Posts in category: nVidia AI

Creative workflows are riddled with hurry up and wait.

GeForce RTX 30 Series GPUs, powered by our second-generation RTX architecture, aim to reduce the wait, giving creators more time to focus on what matters: creating amazing content.

These new graphics cards deliver faster ray tracing and the next generation of AI-powered tools, turning the tedious tasks in creative workflows into things of the past.

With up to 24GB of new, blazing-fast GDDR6X memory, they’re capable of powering the most demanding multi-app workflows, 8K HDR video editing and working with extra-large 3D models.

Plus, two new apps, available to all NVIDIA RTX users, are joining NVIDIA Studio. NVIDIA Broadcast turns any room into a home broadcast studio with AI-enhanced video and voice comms. NVIDIA Omniverse Machinima enables creators to tell amazing stories with video game assets, animated by AI.

Ray Tracing at the Speed of Light

The next generation of dedicated ray tracing cores and improved CUDA performance on GeForce RTX 30 Series GPUs speeds up 3D rendering times by up to 2x across top renderers.

The RT Cores also feature new hardware acceleration for ray-traced motion blur rendering, a common but computationally intensive technique. It’s used to enhance 3D visuals with cinematic flair. But to date, it requires using either an inaccurate motion vector-based post-process, or an accurate but time-consuming rendering step. Now with RTX 30 Series and RT Core accelerated apps like Blender Cycles, creators can enjoy up to 5x faster motion blur rendering than prior generation RTX.

Next-Gen AI Means Less Wait and More Create

GeForce RTX 30 Series GPUs are enabling the next wave of AI-powered creative features, reducing or even eliminating repetitive creative tasks such as image denoising, reframing and retiming of video, and creation of textures and materials.

Along with the release of our next-generation RTX GPUs, NVIDIA is bringing DLSS — real-time super resolution that uses the power of AI to boost frame rates — to creative apps. D5 Render and SheenCity Mars are the first design apps to add DLSS support, enabling crisp, real-time exploration of designs.

Hardware That Zooms

Increasingly, complex digital content creation requires hardware that can run multiple apps concurrently. This requires a large frame buffer on the GPU. Without sufficient memory, systems start to chug, wasting precious time as they swap geometry and textures in and out of each app.

The new GeForce RTX 3090 GPU houses a massive 24GB of video memory. This lets animators and 3D artists work with the largest 3D models. Video editors can tackle the toughest 8K scenes. And creators of all types can stay hyper-productive in multi-app workflows.

The new GPUs also use PCIe 4.0, doubling the connection speed between the GPU and the rest of the PC. This improves performance when working with ultra-high-resolution and HDR video.

GeForce RTX 30 Series graphics cards are also the first discrete GPUs with decode support for the AV1 codec, enabling playback of high-resolution video streams up to 8K HDR using significantly less bandwidth.

AI-Accelerated Studio Apps

Two new Studio apps are making their way into creatives’ arsenals this fall. Best of all, they’re free for NVIDIA RTX users.

NVIDIA Broadcast upgrades any room into an AI-powered home broadcast studio. It transforms standard webcams and microphones into smart devices, offering audio noise removal, virtual background effects and webcam auto framing compatible with most popular live streaming, video conferencing and voice chat applications.

NVIDIA Omniverse Machinima enables creators to tell amazing stories with video game assets, animated by NVIDIA AI technologies. Through NVIDIA Omniverse, creators can import assets from supported games or most third-party asset libraries, then automatically animate characters using an AI-based pose estimator and footage from their webcam. Characters’ faces can come to life with only a voice recording using NVIDIA’s new Audio2Face technology.

NVIDIA is also updating in September GeForce Experience, our companion app for GeForce GPUs, to support desktop and application capture for up to 8K and HDR, enabling creators to record video at incredibly high resolution and dynamic range.

These apps, like most of the world’s top creative apps, are supported by NVIDIA Studio Drivers, which provide optimal levels of performance and reliability.

GeForce RTX 30 Series: Get Creating Soon

GeForce RTX 30 Series graphics cards are available starting September 17.

While you wait for the next generation of creative performance, perfect your creative skillset by visiting the NVIDIA Studio YouTube channel to watch tutorials and tips and tricks from industry-leading artists.

A decade ago, GPUs were judged on whether they could power through Crysis. How quaint.

The latest NVIDIA Ampere GPU architecture, unleashed in May to power the world’s supercomputers and hyperscale data centers, has come to gaming.

And with NVIDIA CEO Jensen Huang Tuesday unveiling the new GeForce RTX 30 Series GPUs, it’s delivering NVIDIA’s “greatest generational leap in company history.”

The GeForce RTX 30 Series, NVIDIA’s second-generation RTX GPUs, deliver up to 2x the performance and 1.9x the power efficiency over previous-generation GPUs.

“If the last 20 years was amazing, the next 20 will seem like nothing short of science fiction,” Huang said, speaking from the kitchen of his Silicon Valley home. Today’s NVIDIA Ampere launch is “a giant step into the future,” he added.

In addition to the trio of new GPUs — the flagship GeForce RTX 3080, the GeForce RTX 3070 and the “ferocious” GeForce RTX 3090 — Huang introduced a slate of new tools for GeForce gamers.

They include NVIDIA Reflex — which makes competitive gamers quicker, NVIDIA Omniverse Machinima — for those using real-time computer graphics engines to create movies, and NVIDIA Broadcast — which harnesses AI to build virtual broadcast studios for streamers.

