This GFN Thursday brings in hordes of fun — and a whole lot of orcs. Orcs Must Die! 3, the newest title from the action-packed, orc-slaying series from Robot Entertainment, is joining the GeForce NOW library when it releases tomorrow, Friday, July 23. In addition, 10 more games are coming to the service this Read article >
This GFN Thursday brings in hordes of fun — and a whole lot of orcs. Orcs Must Die! 3, the newest title from the action-packed, orc-slaying series from Robot Entertainment, is joining the GeForce NOW library when it releases tomorrow, Friday, July 23.
In addition, 10 more games are coming to the service this week.
Play Your Games, Your Way
Gaming on GeForce NOW means having instant access to over 1,000 PC games streaming from the cloud. Whether it’s a low-powered PC, Macs, Chromebooks, SHIELD TVs or Android and iOS mobile devices, GeForce NOW supported devices play real PC games with GeForce levels of performance.
And you don’t just get to play real PC versions of games optimized on GeForce NOW compatible devices. The games you play are the ones you own, streaming from popular stores like Steam, Epic Games Store, Ubisoft Connect and GOG.COM. With GeForce NOW, you never have to rebuy a different version of that game to play it on multiple compatible devices.
Members can play awesome PC games, like Orcs Must Die! 3 in high-powered detail and battle across all of their GeForce NOW compatible devices.
Bring the Mayhem
Orcs Must Die! 3 (Steam) challenges players to slice, burn, toss, zap, grind and give it all they’ve got to keep massive hordes of orcs at bay across the battlefield in an effort to secure the castle walls and victory. Battle with a buddy or slay your enemies solo against enormous orc armies with weapons and traps of your choice.
Players can experience all-new war scenarios that pit players against overwhelming legions of orcs. But don’t worry, players have an arsenal of magic, weapons and new War Machines: traps on an oversized scale that range from mega flip traps that launch orcs ragdolling off the castle walls to mega boom barrel launchers that unleash pyrotechnic glory.
Enjoy a new and exciting story set 20 years after the previous game with fresh characters. Play for glory in weekly challenges to see how long you can survive in Endless Mode to put your name on the leaderboard. Then, survive Scramble Mode and face off against evolving orcs with sinister surprises. Finally, take things a step further in the Drastic Steps campaign as the mayhem takes to the skies against flying orcs.
With Orcs Must Die! 3 releasing on Steam and joining the GeForce NOW library, more gamers than ever before can experience the thrill of stomping orcish hordes — regardless of their low-powered rigs.
“We love that our players can experience all of the action and all of the orcs on any GeForce NOW compatible device,” said Patrick Hudson, CEO at developer Robot Entertainment. “It’s great that players who may not have powerful devices can still play the real PC version of our game at orc-slaying power.”
Members can get ready to slay and play Orcs Must Die! 3 on GeForce NOW when it releases tomorrow, July 23.
Orcs Must Die! 3 isn’t the only new game this GFN Thursday. Members can look out for these sweet titles ready to stream this week:
Now enabled by default on OpenBSD -current is dhcpleased(8), a dynamic host configuration protocol daemon written by florian@ (Florian Obser), who spoke with us about his work:
I suppose this is either the KAME project's fault, or if we don't want to go that far back, Theo's fault. At g2k16 he floated the idea of a network configuration daemon. It would collect "proposals" for IP addresses, default routes and
DNS configuration from various sources (DHCP,
IPv6 router advertisements, umb(4), etc.),
make some policy decisions, configure the network, and set resolv.conf(5)
Walk into a store. Grab your stuff. And walk right out again, without stopping to check out. In just the past three months, California-based AiFi has helped Choice Market increase sales at one of its Denver stores by 20 percent among customers who opted to skip the checkout line. It allowed Żappka, a Polish convenience Read article >
Walk into a store. Grab your stuff. And walk right out again, without stopping to check out.
In just the past three months, California-based AiFi has helped Choice Market increase sales at one of its Denver stores by 20 percent among customers who opted to skip the checkout line.
It allowed Żappka, a Polish convenience store chain, to provide faster checkout for morning train commuters.
It helped pro-racing team Penske and Verizon run a dinky 200-square-foot store at the Indy500, so race fans could quickly get back to the action.
And on Wednesday AiFi announced an expanded partnership with Loop Neighborhood to introduce its computer vision, camera-only platform into stores in California, starting with two Bay Area locations.
