Posts in category: nVidia AI

With coral reefs in rapid decline across the globe, researchers from the University of Hawaii at Mānoa have pioneered an AI-based surveying tool that monitors reef health from the sky.

Using deep learning models and high-resolution satellite imagery powered by NVIDIA GPUs, the researchers have developed a new method for spotting and tracking coral reef halos — distinctive rings of barren sand encircling reefs.

The study, recently published in the Remote Sensing of Environment journal, could unlock real-time coral reef monitoring and turn the tide on global conservation.

“Coral reef halos are a potential proxy for ecosystem health,” said Amelia Meier, a postdoctoral fellow at the University of Hawaii and co-author of the study. “Visible from space, these halo patterns give scientists and conservationists a unique opportunity to observe vast and distant areas. With AI, we can regularly assess halo presence and size in near real time to determine ecosystem well-being.”

Sea-ing Clearly: Illuminating Reef Health

Previously attributed solely to fish grazing, reef halos can also indicate a healthy predator-prey ecosystem, according to researchers’ recent discoveries. While some herbivorous fish graze algae or seagrass near the protective reef perimeter, hunters dig around the seafloor for burrowed invertebrates, laying bare the surrounding sand.

These dynamics indicate the area hosts a healthy food buffet for sustaining a diverse population of ocean dwellers. When the halo changes shape, it signals an imbalance in the marine food web and could indicate an unhealthy reef environment.

In Hot Water

While making up less than 1% of the ocean, coral reefs offer habitat, food and nursery grounds for over 1 million aquatic species. There’s also huge commercial value — about $375 billion annually in commercial and subsistence fishing, tourism and coastal storm protection, and providing antiviral compounds for drug discovery research.

However, reef health is threatened by overfishing, nutrient contamination and ocean acidification. Intensifying climate change — along with the resulting thermal stress from a warming ocean — also increases coral bleaching and infectious disease.

Over half of the world’s coral reefs are already lost or badly damaged, and scientists predict that by 2050 all reefs will face threats, with many in critical danger.

Charting New Horizons With AI

Spotting changes in reef halos is key to global conservation efforts. However, tracking these changes is labor- and time-intensive, limiting the number of surveys that researchers can perform every year. Access to reefs in remote locations also poses challenges.

The researchers created an AI tool that identifies and measures reef halos from global satellites, giving conservationists an opportunity to proactively address reef degradation.

Using Planet SkySat images, they developed ‌a dual-model framework employing two types of convolutional neural networks (CNNs). Relying on computer vision methods for image segmentation, they trained a Mask R-CNN model that detects the edges of the reef and halo, pixel by pixel. A U-Net model trained to differentiate between the coral reef and halo then classifies and predicts the areas of both.

The team used TensorFlow, Keras and PyTorch libraries for training and testing thousands of annotations on the coral reef models.

To handle the task’s large compute requirements, the CNNs operate on an NVIDIA RTX A6000 GPU, boosted by a cuDNN-accelerated PyTorch framework. The researchers received the A6000 GPU as participants in the NVIDIA Academic Hardware Grant Program.

The AI tool quickly identifies and measures around 300 halos across 100 square kilometers in about two minutes. The same task takes a human annotator roughly 10 hours. The model also reaches about 90% accuracy depending on location and can navigate various and complicated halo patterns.

“Our study marks the first instance of training AI on reef halo patterns, as opposed to more common AI datasets of images, such as those of cats and dogs,” Meier said. “Processing thousands of images can take a lot of time, but using the NVIDIA GPU sped up the process significantly.”

One challenge is that image resolution can be a limiting factor in the model’s accuracy. Course-scale imagery with low resolutions makes it difficult to spot ‌reef and halo boundaries and creates less accurate predictions.

Shoring Up Environmental Monitoring

“Our long-term goal is to transform our findings into a robust monitoring tool for assessing changes in halo size and to draw correlations to the population dynamics of predators and herbivores in the area,” Meier said.

With this new approach, the researchers are exploring the relationship between species composition, reef health, and halo presence and size. Currently, they’re looking into the association between sharks and halos. If their hypothesized predator-prey-halo interaction proves true, the team anticipates estimating shark abundance from space.

Creating 3D scans of physical products can be time consuming. Businesses often use traditional methods, like photogrammetry-based apps and scanners, but these can take hours or even days. They also don’t always provide the 3D quality and level of detail needed to make models look realistic in all its applications.

Italy-based startup Covision Media is tapping into AI and NVIDIA RTX to enhance 3D scanning processes and 3D-based content creation.

Covision Media develops AI-based 3D scanners that allow customers to create digital twins of any product, including footwear, eyeglasses, sports equipment, toys, tools and household items. The company is a member of NVIDIA Inception, a free program that provides startups with access to the latest resources and technologies.