Up Close and Personal

A pair of demos tell the tale. In May, we released a demo called Marbles — featuring the world’s first fully path-traced photorealistic real-time graphics.

Chock-full of reflections, textures and light sources, the demo is basically a movie that’s rendered in real time as a marble rolls through an elaborate workshop rich with different materials and textures. It’s a stunningly realistic environment.

In May, Huang showed Marbles running on our top-end Turing architecture-based Quadro RTX 8000 graphics card at 25 frames per second at 720p resolution. An enhanced version of the demo, Marbles at Night, running on NVIDIA Ampere, runs at 30 fps at 1440p.

More telling is a demo that can’t be shown remotely — gameplay running at 60 fps on an 8K LG OLED TV — because video-streaming services don’t support that level of quality.

The GeForce RTX 3090 is the world’s first GPU able to play blockbuster games at 60 fps in 8K resolution, which is 4x the pixels of 4K and 16x the pixels of 1080p.

We showed it to a group of veteran streamers in person to get their reactions as they played through some of latest games.

“You can see wear and tear on the treads,” one said, tilting his head to the side and eyeing the screen in amazement.

“This feels like a Disneyland experience,” another added.

Gamers Battle COVID-19

Huang started his news-packed talk by thanking the more than one million gamers who pooled their GPUs through Folding@Home to fight the COVID-19 coronavirus.

The result was 2.8 exaflops of computing power, 5x the processing power of the world’s largest supercomputer, Huang said, capturing the moment the virus infects a human cell.

“Thank you all for joining this historic fight,” Huang said.

RTX a “Home Run”

For 40 years, since NVIDIA researcher Turner Whitted published his groundbreaking paper on ray tracing, computer science researchers have chased the dream of creating super-realistic virtual worlds with real-time ray tracing, Huang said.

NVIDIA focused intense effort over the past 10 years to realize real-time ray tracing on a large scale. At the SIGGRAPH graphics conference two years ago, NVIDIA unveiled the first NVIDIA RTX GPU.

Based on NVIDIA’s Turing architecture, it combined programmable shaders, RT Cores to accelerate ray-triangle and ray-bounding-box intersections, and the Tensor Core AI processing pipeline.

“Now, two years later, it is clear we have reinvented computer graphics,” Huang said, citing support from all major 3D APIs, tools and game engines, noting that hundreds of RTX-enabled games are now in development. “RTX is a home run,” he said.

Just ask your kids, if you can tear them away from their favorite games for a moment.

Fortnite, from Epic Games, is the latest global sensation to turn on NVIDIA RTX real-time ray-tracing technology, Huang announced.

Now Minecraft and Fortnite, two of the most popular games in the world, have RTX On.

No kid will miss the significance of these announcements.

A Giant Leap in Performance 

The NVIDIA Ampere architecture, the second generation of RTX GPUs, “is a giant leap in performance,” Huang said.

fBuilt on a custom 8N manufacturing process, the flagship GeForce RTX 3080 has 28 billion transistors. It connects to Micron’s new GDDR6X memory — the fastest graphics memory ever made.

“The days of just relying on transistor performance scaling is over,” Huang said.

GeForce RTX 3080: The New Flagship

Starting at $699, the RTX 3080 is the perfect mix of fast performance and cutting-edge capabilities, leading Huang to declare it NVIDIA’s “new flagship GPU.”

Designed for 4K gaming, the RTX 3080 features high-speed GDDR6X memory running at 19Gbps, resulting in performance that outpaces the RTX 2080 Ti by a wide margin.

It’s up to 2X faster than the original RTX 2080. It consistently delivers more than 60 fps at 4K resolution — with RTX ON.

GeForce RTX 3070: The Sweet Spot

Making more power available to more people is the RTX 3070, starting at $499.

And it’s faster than the $1,200 GeForce RTX 2080 Ti — at less than half the price.

The RTX 3070 hits the sweet spot of performance for games running with eye candy turned up.

GeForce RTX 3090: A Big, Ferocious GPU

At the apex of the lineup is the RTX 3090. It’s the fastest GPU ever built for gaming and creative types and is designed to power next-generation content at 8K resolution.

“There is clearly a need for a giant GPU that is available all over the world,” Huang said. “So, we made a giant Ampere.”

And the RTX 3090 is a giant of a GPU. Its Herculean 24GB of GDDR6X memory running at 19.5Gbps can tackle the most challenging AI algorithms and feed massive data-hungry workloads for true 8K gaming.

“RTX 3090 is a beast — a big ferocious GPU,” Huang said. “A BFGPU.”

At 4K it’s up to 50 percent faster than the TITAN RTX before it.

It even comes with silencer — a three-slot, dual-axial, flow-through design — up to 10x quieter and keeps the GPU up to 30 degrees C cooler than the TITAN RTX.

“The 3090 is so big that for the very first time, we can play games at 60 frames per second in 8K,” Huang said. “This is insane.”

Faster Reflexes with NVIDIA Reflex

For the 75 percent of GeForce gamers who play esports, Huang announced the release of this month of NVIDIA Reflex with our Game Ready Driver.

In Valorant, a fast-paced action game, for example, Huang showed a scenario where an opponent, traveling at 1,500 pixels per second, is only visible for 180 milliseconds.

But a typical gamer has a reaction time of 150 ms — from photon to action. “You can only hit the opponent if your PC adds less than 30 ms,” Huang explained.

