game Pass)
• Figment 2: Creed Valley (Xbox, available on PC Game Pass)
• I Am Fish (Xbox)
• Necesse (Steam)
• A Plague Tale: Innocence (Xbox)
• Quake II (Steam, Epic Games Store and Xbox, available on PC Game Pass)
• Road 96 (Xbox)
• Spacelines from the Far Out (Xbox)
• Totally Reliable Delivery Service (Xbox, available on PC Game Pass)
• Warhammer 40,000: Battlesector (Xbox, available on PC Game Pass)
• Yooka-Laylee and the Impossible Lair (Xbox)

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

DENZA, the luxury electric-vehicle brand and joint venture between BYD and Mercedes-Benz, is debuting new intelligent driving features for its entire N7 model lineup, powered by the NVIDIA DRIVE Orin system-on-a-chip (SoC).

The N7 series was introduced earlier this year as a family of spacious five-seater SUVs for commuters looking to sport a deluxe EV with advanced driving functionality.

All N7 models can be equipped with the NVIDIA DRIVE Orin SoC for high-performance compute to simultaneously run in-vehicle applications and deep neural networks for automated driving.

NVIDIA DRIVE Orin serves as the brain behind DENZA’s proprietary Commuter Smart Driving system, which offers an array of smart features, including:

• Navigate on autopilot for high-speed, all-scenario assisted driving.
• Intelligent speed-limit control and emergency lane-keeping aid, for safer commutes on urban roads and highways.
• Enhanced automatic emergency braking and front cross-traffic alert for increased safety at intersections and on narrow streets.
• Automated parking assist, which scouts for parking spots, identifying horizontal, vertical and diagonal spaces to ease the challenge of parking in crowded areas.

Next-Gen Car Configuration

In addition to adopting accelerated computing in the car, DENZA is one of the flagship automotive trailblazers using the NVIDIA Omniverse Cloud platform to build and deploy next-generation car configurators to deliver greater personalization options for the consumer’s vehicle-purchasing experience.

Learn more about the DENZA N7 3D configurator.

Medical-device company Invenio Imaging is developing technology that enables surgeons to evaluate tissue biopsies in the operating room, immediately after samples are collected — providing in just three minutes AI-accelerated insights that would otherwise take weeks to obtain from a pathology lab.

In a surgical biopsy, a medical professional removes samples of cells or tissue that pathologists analyze for diseases such as cancer. By delivering these capabilities through a compact, AI-powered imaging system within the treatment room, Invenio aims to support rapid clinical decision-making.

“This technology will help surgeons make intraoperative decisions when performing a biopsy or surgery,” said Chris Freudiger, chief technology officer of Silicon Valley-based Invenio. “They’ll be able to rapidly evaluate whether the tissue sample contains cancerous cells, decide whether they need to take another tissue sample and, with the AI models Invenio is developing, potentially make a molecular diagnosis for personalized medical treatment within minutes.”

Quicker diagnosis enables quicker treatment. It’s especially critical for aggressive types of cancer that could grow or spread significantly in the weeks it takes for biopsy results to return from a dedicated pathology lab.

Invenio is a member of NVIDIA Inception, a program that provides cutting-edge startups with technological support and AI platform guidance. The company accelerates AI training and inference using NVIDIA GPUs and software libraries.

Laser Focus on Cancer Care

Invenio’s NIO Laser Imaging System is a digital pathology tool that accelerates the imaging of fresh tissue biopsies. It’s been used in thousands of procedures in the U.S. and Europe. In 2021, it received the CE Mark of regulatory approval in Europe.

The company plans to adopt the NVIDIA Jetson Orin series of edge AI modules for its next-generation imaging system, which will feature near real-time AI inference accelerated by the NVIDIA TensorRT SDK.

“We’re building a layer of AI models on top of our imaging capabilities to provide physicians with not just the diagnostic image but also an analysis of what they’re seeing,” Freudiger said. “With the AI performance provided by NVIDIA Jetson at the edge, they’ll be able to quickly determine what kinds of cancer cells are present in a biopsy image.”

Invenio uses a cluster of NVIDIA RTX A6000 GPUs to train neural networks with tens of millions of parameters on pathologist-annotated images. The models were developed using the TensorFlow deep learning framework and trained on images acquired with NIO imaging systems.

“The most powerful capability for us is the expanded VRAM on the RTX A6000 GPUs, which allows us to load large batches of images and capture the variability of features,” Freudiger said. “It makes a big difference for AI training.”