Using Covision’s technology, customers can quickly create 3D scans and automatically preserve detailed textures, materials, colors, geometry, and more to make images look as realistic as possible.

The technology runs on NVIDIA RTX, which allows users to create high-quality, detailed, photorealistic 3D models. Covision Media is also using neural radiance fields (NeRFs) to increase the quality of 3D models while tackling typical challenges like accurately capturing lighting, reflections and transparent surfaces.

adidas and its partner NUREG, a content creation studio, are among the first to use Covision Media’s 3D scanning technology for automating and scaling e-commerce content production.

Unlocking New Possibilities in 3D With RTX and AI 

Covision’s 3D scanners are connected to several workstations that run on NVIDIA RTX A5000 and RTX A6000 GPUs, both of which provide high ray-tracing performance and powerful AI capabilities.

The ray-tracing performance of the NVIDIA OptiX framework, coupled with the NVIDIA RT Cores, enables Covision to precisely measure the lighting of a scanned object. This is one of the biggest unique factors that allows customers to put their scanned products into any kind of virtual environment. Covision also harnesses NVIDIA’s software infrastructure to develop state-of-the-art AI solutions for its neural texture approach.

“Without NVIDIA RTX GPUs, it would simply not be possible to achieve the level of accuracy and performance that we need,” said Dr. Burkhard Güssefeld, tech lead at Covision Media. “NVIDIA’s hardware and software capabilities are indispensable in pushing the boundaries of our technology.”

Covision’s technology allows 3D models to be fully relightable, meaning users can adjust and manipulate the lighting in the scene. Users can also merge partial scans together to build a 360-degree scan of the product, which can be used in extended reality (XR) environments.

The core technology uses computer vision and machine learning. Covision’s strong expertise in NeRFs has enabled them to integrate it into existing pipelines to overcome traditional challenges like transparencies and reflections. This allows Covision Media to quickly reconstruct 3D shapes and appearances with just a few images.

The company has very high requirements for quality, millimetric precision, material separation and relightability. So the team adapted and expanded the capabilities of NeRF technology using data from elements such as precise light poses, controlled environments and accurate geometric cues.

NeRFs allow the team to create high-quality 3D images from the start of the process. This lets them increase throughput while reducing the amount of post-processing work required.

“Our 3D scanner automatically delivers the highest quality assets at mass production while at the same time helping customers to create value and save costs,” said Franz Tschimben, CEO of Covision Media. “Furthermore, our scanning device will help companies create high-quality 3D assets needed to populate applications and worlds on new spatial computing devices and mixed reality headsets, like Apple’s Vision Pro and Meta’s Quest.”

Covision is looking to integrate additional NVIDIA products and research projects into its solutions, such as Nvdiffrast for high-performance differentiable rendering and Tiny CUDA as a fast neural network framework. The team is also‌ deploying a custom NeRF implementation into its system, which will make use of the APIs provided by NVIDIA’s Instant-NGP.

The Brand With Three Stripes Brings 3D to Life

adidas scans thousands of items a year using Covision’s technology for its online websites and apps, where they’re compatible on both desktop and mobile.

The 3D models have helped enhance adidas’ Virtual Try-On feature, which allows customers to virtually try on shoes before buying them. adidas also uses the 3D models to automatically create 2D virtual product photos and videos, replacing the need for traditional product photography.

According to adidas, Covision’s scanning technology has helped the team take a quantum step forward in quality while maintaining its scaled scanning production. With the highly realistic scans, adidas has experienced time and cost efficiencies by switching from traditional content production, such as photo and film, to computer-generated content production.

To scale production of 3D assets, adidas relies on Covision’s technology and works with an important set of partners. NUREG is an essential partner in creating and preparing the 3D assets to go live on adidas’ platforms. In addition to NUREG’s expertise in logistics, styling and scanning, the studio provides its own software tools, as well as specialties in 2D and 3D production, which enable the 3D workflows to be scalable for thousands of assets every year.

“The unparalleled quality and relightability of 3D scans allows our global team of 3D and photo specialists to leverage the 3D models for all final applications we are creating,” said Tommy Lenssen, head of the adidas team at NUREG. “I am furthermore happy with the success of our post-production platform that allows lean collaboration and quality control.”

And for post-production workflows, Covision and NUREG work with The Kow Company, one of the leading image and video editing companies for businesses all over the world.

Customers can buy Covision Media’s 3D scanners to start production in their own content creation studios, or they can get products scanned through Covision’s partners in Europe or North America.

Learn more about Covision Media and NVIDIA RTX.

Underscoring NVIDIA’s growing relationship with the global technology superpower, Indian Prime Minister Narendra Modi met with NVIDIA founder and CEO Jensen Huang Monday evening.