Yet right now, most gamers have latencies greater than 30 ms — many up to 100 ms, Huang noted.

NVIDIA Reflex optimizes the rendering pipeline across CPU and GPU to reduce latency by up to 50 ms, he said.

“Over 100 million GeForce gamers will instantly become more competitive,” Huang said.

Turn Any Room into a Broadcast Studio

For live streamers, Huang announced NVIDIA Broadcast. It transforms standard webcams and microphones into smart devices to turn “any room into a broadcast studio,” Huang said.

It does this with effects like Audio Noise Removal, Virtual Background Effects — whether for graphics or video — and Webcam Auto Framing, giving you a virtual cameraperson.

NVIDIA Broadcast runs AI algorithms trained by deep learning on NVIDIA’s DGX supercomputer — one of the world’s most potent.

“These AI effects are amazing,” Huang said.

NVIDIA Broadcast will be available for download in September and runs on any RTX GPU, Huang said.

Omniverse Machinima

For those now using video games to create movies and shorts — an art form known as Machinima — Huang introduced NVIDIA Omniverse Machinima, based on the Omniverse 3D workflow collaboration platform.

With Omniverse Machinima, creators can use their webcam to drive an AI-based pose-estimator to animate characters. Drive face animation AI with your voice. Add high-fidelity physics like particles and fluids. Make materials physically accurate.

When done with your composition and mixing, you can even render film-quality cinematics with your RTX GPU, Huang said.

The beta will be available in October. Sign up at nvidia.com/machinima.

Nothing Short of Science Fiction

Wrapping up, Huang noted that it’s been 20 years since the NVIDIA GPU introduced programmable shading. “The GPU revolutionized modern computer graphics,” Huang said.

Now the second-generation NVIDIA RTX — fusing programmable shading, ray tracing and AI — gives us photorealistic graphics and the highest frame rates simultaneously, Huang said.

“I can’t wait to go forward 20 years to see what RTX started,” Huang said.

“In this future, GeForce is your holodeck, your lightspeed starship, your time machine,” Huang said. “In this future, we will look back and realize that it started here.”

Expected to read upwards of 200,000 words daily from hundreds, if not thousands, of documents, financial analysts are asked to perform the impossible.

Primer is using AI to apply the equivalent of compression technology to this mountain of data to help make work easier for them as well as analysts across a range of other industries.

The five-year-old company, based in San Francisco, has built a natural language processing and machine learning platform that essentially does all the reading and collating for analysts in a tiny fraction of the time it would normally take them.

Whatever a given analyst might be monitoring, whether it’s a natural disaster, credit default or geo-political event, Primer slashes hours of human research into a few seconds of analysis.

The software combs through massive amounts of content, highlights pertinent information such as quotes and facts, and assembles them into related lists. It distills vast topics into the essentials in seconds.

“We train the models to mimic that human behavior,” said Barry Dauber, vice president of commercial sales at Primer. “It’s really a powerful analyst platform that uses natural language processing and machine learning to surface and summarize information at scale.”

The Power of 1,000 Analysts

Using Primer’s platform running on NVIDIA GPUs is akin to giving an analyst a virtual staff that delivers near-instantaneous results. The software can analyze and report on tens of thousands of documents from financial reports, internal proprietary content, social media, 30,000-40,000 news sources and elsewhere.

“Every time an analyst wants to know something about Syria, we cluster together documents about Syria, in real time,” said Ethan Chan, engineering manager and staff machine learning engineer at Primer. “The goal is to reduce the amount of effort an analyst has to expend to process more information.”

Primer has done just that to the relief of its customers, which includes financial services firms, government agencies and an array of Fortune 500 companies.

As powerful as Primer’s natural language processing algorithms are, up until two years ago they required 20 minutes to deliver results because of the complexity of the document clustering they were asking CPUs to support.

“The clustering was the bottleneck,” said Chan. “Because we have to compare every document with every other document, we’re looking at nearly a trillion flops for a million documents.”

GPUs Slash Analysis Times

Primer’s team added GPUs to the clustering process in 2018 after joining NVIDIA Inception — an accelerator program for AI startups — and quickly slashed those analysis times to mere seconds.

Primer’s GPU work unfolds in the cloud, where it makes equally generous use of AWS, Google Cloud and Microsoft Azure. For prototyping and training of its NLP algorithms such as Named Entity Recognition and Headline Generation (on public, open-source news datasets), Primer uses instances with NVIDIA V100 Tensor Core GPUs.

Model serving and clustering happens on instances with NVIDIA T4 GPUs, which can be dialed up and down based on clustering needs. The company also uses a wrapper called CuPy, which allows for CUDA-powered acceleration of GPUs on Python.

But what Chan believes is Primer’s most innovative use of GPUs is in acceleration of its clustering algorithms.

“Grouping documents together is not something anyone else is doing,” he said, adding that Primer’s success in this area further establishes that “you can use NVIDIA for new use cases and new markets.”

Flexible Delivery Model

With the cloud-based SaaS model, customers can increase or decrease their analysis speed, depending on how much they want to spend on GPUs.

Primer’s offering can also be deployed in a customer’s data center. There, the models can be trained on a customer’s IP and clustering can be performed on premises. This is an important consideration for those working in highly regulated or sensitive markets.

Analysts in finance and national security are currently Primer’s primary users, however, the company could help anyone tasked with combing through mounds of data actually make decisions instead of preparing to make decisions.