On the Path to Clinical Deployment

One of Invenio’s AI products, NIO Glioma Reveal, is approved for clinical use in Europe and available for research use in the U.S. to help identify areas of cancerous cells in brain tissue.

A team of Invenio’s collaborators from the University of Michigan, New York University, University of California San Francisco, the Medical University of Vienna and University Hospital of Cologne recently developed a deep learning model that can find biomarkers of cancerous tumors with 93% accuracy in 90 seconds.

With this ability to analyze different molecular subtypes of cancer within a tissue sample, doctors can predict how well a patient will respond to chemotherapy — or determine whether a tumor has been successfully removed during surgery.

Beyond its work on brain tissue analysis, Invenio this year announced a clinical research collaboration with Johnson & Johnson’s Lung Cancer Initiative to develop and validate an AI solution that can help evaluate lung biopsies. The AI model will help doctors rapidly determine whether collected tissue samples contain cancer.

Lung cancer is the world’s deadliest form of cancer, and in the U.S. alone, lung nodules are found in over 1.5 million patients each year. Once approved for clinical use, Invenio’s NIO Lung Cancer Reveal tool aims to shorten the time needed to analyze tissue biopsies for these patients.

As part of this initiative, Invenio will run a clinical study before submitting the NVIDIA Jetson-powered AI solution for FDA approval.

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As generative AI sweeps across corporate boardrooms around the world, global telecommunications companies are exploring how to cost-effectively deliver many of these new AI applications to the edge over 5G and upcoming 6G networks.

Telcos plan to deploy over 17 million 5G microcells and towers worldwide by 2025. Building, managing and optimizing this new infrastructure while maintaining quality-of-service delivery and maximizing the customer experience is the industry’s next big challenge.

Today, NTT DOCOMO announced it is deploying a GPU-accelerated wireless solution in its network in Japan. This makes it the first-ever telco in the world to deploy a GPU-accelerated commercial 5G network.

DOCOMO’s move aims to address the multibillion dollar problem of driving improvements in performance, total cost of ownership and energy efficiency while unlocking the flexibility, scalability and supply chain diversity promise of Open RAN.

The 5G Open RAN solution uses a high-performance 5G virtual radio access network (vRAN) from Fujitsu built on the NVIDIA Aerial vRAN stack and NVIDIA Converged Accelerators. This combination enables telcos to create a fully software- and cloud-defined network that can dynamically allocate resources using industry-standard equipment.

“Open RAN offers the opportunity to build next-generation 5G networks with unprecedented flexibility and scalability thanks to multivendor connections,” said Sadayuki Abeta, global head of Open RAN solutions at NTT DOCOMO. “We look forward to continuing working with NVIDIA on infrastructure solutions that meet those needs.”

The 5G Open RAN solution is the first 5G vRAN for telco commercial deployment using the NVIDIA Aerial platform, with a hardened, carrier-grade vRAN stack. The platform brings together the NVIDIA Aerial vRAN stack for 5G, AI frameworks, accelerated compute infrastructure and long-term software support and maintenance.

Cost and Energy-Efficiency Benefits of GPU Acceleration

Working with offerings from Fujitsu and Wind River, the new 5G solution uses the NVIDIA Aerial platform to lower costs and reduce power consumption. Compared to its existing 5G network deployments, DOCOMO says the solution reduces total costs by up to 30%, network design utilization by up to 50%, and power consumption at base stations by up to 50%.

“Delivering a 5G Open RAN network that meets stringent performance requirements of operators is a significant accomplishment,” said Masaki Taniguchi, senior vice president and head of the Mobile System Business Unit at Fujitsu Limited. “Using our Fujitsu vCU/vDU, in combination with NVIDIA Aerial platform, will help network operators to efficiently build high-performance 5G networks for consumers and businesses alike.”

NVIDIA’s contribution to the DOCOMO rollout is part of a growing portfolio of 5G solutions that are driving transformation in the telecommunications industry. Anchored on NVIDIA Aerial vRAN stack and NVIDIA Converged Accelerators — combined with NVIDIA BlueField data processing units (DPUs) and a suite of AI frameworks — NVIDIA provides a high-performance, software-defined, cloud-native, AI-enabled 5G for on-premises and telco operators’ RAN.