AiFi, a member of the NVIDIA Inception accelerator for AI and deep learning startups, has moved out of the proof-of-concept stage and into stores across the world.
Its technology makes shopping more convenient and helps retailers better understand their customers.
“Retailers can now get as much information about physical shopping habits as online stores are getting from ecommerce,” said AiFi CEO and co-founder Steve Gu, a veteran of Apple and Google.
AiFi’s ability to analyze shopper habits is even more impressive because its stores don’t need to buy costly sensors and RFID tags.
Instead, the company uses real-time image recognition and edge AI powered by NVIDIA GPUs to recognize the items shoppers select and charge them, usually through an app linked to the customer’s credit card.
It’s not an easy task in busy stores stocked with many hundreds of items, but the five-year-old company’s technology now achieves an accuracy rate of 99 percent.
To date, more than 15 stores worldwide are putting the company’s technology to work. Those stores are already serving satisfied customers who return again and again.
At Choice Market, 60 percent of shoppers who tried the checkout-free option used it again within a month. Twenty percent came back three times.
The computer-vision-powered system works smoothly alongside the store’s traditional checkout system, and is integrated with the Choice Now app, where customers can shop checkout-free, and place online orders and arrange pickups.
AiFi is revolutionizing retail operations with AI. At the Indy500 auto race earlier this year, Penske Entertainment’s nano-store allowed fans to buy snacks, beverages and merchandise with an app. No need to stop and swipe a credit card.
This speed translates well to any kind of store where people need to slip in and out in a hurry. Żappka partnered with AiFi to open its first public autonomous store in Poznan, Poland, quickly drawing huge amounts of foot traffic from commuters going to and from a nearby train station.
With AiFi integrated with the Żappka App, which has over 5 million users, harried commuters could hustle out the door with a newspaper and a morning coffee.
More stores equipped with AiFi’s technology are coming. In France, the company is working with Carrefour on what the retailer calls its “Flash LabStore,” a frictionless store at its headquarters in Massy.
And in the UK, Britain’s fourth-largest supermarket, Morrisons, is working with AiFi to test out a store with no checkout.
These stores represent a growing number of collaborations with major retailers that see AiFi’s combination of AI and computer vision as the key to a brick and mortar retail renaissance that will ultimately put more goods in front of more customers, in more places.
The final push for the hat trick came down to the wire. Five minutes before the deadline, the team submitted work in its third and hardest data science competition of the year in recommendation systems. Called RecSys, it’s a relatively new branch of computer science that’s spawned one of the most widely used applications in Read article >
The final push for the hat trick came down to the wire.
Five minutes before the deadline, the team submitted work in its third and hardest data science competition of the year in recommendation systems. Called RecSys, it’s a relatively new branch of computer science that’s spawned one of the most widely used applications in machine learning, one that helps millions find what they want to watch, buy and play.
The team’s combination of six AI models packed into the contest’s limit of 20 gigabytes all of the smarts it culled from studying 750 million data points. An unusual rule in the competition said the models had to run in less than 24 hours on a single core in a cloud CPU.
They hit the submission button and waited.
Twenty-three hours and 40 minutes later an email arrived: They hit No. 1 on the leaderboard.
“The email came in right under the buzzer — 20 minutes later and we would have timed out,” said Chris Deotte, one of several team members who’s also a grandmaster in Kaggle competitions, the online Olympics of data science.
“We were really on the edge,” said Benedikt Schifferer, a teammate who helps design NVIDIA Merlin, a framework to help users quickly build their own recommendation systems.
GPUs could have busted through the inference job in a fraction of the time. Adapting the work to one CPU core “was like going back to the distant past,” said Gilberto “Giba” Titericz, a Brazil-based Kaggle grandmaster on the team.
In fact, once the competition was over, the team demonstrated the inference job that took nearly 24 hours on a CPU core could run on a single NVIDIA A100 Tensor Core GPU in just five and a half minutes.
Sorting 40M Items a Day
For that competition, Twitter gave participants millions of data points a day for 28 days and asked them to predict which tweets users would like or retweet. It was an industrial-strength challenge from the leading technical conference on RecSys, an event that draws a who’s who of top engineers from Facebook, Google, Spotify and other players.
The discipline is as hard as it is helpful. Recommendation systems fuel our digital economy, serving up suggestions faster and smarter than a traditional search.