Looking directly at the sun isn’t recommended — unless you’re doing it with AI, which is what NASA is working on.

The surface of the sun, which is the layer you can see with the eye, is actually bubbly: intense heat creates a boiling reaction, similar to water at high temperature. So when NASA researchers magnify images of the sun with a telescope, they can see tiny blobs, called granules, moving on the surface.

Studying the movement and flows of the granules helps the researchers better understand what’s happening underneath that outer layer of the sun.

The computations for tracking the motion of granules requires advanced imaging techniques. Using data science and GPU computing with NVIDIA Quadro RTX-powered HP Z8 workstations, NASA researchers have developed deep learning techniques to more easily track the flows on the sun’s surface.

RTX Flares Up Deep Learning Performance

When studying how storms and hurricanes form, meteorologists analyze the flows of winds in Earth’s atmosphere. For this same reason, it’s important to measure the flows of plasma in the sun’s atmosphere to learn more about the short- and long-term evolution of our nearest star.

This helps NASA understand and anticipate events like solar flares, which can affect power grids, communication systems like GPS or radios, or even put space travel at risk because of the intense radiation and charged particles associated with space weather.

“It’s like predicting earthquakes,” said Michael Kirk, research astrophysicist at NASA. “Since we can’t see very well beneath the surface of the sun, we have to take measurements from the flows on the exterior to infer what is happening subsurface.”

Granules are transported by plasma motions — hot ionized gas under the surface. To capture these motions, NASA developed customized algorithms best tailored to their solar observations, with a deep learning neural network that observes the granules using images from the Solar Dynamics Observatory, and then learns how to reconstruct their motions.

“Neural networks can generate estimates of plasma motions at resolutions beyond what traditional flow tracking methods can achieve,” said Benoit Tremblay from the National Solar Observatory. “Flow estimates are no longer limited to the surface — deep learning can look for a relationship between what we see on the surface and the plasma motions at different altitudes in the solar atmosphere.”

“We’re training neural networks using synthetic images of these granules to learn the flow fields, so it helps us understand precursor environments that surround the active magnetic regions that can become the source of solar flares,” said Raphael Attie, solar astronomer at NASA’s Goddard Space Flight Center.

NVIDIA GPUs were essential in training the neural networks because NASA needed to complete several training sessions with data preprocessed in multiple ways to develop robust deep learning models, and CPU power was not enough for these computations.

When using TensorFlow on a 72 CPU-core compute node, it took an hour to complete only one pass with the training data. Even in a CPU-based cloud environment, it would still take weeks to train all the models that the scientists needed for a single project.

With an NVIDIA Quadro RTX 8000 GPU, the researchers can complete one training in about three minutes — a 20x speedup. This allows them to start testing the trained models after a day instead of having to wait weeks.

“This incredible speedup enables us to try out different ways to train the models and make ‘stress tests,’ like preprocessing images at different resolutions or introducing synthetic errors to better emulate imperfections in the telescopes,” said Attie. “That kind of accelerated workflow completely changed the scope of what we can afford to explore, and it allows us to be much more daring and creative.”

With NVIDIA Quadro RTX GPUs, the NASA researchers can accelerate workflows for their solar physics projects, and they have more time to conduct thorough research with simulations to gain deeper understandings of the sun’s dynamics.

Learn more about NVIDIA and HP data science workstations, and listen to the AI Podcast with NASA.

Cells under a microscope, grapes on a vine and species in a forest are just a few of the things that AI can identify using the image annotation platform created by startup V7 Labs.

Whether a user wants AI to detect and label images showing equipment in an operating room or livestock on a farm, the London-based company offers V7 Darwin, an AI-powered web platform with a trained model that already knows what almost any object looks like, according to Alberto Rizzoli, co-founder of V7 Labs.

It’s a boon for small businesses and other users that are new to AI or want to reduce the costs of training deep learning models with custom data. Users can load their data onto the platform, which then segments objects and annotates them. It also allows for training and deploying models.

V7 Darwin is trained on several million images and optimized on NVIDIA GPUs. The startup is also exploring the use of NVIDIA Clara Guardian, which includes NVIDIA DeepStream SDK intelligent video analytics framework on edge AI embedded systems. So far, it’s piloted laboratory perception, quality inspection, and livestock monitoring projects, using the NVIDIA Jetson AGX Xavier and Jetson TX2 modules for the edge deployment of trained models.

V7 Labs is a member of NVIDIA Inception, a program that provides AI startups with go-to-market support, expertise and technology assistance.

Pixel-Perfect Object Classification

“For AI to learn to see something, you need to give it examples,” said Rizzoli. “And to have it accurately identify an object based on an image, you need to make sure the training sample captures 100 percent of the object’s pixels.”

Annotating and labeling an object based on such a level of “pixel-perfect” granular detail takes just two-and-a-half seconds for V7 Darwin — up to 50x faster than a human, depending on the complexity of the image, said Rizzoli.

Saving time and costs around image annotation is especially important in the context of healthcare, he said. Healthcare professionals must look at hundreds of thousands of X-ray or CT scans and annotate abnormalities, Rizzoli said, but this can be automated.

For example, during the COVID-19 pandemic, V7 Labs worked with the U.K.’s National Health Service and Italy’s San Matteo Hospital to develop a model that detects the severity of pneumonia in a chest X-ray and predicts whether a patient will need to enter an intensive care unit.

The company also published an open dataset with over 6,500 X-ray images showing pneumonia, 500 cases of which were caused by COVID-19.