Fujitsu, NVIDIA and Wind River have been working under the OREX (5G Open RAN service brand), which was launched by DOCOMO in February 2021, to develop the Open RAN 5G vRAN. OREX has been deployed in Japan based on Fujitsu’s virtualized DU (vDU) and virtualized CU (vCU) and leverages commercial off-the-shelf servers, the Wind River cloud platform, Fujitsu’s 5G vRAN software and the NVIDIA Aerial vRAN stack and NVIDIA Converged Accelerators.

“Wind River is delighted to work with NTT DOCOMO, Fujitsu and NVIDIA towards a vision of improved efficiency of RAN deployments and operations,” said Paul Miller, chief technology officer at Wind River. “Wind River Studio provides a cloud-native, distributed cloud, automation, and analytics solution based on open source, so that operators can deploy and manage their 5G edge networks globally at high scale with faster innovation. This solution is proven in highly scaled production deployments today.”

OREX: Building Out From Japan and Beyond

DOCOMO and its partners in OREX are promoting a multivendor, Open RAN-compliant 5G vRAN to the global operator community. The commercial deployment in Japan is a first step in the vision of OREX, where members can commercially validate their solutions and then promote them to other operators globally.

NVIDIA is working with DOCOMO and other partners to support operators around the world to deploy high-performance, energy-efficient, software-defined, commercial 5G vRAN.

Talk about a Grand Slam.

Denny’s CEO Kelli Valade was joined Tuesday by NVIDIA CEO Jensen Huang Tuesday to unveil a plaque at the Silicon Valley Denny’s where NVIDIA’s founders hatched their idea for a chip that would enable realistic 3D graphics on personal computers.

“This is a place where we fuel ideas, your story is so inspiring it will continue to inspire people at Dennny’s,” Valade said, as she presented the plaque to Huang.

“Denny’s has taught me so many lessons,” Huang said.

Both CEOs got their start working in diners. Valade got her first job as a waitress at a diner when she was 16. Huang got his first job at Denny’s in Portland when he was 15.

“I was a dishwasher, I was a busboy, I waited tables,” Huang said. “No one can carry more coffee cups than I can.”

To fuel even more great ideas, Valade announced the Denny’s Trillion-Dollar Incubator Contest — offering $25,000 in seed money for the next $1 trillion idea.

The contest is open to anyone with a creative and innovative idea that could impact the world. The only catch? The idea must originate — like NVIDIA — in a Denny’s booth.

NVIDIA, the leading accelerated computing and AI company, got its start at the 24-hour diner chain known for favorites such as its signature Grand Slam combo.

In 1993, three friends — Huang, Chris Malachowsky and Curtis Priem — met at Denny’s to discuss creating a chip that would enable realistic 3D graphics on personal computers.

The Denny’s just off a busy thoroughfare in the heart of Silicon Valley was the perfect place to start a business, said Huang, who lived nearby at the time with his wife and kids.

“It had all the coffee you could drink and no one could chase you out,” Huang told Valade.

Tuesday’s event took place in a corner of the bustling restaurant — one of the most popular Denny’s locations in Northern California — as families, retirees, and workers coming off the night shift piled in for plates piled high with eggs and pancakes, sausage and bacon.

Huang was among them, starting the day with a meeting where he and his table polished off a Lumberjack Slam, Moons Over My Hammy, and a Super Bird sandwich — washed down with plenty of coffee. 

Huang, whose family immigrated to the United States from Taiwan when he was a child, told Valade he had his first hamburger at Dennys and his first milkshake.

“We make the best pancakes here,” Huang said.

“I love how you still say ‘we,’” Valade said.

“Made fresh every day,” Huang added with a grin.

Valade and Huang said Denny’s can be a great launching pad, not just for great ideas, but for great careers.

“Start your first job in the restaurant business,” Huang said. “It teaches you humility, it teaches you hard work, it teaches you hospitality.”

Valade agreed wholeheartedly, who, after talking shop with Huang, checked in with diners like Alfred, who was tucking into a stack of pancakes amid the morning rush.

For people across Silicon Valley, it’s the place to be. “I come here every day,” the retired roofer said.

Full contest details for the Denny’s Trillion Dollar Incubator Contest can be found at www.dennys.com/trilliondollarincubator. Contestants can submit their ideas online or at Denny’s restaurant by Nov. 21st at 8:59 am. The winner will be announced early next year.

IMAGE CREDIT: Don Feria/AP Images for Denny’s