The meeting at 7 Lok Kalyan Marg — as the Prime Minister’s official residence in New Delhi is known — comes as Modi prepares to host a gathering of leaders from the G20 group of the world’s largest economies, including U.S. President Joe Biden, later this week.

“Had an excellent meeting with Mr. Jensen Huang, the CEO of NVIDIA,” Modi said in a social media post. “We talked at length about the rich potential India offers in the world of AI.”

The event marks the second meeting between Modi and Huang, highlighting NVIDIA’s role in the country’s fast-growing technology industry.

The meeting with Modi comes just a week after India became the first nation to successfully land on the Moon’s south pole, highlighting the expanding technological capabilities of the world’s largest democracy.

Following Huang’s meeting with Modi, Huang met with several dozen researchers from global powerhouses of science and technology, such as the Indian Institute of Science and the various campuses of the Indian Institute of Technology, for an informal dinner.

The attendees represented a dazzling collection of some of the top minds in fields as diverse as large language models, astrophysics, medicine, quantum computing, and natural language processing.

The evening’s discussions ranged across topics from the use of technology to address language barriers, improve agriculture yields, bridge gaps in health care services and transform digital economies — as well as addressing some of the grand scientific challenges of our time.

NVIDIA has deep ties to India.

NVIDIA began operations in India in 2004 in Bangalore, almost two decades ago. India is now home to four engineering development centers in India — in Gurugram, Hyderabad, Pune and Bengaluru  — and there are now more than 3,800 NVIDIANs in India.

In addition, there are more than 320,000 India-based developers in NVIDIA’s developer program. NVIDIA’s CUDA parallel programming platform is downloaded roughly 40,000 times a month in India, and NVIDIA estimates there are 60,000 experienced CUDA developers in India.

That growth comes as India’s government continues to expand the nation’s information technology infrastructure.

For example, a compute grid is expected to link 20 cities across the country soon, helping researchers and scientists collaborate and share data and computing resources more efficiently.

That effort, in turn, promises to help support India’s ambitious development goals in the years to come.

Modi has set a target of 2030 for India to become the world’s third-largest economy. It’s currently the fifth largest.

And Modi has set a target of 2047, the hundredth anniversary of India’s independence, for the South Asian nation to join the ranks of developed economies.

Entrepreneurs are cultivating generative AI from the west coast of Africa to the eastern edge of the Arabian Desert.

Gen AI is the latest of the big plans Kofi Genfi and Nii Osae have been hatching since they met 15 years ago in high school in Accra, Ghana’s capital that sits on the Gulf of Guinea.

“We watched this latest wave of AI coming for the last few years,” said Osae, a software engineer who discovered his passion for machine learning in college.

So, late last year, they expanded Mazzuma — their mobile-payments startup that’s already processed more than $150 million in transactions — to include MazzumaGPT.

The large language model (LLM) trained on two popular blockchain languages so it can help developers quickly draft smart contracts, a Web3 market that International Data Corp. projects could hit $19 billion next year.

Thousands of Hits

In its first month, 400 developers from 70 countries used the LLM that sports 175 billion parameters, a rough measure of a model’s size and strength.

It’s the latest success for the pair that in 2018 made Forbes’ list of 30 top entrepreneurs in Africa under 30.

“Given the high growth and large demographics, there are big opportunities in this region,” said Genfi, who started his first company, an Apple device reseller, when he was 19.

Osae nurtures that potential as founder and chair of the 100+ member AI Association of Ghana. “I think we’re on a trajectory to leapfrog progress elsewhere,” he said.

LLMs Speak Arabic

About two years ago and 6,000 miles to the northeast, another pair of entrepreneurs launched a generative AI business in the Persian Gulf emirate of Dubai, home of the Burj Khalifa, the world’s tallest building.

Yakov Livshits already had about a dozen active startups when AI researcher Eli Braginskiy, a friend with family ties, came to him with the idea for MetaDialog. The startup built the first LLM to support both Arabic and English, a 7-billion-parameter model trained on one of the world’s largest Arabic/English datasets.

“We call it Baby, because we’re proud of it, and we’re building a larger, 40-billion parameter model now,” said Braginskiy.

“Our Baby LLM is currently integrated in one of the biggest governments in the region, and we’re talking with three other governments interested in using it, too,” said Livshits.

With more than 3 million people in just 13 square miles, Dubai is a vibrant hub for the region.

“The way governments in the Middle East think about AI and advanced tech in general is very bold — they want to move fast, so we’re training custom models in different languages and will present them at the GITEX conference” said Livshits, who lived in Russia, Israel and the U.S. before moving to Dubai.

In February, Saudi Arabia alone announced a $2.4 billion startup fund to help diversify the nation’s economy.