V7 Darwin can be used in a laboratory setting, helping to detect protocol errors and automatically log experiments.

Application Across Industries

Companies in a wide variety of industries beyond healthcare can benefit from V7’s technology.

“Our goal is to capture all of computer vision and make it remarkably easy to use” said Rizzoli. “We believe that if we can identify a cell under a microscope, we can also identify, say, a house from a satellite. And if we can identify a doctor performing an operation or a lab technician performing an experiment, we can also identify a sculptor or a person preparing a cake.”

Global uses of the platform include assessing the damage of natural disasters, observing the growth of human and animal embryos, detecting caries in dental X-rays, creating autonomous machines to evaluate safety protocols in manufacturing, and allowing farming robots to count their harvests.

Stay up to date with the latest healthcare news from NVIDIA, and explore how AI, accelerated computing, and GPU technology contribute to the worldwide battle against the novel coronavirus on our COVID-19 research hub.

With Lime and Bird scooters covering just about every major U.S. city, you’d think all bets were off for walking. Think again.

Piaggio Fast Forward is staking its future on the idea that people will skip e-scooters or ride-hailing once they take a stroll with its gita robot. A Boston-based subsidiary of the iconic Vespa scooter maker, the company says the recent focus on getting fresh air and walking during the COVID-19 pandemic bodes well for its new robotics concept.

The fashionable gita robot — looking like a curvaceous vintage scooter — can carry up to 40 pounds and automatically keeps stride so you don’t have to lug groceries, picnic goodies or other items on walks. Another mark in gita’s favor: you can exercise in the fashion of those in Milan and Paris, walking sidewalks to meals and stores. “Gita” means short trip in Italian.

The robot may turn some heads on the street. That’s because Piaggio Fast Forward parent Piaggio Group, which also makes Moto Guzzi motorcycles, expects sleek, flashy designs under its brand.

The first idea from Piaggio Fast Forward was to automate something like a scooter to autonomously deliver pizzas. “The investors and leadership came from Italy, and we pitched this idea, and they were just horrified,” quipped CEO and founder Greg Lynn.

If the company gets it right, walking could even become fashionable in the U.S. Early adopters have been picking up gita robots since the November debut. The stylish personal gita robot, enabled by the NVIDIA Jetson TX2 supercomputer on a module, comes in signal red, twilight blue or thunder gray.

Gita as Companion

The robot was designed to follow a person. That means the company didn’t have to create a completely autonomous robot that uses simultaneous localization and mapping, or SLAM, to get around fully on its own, said Lynn. And it doesn’t use GPS.

Instead, a gita user taps a button and the robot’s cameras and sensors immediately capture images that pair it with its leader to follow the person.

Using neural networks and the Jetson’s GPU to perform complex image processing tasks, the gita can avoid collisions with people by understanding how people move  in sidewalk traffic, according to the company. “We have a pretty deep library of what we call ‘pedestrian etiquette,’ which we use to make decisions about how we navigate,” said Lynn.

Pose-estimation networks with 3D point cloud processing allow it to see the gestures of people to anticipate movements, for example. The company recorded thousands of hours of walking data to study human behavior and tune gita’s networks. It used simulation training much the way the auto industry does, using virtual environments. Piaggio Fast Forward also created environments in its labs for training with actual gitas.

“So we know that if a person’s shoulders rotate at a certain degree relative to their pelvis, they are going to make a turn,” Lynn said. “We also know how close to get to people and how close to follow.”

‘Impossible’ Without Jetson 

The robot has a stereo depth camera to understand the speed and distance of moving people, and it has three other cameras for seeing pedestrians for help in path planning. The ability to do split-second inference to make sidewalk navigation decisions was important.

“We switched over and started to take advantage of CUDA for all the parallel processing we could do on the Jetson TX2,” said Lynn.

Piaggio Fast Forward used lidar on its early design prototype robots, which were tethered to a bulky desktop computer, in all costing tens of thousands of dollars. It needed to find a compact, energy-efficient and affordable embedded AI processor to sell its robot at a reasonable price.

“We have hundreds of machines out in the world, and nobody is joy-sticking them out of trouble. It would have been impossible to produce a robot for $3,250 if we didn’t rely on the Jetson platform,” he said.

Enterprise Gita Rollouts

Gita robots have been off to a good start in U.S. sales with early technology adopters, according to the company, which declined to disclose unit sales. They have also begun to roll out in enterprise customer pilot tests, said Lynn.   

Cincinnati-Northern Kentucky International Airport is running gita pilots for delivery of merchandise purchased in airports as well as food and beverage orders from mobile devices at the gates.

Piaggio Fast Forward is also working with some retailers who are experimenting with the gita robots for handling curbside deliveries, which have grown in popularity for avoiding the insides of stores.

The company is also in discussions with residential communities exploring usage of gita robots for the replacement of golf carts to encourage walking in new developments.

Piaggio Fast Forward plans to launch several variations in the gita line of robots by next year.

“Rather than do autonomous vehicles to move people around, we started to think about a way to unlock the walkability of people’s neighborhoods and of businesses,” said Lynn.

Piaggio Fast Forward is a member of NVIDIA Inception, a virtual accelerator program that helps startups in AI and data science get to market faster.

With NVIDIA SHIELD TV, there’s always more to love.

Today’s software update — SHIELD Software Experience Upgrade 8.2 — is the 25th for owners of the original SHIELD TV. It’s a remarkable run, spanning more than 5 years since the first SHIELD TVs launched in May 2015.