Industry challenges help advance the field for everyone, whether they’re seeking the perfect gift for a spouse or trying to find an old friend online.
Three Wins in Five Months
Earlier this year, the full NVIDIA team led a field of 40 in the Booking.com Challenge. They used millions of anonymized data points to correctly predict the final city a vacationer in Europe would choose to visit.
The annual meeting of the Special Interest Group on Information Retrieval, SIGIR, draws experts from companies that span Alibaba to Walmart Labs. Its 2021 challenge provided 37 million data points from online shopping sessions and asked participants to predict which products users would buy.
Overlap with the ACM contest forced the NVIDIA team to split into two groups that coordinated their efforts between the contests. Ratcheting up the pressure, some team members were heads down writing a paper for the ACM RecSys conference.
The Art of the Fast Break
Two factors propelled a five-person NVIDIA team with members spread across Brazil, Canada, France and the U.S. to the best overall performance, taking first or second place in every leaderboard. They made a big bet on Transformer models developed for natural-language processing and increasingly adopted for recsys, and they understood the art of the handoff.
“As one member is going to bed another picks up the work in a different time zone,” said Even Oldridge, who leads the Merlin group.
“When it all clicks, it’s very effective, and I’m amazed at what we’ve accomplished in the last year building our internal knowledge and our standing in the recsys community to the point where we could win three major competitions in five months,” he said.
Respecting User Privacy
The contest required models to make predictions with no background on users beyond their current browsing session.
“That’s an important task because sometimes users want to browse anonymously, and some privacy laws limit access to historical information,” said Gabriel Moreira, a senior Merlin researcher in São Paulo who led NVIDIA’s SIGIR team.
The competition marked the first time the team used only Transformer models in their solution to a challenge. Moreira’s team aims to make the massive neural networks more easily available to every Merlin customer.
From a Hat Trick to a Haul
On June 30, we notched a fourth consecutive win in RecSys, what hockey players call a haul. MLPerf, an industry benchmarking group, announced that NVIDIA and its partners set records in all its latest training benchmarks, including one in recommendation systems.
The competitions fuel ideas for new techniques that find their way into recsys frameworks like Merlin and related tools, papers and online classes held by the NVIDIA Deep Learning Institute. The ultimate goal: Help everyone succeed.
In interviews NVIDIA’s recsys experts freely shared their know-how — part art, part science.
A Pro Tip on RecSys
One best practice is using a diversity of models that work together as an ensemble.
In the ACM RecSys Challenge, the team used both tree and neural-network models. The outputs from one stage became inputs for the next in a process called stacking.
“A single model can make a mistake due to a data error or convergence issue, but if you take an ensemble of several models, it’s very powerful,” said Bo Liu, the newest member of NVIDIA’s Kaggle grandmaster team.
Meet RecSys Experts Online
On July 29, you can meet RecSys experts from Facebook, NVIDIA and TensorFlow to learn more about how to create great recommender systems.
NVIDIA today launched TensorRT™ 8, the eighth generation of the company’s AI software, which slashes inference time in half for language queries -- enabling developers to build the world’s best-performing search engines, ad recommendations and chatbots and offer them from the cloud to the edge.
Top game artists, producers, developers and designers are coming together this week for the annual Game Developers Conference. As they exchange ideas, educate and inspire each other, the NVIDIA Studio ecosystem of RTX-accelerated apps, hardware and drivers is helping advance their craft. GDC 2021 marks a major leap in game development with NVIDIA RTX technology Read article >
Top game artists, producers, developers and designers are coming together this week for the annual Game Developers Conference. As they exchange ideas, educate and inspire each other, the NVIDIA Studio ecosystem of RTX-accelerated apps, hardware and drivers is helping advance their craft.
GDC 2021 marks a major leap in game development with NVIDIA RTX technology integrated in the latest releases of Unity, Unreal Engine 4, Toolbag and more. They’re supported by the July NVIDIA Studio Driver, available today, providing peak performance and reliability.
Developers can create better looking games, in less time, without worrying about their systems crashing, with NVIDIA Studio.
Game Development Runs Faster with NVIDIA Studio
The two most popular PC game engines, Unity and Unreal Engine, recently received additional RTX benefits.
The new 2021.2 beta release of Unity delivered native support for NVIDIA DLSS, allowing game developers to easily incorporate advanced AI rendering into their games. DLSS produces image quality that’s comparable to native resolution — and sometimes even better — while only conventionally rendering a fraction of the pixels, boosting real-time performance for more engaging experiences and saving artists valuable exporting time.