Corporations Want Custom LLMs

In Abu Dhabi, just a hundred miles down the coast, Hussein Al-Natsheh leads a team of engineers and data scientists at Beyond Limits training and fine tuning LLMs. One is already drafting documents for a large energy company and verifying they comply with its standards.

Beyond Limits also works on models for energy companies, utilities and other customers that will index and search corporate documents, draft marketing materials and more.

“Companies need their own LLMs trained on their own data which is confidential, so we have machines reading their data, not us,” said Al-Natsheh, a native of Amman, Jordan, who, prior to joining Beyond Limits, worked on Salma, one of the first Arabic speech assistants.

Drilling for Data

Now that data is the new oil, Beyond Limits is developing toolkits to extract it from unstructured files — corporate emails, PowerPoint and other sources — so it can help companies train custom LLMs approaching 70 billion parameters in size.

The toolkits can help address the lack of data samples from the many Arabic dialects. Indeed, a report from the UAE government on 100 top gen AI uses called for more work on Arabic, a language spoken by nearly half a billion people.

The good news is governments and large companies like G42, a regional cloud service company, are pouring resources into the problem. For example, Beyond Limits was able to create its regional headquarters in Dubai thanks to its last funding round, much of which came from G42.

A Big Boost from Inception

All three companies are members of NVIDIA Inception, a free program that helps startups working on cutting-edge technologies like generative AI.

As part of Inception, Beyond Limits had access to libraries in NVIDIA NeMo, a framework for building massive gen AI models, and which cut training time in one case from five days to one.

“NVIDIA software makes our work much easier, and our clients trust NVIDIA technology,” said Al-Natsheh.

As part of Inception, Mazzuma got access to cloud GPU services to accelerate its experiments and introductions to potential investors.

“That really gave us a boost, and there’s a lot of assurance that comes from working with the best people and tools,” said Genfi.

Treating Partners Well

For its part, MetaDialog trained its Baby LLM on 440 NVIDIA A100 Tensor Core GPUs using a service operated by MosaicML, an Inception member recently acquired by Databricks.

“I’ve built many startups, and no company treats its partners as well as NVIDIA,” said Livshits.

At top: From left to right, Nii Osae, Hussein Al-Natsheh, Eli Braginskiy, Yakov Livshits and Kofi Genfi.

Academics Mory Gharib and Alireza Ramezani in 2020 were spitballing a transforming robot that is now getting a shot at work that’s literally out of this world: NASA Mars Rover missions.

Caltech has unveiled its multi-talented robot that can fly, drive, walk and do eight permutations of motions through a combination of its skills. They call it the Multi-Modal Mobility Morphobot, or M4, which is enabled by the NVIDIA Jetson platform for edge AI and robotics.

“It grew in the number of functions that we wanted to do,” said Gharib, a professor of aeronautics and bioinspired engineering at Caltech. “When we proposed it to our design team, at first they all said, ‘no.’”

Caltech funded its initial research, and NASA and its Jet Propulsion Lab (JPL) funded its next phase and brought in Ramezani, an assistant professor of electrical and computer engineering at Northeastern University, as a faculty researcher at JPL last summer to develop it further.

Its M42 version is now under development at NASA as a Mars Rover candidate and has interest from the U.S. Department of Transportation, Gharib said.

“At NASA, we’re being tested right now for transforming while landing,” he said.

And since recently releasing a paper on it in Nature Communications, Gharib says he’s been inundated with proposals.

“We’re kind of dizzy about how it suddenly got so much attention,” he said. “Different organizations want to do different things and are coming to approach us.”

Firefighting, Search and Rescue Operations 

The Caltech team behind the paper — Gharib and Ramezani, as well as Eric Sihite, a postdoctoral scholar research associate in aerospace at Caltech; Arash Kalantari, from JPL; and Reza Nemovi, a design engineer at CAST — said the M4 is designed for diverse mission requirements in search and rescue, among other areas.

For example, when it’s not feasible to roll or walk into areas — like fire zones —  it can fly and do reconnaissance to assess situations using its cameras and sensors.

According to Gharib, multiple fire departments in the Los Angeles area have contacted Gharib with interest in the M4.

“For first responders, this is huge because you need to land in a safe area and then drive into the situation,” he said.

Versatile Drone Deliveries to Get the Job Done

Caltech’s team also aims to solve complications with drone deliveries using the M4. Drone deliveries are the “low hanging fruit,” for this robot, said Gharib.

Traditional drones for deliveries are problematic because nobody wants drones landing near their home or business for safety reasons, he said. The M4 can land somewhere isolated from people and then drive to finish deliveries, making it a safer option, he added.

The M4 can also fly into areas where truck deliveries might have a difficult time getting into or can’t offer delivery service at all.

“There are a lot of places where truck deliveries can’t go,” he said.