The latest upgrade brings a host of new features and improvements for daily streamers and media enthusiasts.

Stream On

One of the fan-favorite features for the newest SHIELD TVs is the AI upscaler. It works by training a neural network model on countless images. Deployed on 2019 SHIELD TVs, the AI model can then take low-resolution video and produce incredible sharpness and enhanced details no traditional scaler can recreate. Edges look sharper. Hair looks scruffier. Landscapes pop with striking clarity.

To see the difference between “basic upscaling” and “AI-enhanced upscaling” on SHIELD, click the image below and move the slider left and right.

Today’s upgrade adds more UHD 4K upscaling support from 360p to 1440p content. And on 2019 SHIELD TV Pros, we added support for 60fps content. Now SHIELD can upscale live sports on HD TV and HD video from YouTube to 4K with AI. In the weeks ahead, following an update to the NVIDIA Games app in September, we’ll add 4K 60fps upscaling to GeForce NOW.

The customizable menu button on the new SHIELD remote is another popular addition to the family. It’s getting two more actions to customize.

In addition to an action assigned to a single press, users can now configure a custom action for double press and long press. With over 25 actions available, the SHIELD remote is now the most customizable remote for streamers. This powerful feature works with all SHIELD TVs and the SHIELD TV app, available on the Google Play Store and iOS App Store.

More to Be Enthusiastic About

We take pride in SHIELD being a streaming media player enthusiasts can be, well, enthusiastic about. With our latest software upgrade, we’re improving our IR and CEC volume control support.

These upgrades include support for digital projectors, and allowing functionality when SHIELD isn’t active. It also adds IR volume control when using the SHIELD TV app, and when you’ve paired your Google Home with SHIELD. The 2019 SHIELD remote adds IR control to change the input source on TVs, AVRs and soundbars.

Additionally, earlier SHIELD generations — both 2015 and 2017 models — now have an option to match the frame rate of displayed content.

We’ve added native SMBv3 support as well, providing faster and more secure connections between PC and SHIELD. SMBv3 now works without requiring a PLEX media server.

With SHIELD, there’s always more to love. Download the latest software upgrade today, and check out the release notes for a complete list of all the new features and improvements.

Self-driving cars continue to amaze passengers as a truly transformative technology. However, in the time of COVID-19, a self-cleaning car may be even more appealing.

Robotaxi startup Voyage introduced its third-generation vehicle, the G3, this week. The  autonomous vehicle, a Chrysler Pacifica Hybrid minivan retrofitted with self-driving technology, is the company’s first designed to operate without a driver and is equipped with an ambulance-grade ultraviolet light disinfectant system to keep passengers healthy.

The new vehicles use the NVIDIA DRIVE AGX Pegasus compute platform to enable the startup’s self-driving AI for robust perception and planning. The automotive-grade platform delivers safety to the core of Voyage’s autonomous fleet.

Given the enclosed space and the proximity of the driver and passengers, ride-hailing currently poses a major risk in a COVID-19 world. By implementing a disinfecting system alongside driverless technology, Voyage is ensuring self-driving cars will continue to develop as a safer, more efficient alternative to everyday mobility.

The G3 vehicle uses an ultraviolet-C system from automotive supplier GHSP to destroy pathogens in the vehicle between rides. UV-C works by inactivating a pathogen’s DNA, blocking its reproductive cycle. It’s been proven to be up to 99.9 percent effective and is commonly used to sterilize ambulances and hospital rooms.

The G3 is production-ready and currently testing on public roads in San Jose, Calif., with production vehicles planned to come out next year.

G3 Compute Horsepower Takes Off with DRIVE AGX Pegasus

Voyage has been using the NVIDIA DRIVE AGX platform in its previous-generation vehicles to power its Shield automatic emergency braking system.

With the G3, the startup is unleashing the 320 TOPS of performance from NVIDIA DRIVE AGX Pegasus to process sensor data and run diverse and redundant deep neural networks simultaneously for driverless operation. Voyage’s onboard computers are automotive grade and safety certified, built to handle the harsh vehicle environment for safe daily operation.

DRIVE AGX Pegasus is built on two NVIDIA Xavier systems-on-a-chip. Xavier is the first SoC built for autonomous machines and was recently determined by global safety agency TÜV SÜD to meet all applicable requirements of ISO 26262. This stringent assessment means it meets the strictest standard for functional safety.

Xavier’s safety architecture combined with the AI compute horsepower of the DRIVE AGX Pegasus platform delivers the robustness and performance necessary for the G3’s fully autonomous capabilities.

Moving Forward as the World Shelters in Place

As the COVID-19 pandemic continues to limit the way people live and work, transportation must adapt to keep the world moving.

In addition to the UV-C lights, Voyage has also equipped the car with HEPA-certified air filters to ensure safe airflow inside the car. The startup uses its own employees to manage and operate the fleet, enacting strict contact tracing and temperature checks to help minimize virus spread.

While these measures are in place to specifically protect against the COVID-19 virus, they demonstrate the importance of an autonomous vehicle as a place where passengers can feel safe. No matter the condition of the world, autonomous transportation translates to a worry-free voyage, every time.

Only a dream just a few years ago, real-time ray tracing has become the new reality in graphics because of NVIDIA RTX — and it’s just getting started.

The world’s top gaming franchises, the most popular gaming engines and scores of creative applications across industries are all onboard for real-time ray tracing.