Right now, the M4 is capable of traveling as fast as 40 mph, and its battery can last up to 30 minutes on a charge. But the team is working to design larger drones with longer flight times, bigger payloads and increased travel distances.

The sky’s the limit.

Learn about NVIDIA Jetson Nano.

Just like that, summer falls into September, and some of the most anticipated games of the year, like the Cyberpunk 2077: Phantom Liberty expansion, PAYDAY 3 and Party Animals, are dropping into the GeForce NOW library at launch this month.

They’re part of 24 new games hitting the cloud gaming service in September. And the next Game Pass title to join the cloud at launch is Sea of Stars, part of 13 new games this week.

Keep an eye on GFN Thursday to see the next Microsoft titles joining the cloud this month, including Quake II, Gears Tactics and Halo Infinite. 

Plus, NVIDIA has worked with Google to give Chromebook owners a new offer that includes three free months of a GeForce NOW Priority membership. GeForce NOW cloud gaming ‌goes perfectly together with Chromebooks, which provide up to 1,600p resolution and 120Hz+ displays.

Party Hard in the Cloud

Make painfully great memories with friends in Party Animals, a hilarious, physics-based party brawler from Recreate Games and Source Technology. Fight friends as adorable puppies, mischievous kittens, magical unicorns or other fuzzy creatures or terrorize them as fearsome sharks and ferocious dinosaurs to be the last one standing.

Battle it out by picking up an assortment of weapons to get an edge over others or punch, toss, jump, kick and headbutt others in the brawl. Bring the action across multiple game modes — each requires a different strategy to win.

Get fierce for party game night, whether playing with friends locally on the couch or across devices online. Party Animals joins the cloud at launch on Thursday, Sept. 21.

Work Hard, Play Hard

One of the best ways to stream games from GeForce NOW is with the new Cloud Gaming Chromebooks, which feature screens that display beautiful scenes at up to 1,600p and 120Hz+.

Chromebook gamers can jump right into 100+ free-to-play titles and over 1,600 hit games, like Baldur’s Gate 3, Remnant II, supported games from the Xbox PC Game Pass library and more. GeForce NOW Priority members can also explore the worlds of Cyberpunk 2077, Control and other titles with RTX ON, and Ultimate members can level up and access new NVIDIA technologies like DLSS 3.5 in upcoming games like Alan Wake 2 and Portal with RTX. Compete online with ultra-low latency and other features perfect for playing.

Starting today, Google and NVIDIA are offering all Chromebook owners three free months of a GeForce NOW Priority membership to get gamers started. And those interested in leveling up to an Ultimate membership, the highest-performing tier, are already able to get three free months of a GeForce NOW Ultimate membership with the purchase of a Cloud Gaming Chromebook. Find more details on how to redeem the offer in Google’s Keyword blog or on the Chromebooks Perks page.

New Games as Far as the Eye Can Sea

New games come with each GFN Thursday, and this week’s batch includes Sea of Stars from Sabotage Studio. A retro-inspired role-playing game drawing from classics like Chrono Trigger, it features a vibrant world, a dynamic combat system and a story of cosmic proportions. Play as two Children of the Solstice, who combine the powers of the sun and moon to perform Eclipse Magic, the only force capable of fending off the monstrous creations of an evil alchemist known as the Fleshmancer. Sea of Stars is now available for members to stream from the cloud via Game Pass or Steam.

Check out the list of 13 new games joining this week:

• Sea of Stars (New release on Xbox and Steam, Aug. 28)
• Untamed Tactics (New release on Steam, Aug. 28)
• Trine 5: A Clockwork Conspiracy (New release on Steam, Aug. 31)
• Deep Rock Galactic (Xbox)
• HITMAN – World of Assassination (Xbox)
• King’s Bounty: The Legend (Epic Games Store)
• Little Big Workshop (Epic Games Store)
• NARAKA: BLADEPOINT  (Xbox)
• Portal: Prelude with RTX (Steam)
• Railway Empire 2 (Epic Games Store)
• Shadowrun Returns (Xbox)
• Snake Pass (Epic Games Store)
• STORY OF SEASONS: Friends of Mineral Town (Epic Games Store)

And here’s a peek at what September will look like:

• Chants of Sennaar (New release on Steam, Sept. 5)
• SYNCED (New release on Steam, Sept. 7)
• Deceit 2 (New release on Steam, Sept. 14)
• The Crew Motorfest (New release on Ubisoft, Sept. 14)
• Ad Infinitum (New release on Steam, Sept. 14)
• Party Animals (New release on Steam, Sept. 20)
• Warhaven (New release on Steam, Sept. 20)
• PAYDAY 3 (New release on Xbox, Steam and Epic Games Store, Sept. 21)
• Cyberpunk 2077: Phantom Liberty (New release on Steam, Epic Games Store and GOG, Sept. 25)
• Paleo Pines (New release on Steam, Sept. 26)
• Infinity Strash: DRAGON QUEST The Adventure of Dai (New release on Steam, Sept. 28)
• Wildmender (New release on Steam, Sept. 28)
• Broforce (Steam)
• Death in the Water 2 (Steam)
• Deceive Inc. (Steam)
• Devil May Cry 5 (Steam)
• Don Duality (Steam)
• Dust Fleet (Steam)
• Kingdoms Reborn (Steam)
• Mega City Police (Steam)
• Necesse (Steam)
• Saints Row (Steam)
• Shadow Gambit: The Cursed Crew (Epic Games Store)
• SPRAWL (Steam)
• War for the Overworld (Steam)

This week’s Game On giveaway with SteelSeries includes Dying Light 2 and three-day Ultimate membership codes. It’s the last week of the giveaway, so check out the SteelSeries page for details on how to enter.

Amazing August

On top of the 32 games announced in August, an additional 36 joined the cloud last month across multiple stores:

• Orwell: Keeping an Eye on You (Free game on Epic Games Store, Aug. 10)
• Age of Empires: Definitive Edition (Xbox)
• Age of Empires III: Definitive Edition (Xbox)
• Age of Empires IV (Xbox)
• Age of Wonders 4 (Epic Games Store)
• Aliens: Dark Descent (Epic Games Store)
• Amnesia: The Bunker (Epic Games Store)
• Crusader Kings III (Xbox)
• Darkest Dungeon II (Epic Games Store)
• Dead Cells (Xbox)
• Deathloop (Xbox)
• DOOM 2016 (Steam)
• DOOM Eternal (Steam)
• F1 Manager 2023 (Epic Games Store)
• Gears 5 (Xbox)
• The Great War: Western Front (Epic Games Store)
• Grounded (Xbox)
• Kovaak’s FPS Trainer (Steam)
• Mount & Blade II: Bannerlord (Xbox)
• No Man’s Sky (Xbox)
• The Outlast Trials (Epic Games Store)
• Pentiment (Xbox)
• Project Highrise (Epic Games Store)
• Quake (Xbox, Steam and Epic Games Store)
• Shadowrun: Dragonfall – Director’s Cut (Xbox)
• Stellaris (Xbox)
• Symphony of War: The Nephilim Saga (Epic Games Store)
• System Shock (Epic Games Store)
• The Texas Chain Saw Massacre (Xbox)
• Trackmania (Steam)
• Ultimate KovaaK’s Challenge
• Valheim (Xbox)
• Warhammer 40,000: Darktide (Xbox)
• Wolfenstein II: The New Colossus (Xbox, Steam)
• Wolfenstein: The New Order (Steam and Epic Games Store)
• Wolfenstein: Youngblood (Xbox, Steam)

Before starting the weekend, we’ve got a question for you. Let us know the answer on Twitter or in the comments below.

Best animal in a video game. Go.

Bonus points for pictures…

— NVIDIA GeForce NOW (@NVIDIAGFN) August 30, 2023

Each year, nearly 32 million people travel through the Bengaluru Airport, or BLR, one of the busiest airports in the world’s most populous nation.

To provide such multitudes with a safer, quicker experience, the airport in the city formerly known as Bangalore is tapping vision AI technologies powered by Industry.AI.

A member of the NVIDIA Metropolis vision AI partner ecosystem, Industry.AI has deployed its vision AI platform across BLR’s newest terminal, T2, known as the Garden Terminal for its green spaces, indoor gardens and waterfalls. It’s one of the first deployments of intelligent video analytics at scale in an Indian airport.

Industry.AI increases the safety and efficiency of the terminal’s operations by using vision AI and object detection to track abandoned baggage, flag long passenger queues and alert security teams of potential issues, among other use cases.

By identifying congestion points and anticipating delays with vision AI, staff can proactively redirect passengers to less crowded areas or provide signals to open additional checkpoints, reducing wait times and enhancing passenger experiences.

“Deploying vision AI at this scale is a first for us,” said George Fanthome, chief information officer at BLR’s parent company. “By adopting such advanced deep learning technologies, we strive to be one of the best airports in the world and provide our customers the best experience.”

Smarter, Safer Airport Operations

The Industry.AI platform connects more than 500 live camera feeds across the BLR terminal to vision AI technologies that can accomplish nearly a dozen tasks in real time.

For one, the platform can detect when luggage or a purse is left unattended.

It also helps to manage passenger queues at terminal entries, check-in counters, security check lanes and other areas. Airport staff can be trained to proactively perform tasks based on historical data of passenger movement collected by the AI platform.

“Our platform speeds up passenger flow during peak hours of operation by alerting airport staff about longer-than-optimal lines,” said Tejpreet Chopra, CEO of Industry.AI. “This is done through a dashboard with a real-time visual and sensor feed that allows the airport staff to respond to the situation in the shortest possible time.”

Unauthorized people and vehicles in the airport can also be tracked and alerted to the platform’s users in real time for enhanced security. In addition, Industry.AI detects speed violations made by vehicles outside the terminal, helping to manage safe transportation around the travel hub.

Industry.AI uses the NVIDIA TAO Toolkit and A100 Tensor Core GPUs to train its AI models. For AI inference, the company taps NVIDIA Triton Inference Server and A30 Tensor Core GPUs.

And with the NVIDIA DeepStream software development kit for AI-powered video analytics, along with technical expertise from NVIDIA — a benefit of being a member of the NVIDIA Inception program for cutting-edge startups — Industry.AI built and deployed the BLR solution in just three months.

“NVIDIA Metropolis enabled us to develop our vision AI applications more cost-effectively and bring them to market faster,” Chopra said.

Looking forward, Industry.AI plans to deploy NVIDIA-powered accelerated computing and vision AI technologies across BLR’s other terminals and at additional airports, too.

“BLR’s focus on adopting advanced AI technologies sets a new benchmark for passenger experience at airports,” Chopra said.

Learn more about the NVIDIA Metropolis platform and how it’s used to build smarter, safer airports.

In the global entertainment landscape, TV show and film production stretches far beyond Hollywood or Bollywood — it’s a worldwide phenomenon.

However, while streaming platforms have broadened the reach of content, dubbing and translation technology still has plenty of room for growth.

Deepdub acts as a digital bridge, providing access to content by using generative AI to break down language and cultural barriers.

On the latest episode of NVIDIA’s AI Podcast, host Noah Kravitz spoke with the Israel-based startup’s co-founder and CEO, Ofir Krakowski. Deepdub uses AI-driven dubbing to help entertainment companies boost efficiency and cut costs while increasing accessibility.

The company is a member of NVIDIA Inception, a free program that offers startups go-to-market support, expertise and technological assistance.

Traditional dubbing is slow, costly and often missing the mark, Krakowski says. Current technology struggles with the subtleties of language, leaving jokes, idioms or jargon lost in translation.

Deepdub offers a web-based platform that enables people to interact with sophisticated AI models to handle each part of the translation and dubbing process efficiently. It translates the text, generates a voice and mixes it into the original music and audio effects.

But as Krakowksi points out, even the best AI models make mistakes, so the platform involves a human touchpoint to verify translations and ensure that generated voices sound natural and capture the right emotion.

Deepdub is also working on matching lip movements to dubbed voices.

Ultimately, Krakowski hopes to free the world from the restrictions placed by language barriers.

“I believe that the technology will enable people to enjoy the content that is created around the world,” he said. “It will globalize storytelling and knowledge, which are currently bound by language barriers.”

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Dramatic gains in hardware performance have spawned generative AI, and a rich pipeline of ideas for future speedups that will drive machine learning to new heights, Bill Dally, NVIDIA’s chief scientist and senior vice president of research, said today in a keynote.

Dally described a basket of techniques in the works — some already showing impressive results — in a talk at Hot Chips, an annual event for processor and systems architects.

“The progress in AI has been enormous, it’s been enabled by hardware and it’s still gated by deep learning hardware,” said Dally, one of the world’s foremost computer scientists and former chair of Stanford University’s computer science department.

He showed, for example, how ChatGPT, the large language model (LLM) used by millions, could suggest an outline for his talk. Such capabilities owe their prescience in large part to gains from GPUs in AI inference performance over the last decade, he said.

Research Delivers 100 TOPS/Watt

Researchers are readying the next wave of advances. Dally described a test chip that demonstrated nearly 100 tera operations per watt on an LLM.

The experiment showed an energy-efficient way to further accelerate the transformer models used in generative AI. It applied four-bit arithmetic, one of several simplified numeric approaches that promise future gains.

Looking further out, Dally discussed ways to speed calculations and save energy using logarithmic math, an approach NVIDIA detailed in a 2021 patent.

Tailoring Hardware for AI

He explored a half dozen other techniques for tailoring hardware to specific AI tasks, often by defining new data types or operations.

Dally described ways to simplify neural networks, pruning synapses and neurons in an approach called structural sparsity, first adopted in NVIDIA A100 Tensor Core GPUs.

“We’re not done with sparsity,” he said. “We need to do something with activations and can have greater sparsity in weights as well.”

Researchers need to design hardware and software in tandem, making careful decisions on where to spend precious energy, he said. Memory and communications circuits, for instance, need to minimize data movements.

“It’s a fun time to be a computer engineer because we’re enabling this huge revolution in AI, and we haven’t even fully realized yet how big a revolution it will be,” Dally said.