Leading studios, design firms and industry luminaries are using real-time ray tracing to advance content creation and drive new possibilities in graphics, including virtual productions for television, interactive virtual reality experiences, and realistic digital humans and animations.

The Future Group and Riot Games used NVIDIA RTX to deliver the world’s first ray-traced broadcast. Rob Legato, the VFX supervisor for Disney’s recent remake of The Lion King, referred to real-time rendering with GPUs serving as the future of creativity. And developers have adopted real-time techniques to create cinematic video game graphics, like ray-traced reflections in Battlefield V, ray-traced shadows in Shadow of the Tomb Raider and path-traced lighting in Minecraft.

These are just a few of many examples.

In early 2018, ILMxLAB, Epic Games and NVIDIA released a cinematic called Star Wars: Reflections. We revealed that the demo was rendered in real time using ray-traced reflections, area light shadows and ambient occlusion — all on a $70,000 NVIDIA DGX workstation packed with four NVIDIA Volta GPUs. This major advancement captured global attention, as real-time ray tracing with this level of fidelity could only be done offline on gigantic server farms.

Fast forward to August 2018, when we announced the GeForce RTX 2080 Ti at Gamescom and showed Reflections running on just one $1,200 GeForce RTX GPU, with the NVIDIA Turing architecture’s RT Cores accelerating ray tracing performance in real time.

Today, over 50 content creation and design applications, including 20 of the leading commercial renderers, have added support for NVIDIA RTX. Real-time ray tracing is more widely available, allowing professionals to have more time for iterating designs and capturing accurate lighting, shadows, reflections, translucence, scattering and ambient occlusion in their images.

RTX Ray Tracing Continues to Change the Game

From product and building designs to visual effects and animation, real-time ray tracing is revolutionizing content creation. RTX allows creative decisions to be made sooner, as designers no longer need to play the waiting game for renders to complete.

What was once considered impossible just two years ago has now become a reality for anyone with an RTX GPU — NVIDIA’s Turing architecture delivers new capabilities that made real-time ray tracing achievable. Its RT Cores accelerate two of the most computationally intensive tasks: bounding volume hierarchy traversal and ray-triangle intersection testing. This allows the streaming multiprocessors, which perform the computations, to improve programmable shading instead of spending thousands of instruction slots for each ray cast.

Turing’s Tensor Cores enable users to leverage and enhance AI denoising for generating clean images quickly. All of these new features combined are what make real-time ray tracing possible. Creative teams can render images faster, complete more iterations and finish projects with cinematic, photorealistic graphics.

“Ray tracing, especially real-time ray tracing, brings the ground truth to an image and allows the viewer to make immediate, sometimes subconscious decisions about the information,” said Jon Peddie, president of Jon Peddie Research. “If it’s entertainment, the viewer is not distracted and taken out of the story by artifacts and nagging suspension of belief. If it’s engineering, the user knows the results are accurate and can move closer and more quickly to a solution.”

Artists can now use a single GPU for real-time ray tracing to create high-quality imagery, and they can harness the power of RTX through numerous ways. Popular game engines Unity and Unreal Engine are leveraging RTX. GPU renderers like V-Ray, Redshift and Octane are adopting OptiX for RTX acceleration. And workstation vendors like BOXX, Dell, HP, Lenovo and Supermicro offer real-time ray tracing-capable systems, allowing users to harness the power of RTX in a single, flexible desktop or mobile workstation.

RTX GPUs also provide the memory required for handling massive datasets, whether it’s complex geometry or large numbers of high-resolution textures. The NVIDIA Quadro RTX 8000 GPU provides a 48GB frame buffer, and with NVLink high-speed interconnect technology doubling that capacity, users can easily manipulate massive, complex scenes without spending time constantly decimating or optimizing their datasets.

“DNEG’s virtual production department has taken on an ever increasing amount of work, particularly over recent months where practical shoots have become more difficult,” said Stephen Willey, head of technology at DNEG. “NVIDIA’s RTX and Quadro Sync solutions, coupled with Epic’s Unreal Engine, have allowed us to create far larger and more realistic real-time scenes and assets. These advances help us offer exciting new possibilities to our clients.”

More recently, NVIDIA introduced techniques to further improve ray tracing and rendering. With Deep Learning Super Sampling, users can enhance real-time rendering through AI-based super resolution. NVIDIA DLSS allows them to render fewer pixels and use AI to construct sharp, higher-resolution images.

At SIGGRAPH this month, one of our research papers dives deep into how to render dynamic direct lighting and shadows from millions of area lights in real time using a new technique called reservoir-based spatiotemporal importance resampling, or ReSTIR.

Real-Time Ray Tracing Opens New Possibilities for Graphics

RTX ray tracing is transforming design across industries today.

In gaming, the quality of RTX ray tracing creates new dynamics and environments in gameplay, allowing players to use reflective surfaces strategically. For virtual reality, RTX ray tracing brings new levels of realism and immersiveness for professionals in healthcare, AEC and automotive design. And in animation, ray tracing is changing the pipeline completely, enabling artists to easily manage and manipulate light geometry in real time.

Real-time ray tracing is also paving the way for virtual productions and believable digital humans in film, television and immersive experiences like VR and AR.