More Flexible Networks

In a separate talk, Kevin Deierling, NVIDIA’s vice president of networking, described the unique flexibility of NVIDIA BlueField DPUs and NVIDIA Spectrum networking switches for allocating resources based on changing network traffic or user rules.

The chips’ ability to dynamically shift hardware acceleration pipelines in seconds enables load balancing with maximum throughput and gives core networks a new level of adaptability. That’s especially useful for defending against cybersecurity threats.

“Today with generative AI workloads and cybersecurity, everything is dynamic, things are changing constantly,” Deierling said. “So we’re moving to runtime programmability and resources we can change on the fly,”

In addition, NVIDIA and Rice University researchers are developing ways users can take advantage of the runtime flexibility using the popular P4 programming language.

Grace Leads Server CPUs

A talk by Arm on its Neoverse V2 cores included an update on the performance of the NVIDIA Grace CPU Superchip, the first processor implementing them.

Tests show that, at the same power, Grace systems deliver up to 2x more throughput than current x86 servers across a variety of CPU workloads. In addition, Arm’s SystemReady Program certifies that Grace systems will run existing Arm operating systems, containers and applications with no modification.

Grace uses an ultra-fast fabric to connect 72 Arm Neoverse V2 cores in a single die, then a version of NVLink connects two of those dies in a package, delivering 900 GB/s of bandwidth. It’s the first data center CPU to use server-class LPDDR5X memory, delivering 50% more memory bandwidth at similar cost but one-eighth the power of typical server memory.

Hot Chips kicked off Aug. 27 with a full day of tutorials, including talks from NVIDIA experts on AI inference and protocols for chip-to-chip interconnects, and runs through today.

As generative AI and large language models (LLMs) continue to drive innovations, compute requirements for training and inference have grown at an astonishing pace.

To meet that need, Google Cloud today announced the general availability of its new A3 instances, powered by NVIDIA H100 Tensor Core GPUs. These GPUs bring unprecedented performance to all kinds of AI applications with their Transformer Engine — purpose-built to accelerate LLMs.

Availability of the A3 instances comes on the heels of NVIDIA being named Google Cloud’s Generative AI Partner of the Year — an award that recognizes the companies’ deep and ongoing collaboration to accelerate generative AI on Google Cloud.

The joint effort takes multiple forms, from infrastructure design to extensive software enablement, to make it easier to build and deploy AI applications on the Google Cloud platform.

At the Google Cloud Next conference, NVIDIA founder and CEO Jensen Huang joined Google Cloud CEO Thomas Kurian for the event keynote to celebrate the general availability of NVIDIA H100 GPU-powered A3 instances and speak about how Google is using NVIDIA H100 and A100 GPUs for internal research and inference in its DeepMind and other divisions.

During the discussion, Huang pointed to the deeper levels of collaboration that enabled NVIDIA GPU acceleration for the PaxML framework for creating massive LLMs. This Jax-based machine learning framework is purpose-built to train large-scale models, allowing advanced and fully configurable experimentation and parallelization.

PaxML has been used by Google to build internal models, including DeepMind as well as research projects, and will use NVIDIA GPUs. The companies also announced that PaxML is available immediately on the NVIDIA NGC container registry.

Generative AI Startups Abound

Today, there are over a thousand generative AI startups building next-generation applications, many using NVIDIA technology on Google Cloud. Some notable ones include Writer and Runway.

Writer uses transformer-based LLMs to enable marketing teams to quickly create copy for web pages, blogs, ads and more. To do this, the company harnesses NVIDIA NeMo, an application framework from  NVIDIA AI Enterprise that helps companies curate their training datasets, build and customize LLMs, and run them in production at scale.

Using NeMo optimizations, Writer developers have gone from working with models with hundreds of millions of parameters to 40-billion parameter models. The startup’s customer list includes household names like Deloitte, L’Oreal, Intuit, Uber and many other Fortune 500 companies.

Runway uses AI to generate videos in any style. The AI model imitates specific styles prompted by given images or through a text prompt. Users can also use the model to create new video content using existing footage. This flexibility enables filmmakers and content creators to explore and design videos in a whole new way.

Google Cloud was the first CSP to bring the NVIDIA L4 GPU to the cloud. In addition, the companies have collaborated to enable Google’s Dataproc service to leverage the RAPIDS Accelerator for Apache Spark to provide significant performance boosts for ETL, available today with Dataproc on the Google Compute Engine and soon for Serverless Dataproc.

The companies have also made NVIDIA AI Enterprise available on Google Cloud Marketplace and integrated NVIDIA acceleration software into the Vertex AI development environment.

Find more details about NVIDIA GPU instances on Google Cloud and how NVIDIA is powering generative AI, and see how organizations are running their mission-critical enterprise applications with NVIDIA NeMo on the GPU-accelerated Google Cloud.

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