And with NVIDIA Omniverse — the first real-time ray tracer that can scale to any number of GPUs — creatives can simplify collaborative studio workflows with their favorite applications like Unreal Engine, Autodesk Maya and 3ds Max, Substance Painter by Adobe, Unity, SideFX Houdini, and many others. Omniverse is pushing ray tracing forward, enabling users to create visual effects, architectural visualizations and manufacturing designs with dynamic lighting and physically based materials.

Explore the Latest in Ray Tracing and Graphics

Join us at the SIGGRAPH virtual conference to learn more about the latest advances in graphics, and get an exclusive look at some of our most exciting work.

Be part of the NVIDIA community and show us what you can create by participating in our real-time ray tracing contest. The selected winner will receive the latest Quadro RTX graphics card and a free pass to discover what’s new in graphics at NVIDIA GTC, October 5-9.

The future of graphics is here, and AI is leading the way.

At the SIGGRAPH 2020 virtual conference, NVIDIA is showcasing advanced AI technologies that allow artists to elevate storytelling and create stunning, photorealistic environments like never before.

NVIDIA tools and software are behind the many AI-enhanced features being added to creative tools and applications, powering denoising capabilities, accelerating 8K editing workflows, enhancing material creation and more.

Get an exclusive look at some of our most exciting work, including the new NanoVDB library that boosts workflows for visual effects. And check out our groundbreaking research,  AI-powered demos, and speaking sessions to explore the newest possibilities in real-time ray tracing and AI.

NVIDIA Extends OpenVDB with New NanoVDB

OpenVDB is the industry-standard library used by VFX studios for simulating water, fire, smoke, clouds and other effects. As part of its collaborative effort to advance open source software in the motion picture and media industries, the Academy Software Foundation (ASWF) recently announced GPU-acceleration in OpenVDB with the new NanoVDB for faster performance and easier development.

OpenVDB provides a hierarchical data structure and related functions to help with calculating volumetric effects in graphic applications. NanoVDB adds GPU support for the native VDB data structure, which is the foundation for OpenVDB.

With NanoVBD, users can leverage GPUs to accelerate workflows such as ray tracing, filtering and collision detection while maintaining compatibility with OpenVDB. NanoVDB is a bridge between an existing OpenVDB workflow and GPU-accelerated rendering or simulation involving static sparse volumes.

Hear what some partners have been saying about NanoVDB.

“With NanoVDB being added to the upcoming Houdini 18.5 release, we’ve moved the static collisions of our Vellum Solver and the sourcing of our Pyro Solver over to the GPU, giving artists the performance and more fluid experience they crave,” said Jeff Lait, senior mathematician at SideFX.

“ILM has been an early adopter of GPU technology in simulating and rendering dense volumes,” said Dan Bailey, senior software engineer at ILM. “We are excited that the ASWF is going to be the custodian of NanoVDB and now that it offers an efficient sparse volume implementation on the GPU. We can’t wait to try this out in production.”

“After spending just a few days integrating NanoVDB into an unoptimized ray marching prototype of our next generation renderer, it still delivered an order of magnitude improvement on the GPU versus our current CPU-based RenderMan/RIS OpenVDB reference,” said Julian Fong, principal software engineer at Pixar. “We anticipate that NanoVDB will be part of the GPU-acceleration pipeline in our next generation multi-device renderer, RenderMan XPU.”

Learn more about NanoVDB.

Research Takes the Spotlight

During the SIGGRAPH conference, NVIDIA Research and collaborators will share advanced techniques in real-time ray tracing, along with other breakthroughs in graphics and design.

Learn about a new algorithm that allows artists to efficiently render direct lighting from millions of dynamic light sources. Explore a new world of color through nonlinear color triads, which are an extension of gradients that enable artists to enhance image editing and compression.

And hear from leading experts across the industry as they share insights about the future of design:

• Omniverse: Get the latest updates on NVIDIA Omniverse, a computer graphics and simulation platform that lets artists work seamlessly in real time across popular content-creation applications.
• RTX-accelerated ray tracing with OptiX 7: Learn about the general concepts behind OptiX and how to fully optimize your application to get the most out of hardware ray-tracing cores of modern GPUs.
• Making Machine Learning Work: From Ideas to Production Tools: Experts from NVIDIA, Weta Digital, Ubisoft and more will discuss how machine learning is enhancing the production of computer graphics.
• Join a virtual round table with AWS or visit our virtual booth with Microsoft to learn more about Quadro virtual workstations and customer cases.

Check out all the groundbreaking research and presentations from NVIDIA.

Eye-Catching Demos You Can’t Miss

This year at SIGGRAPH, NVIDIA demos will showcase how AI-enhanced tools and GPU-powered simulations are leading a new era of content creation:

• Synthesized high-resolution images with StyleGAN2: Developed by NVIDIA Research, StyleGAN uses transfer learning to produce portraits in a variety of painting styles.
• Mars lander simulation: A high-resolution simulation of retropropulsion is used by NASA scientists to plan how to control the speed and orientation of vehicles under different landing conditions.
• AI denoising on Blender: RTX AI features like OptiX Denoiser enhances rendering to deliver an interactive ray-tracing experience.
• 8K video editing on RTX Studio laptops: GPU acceleration for advanced video editing and visual effects, including AI-based features in DaVinci Resolve, helping editors produce high-quality video and iterate faster.

Check out all the NVIDIA demos and sessions at SIGGRAPH.

More Exciting Graphics News to Come at GTC

The breakthroughs and innovation doesn’t stop here. Register now to explore more of the latest NVIDIA tools and technologies at GTC, October 5-9.