DLSS SDK 2.2.1, the latest offered by NVIDIA and built into Unity 2021.2, brings a new blueprint function to enable the optimal image quality for a particular resolution, called “Auto” mode. There’s also an optional sharpening slider so developers can further tune their visuals.
Unreal Engine 4.27, currently in preview, included an experimental feature called Eye-Tracked Foveated Rendering. The technique renders a single image at varying resolutions, sharpening the point of focus, while blurring other parts, to mimic human eyesight.
It’s perfect for extended reality with improved performance on NVIDIA RTX GPUs, using NVIDIA Variable Rate Shading, and no discernable loss of picture quality. In addition, GPU Lightmass baking built on RTX ray tracing introduced parameters to better control lighting and levels of detail in production assets.
Marmoset Toolbag 4.03 sports a new ray-tracing engine, optimized to run on all modern GPUs. Even faster ray-traced results are achieved with native hardware support of NVIDIA RTX devices.
The most recent update added RTX-accelerated AI denoising, allowing game artists to quickly visualize materials with photorealistic lighting and shadows.
RTX-accelerated ray racing with improved shading, global illumination and reflections raise the visual quality bar, while RTX-accelerated baking speeds up asset creation.
NVIDIA Omniverse is a platform for 3D content creation and collaboration. It was built from the ground up to be easily extensible and customizable with a modular development framework. The platform includes ready-made Omniverse Apps like Machinima and Audio2Face, plus a collection of over 200 Omniverse Kit Extensions, small pieces of code purpose-built to achieve a specific task.
Game developers can use the prebuilt apps or extensions, or easily build their own tools on Omniverse Kit, a robust system allowing coders with basic programming knowledge to build extensions, apps and microservices to assist in content creation pipelines.
Developers can learn more about Omniverse in the GDC session Collaborative Game Development with NVIDIA Omniverse, taking place from 8:30-9:30 a.m. PT on July 22. The session will feature tips on collaborative workflows between leading industry applications such as Unreal Engine 4, 3ds Max, and Maya, plus an introduction on how to build on Omniverse Kit. Interested developers can register here.
The Studio Advantage, Built for the Bold
NVIDIA Studio ushered in a new era of creative performance with laptops and desktops purpose-built to power the world’s most innovative minds. Packed with industry-leading RTX GPUs, these machines deliver unprecedented levels of computing power.
Future game developers and content creators can unleash their creativity and build magnificent worlds with the latest RTX 30-Series GPU-powered NVIDIA Studio laptops.
Perfect for students heading back to school, Studio laptops accelerate more than just the latest game engines, they power dozens of applications in STEM — including engineering, computer science, data science and economics applications — plus the apps creators rely on. The latest selection of Studio laptops can be found in the Studio Shop.
Together with game engine and creative app developers, teams of testers and engineers are continually optimizing the way NVIDIA hardware works with top software — enhancing features, reducing the repetitive and speeding up workflows. Studio Drivers undergo extensive testing to deliver the performance and reliability developers need, helping them create the blockbuster games at the speed of imagination.
Further Boost Creativity With the July Studio Driver
The July NVIDIA Studio Driver available today features support for updates to Unity, Unreal Engine, Toolbag, Omniverse and more.
Enscape 3.1, dropping July 21, adds a new NVIDIA real-time denoiser and support for NVIDIA DLSS, designed for real-time engines utilizing NVIDIA RTX GPUs.
This enables smoother viewport visibility, as well as the ability to render at lower resolutions, enabling higher framerates, using AI super resolution to upscale the image to equal if not higher visual fidelity.
Pixar Animation Studios RenderMan 24 added RenderMan XPU, a look-development focused GPU-accelerated ray tracer.
Together with AI denoising in the viewport, RenderMan XPU enables artists to interactively create their art and view an image that is predictive of the final frame render.
Click here to download the Maya teapot asset used in performance testing.
Topaz Video Enhance AI now offers Slow Motion, a new RTX GPU Tensor Core powered AI feature that generates a high-quality, smooth, slow-motion capture with minimal artifacts.
Crucially, eliminating the need for an expensive high-frame-rate camera.
Finally, gamers and content creators who use Discord to collaborate and share content with friends can use the new NVDEC integration, exclusive to NVIDIA GPUs, for accelerated video decoding. This lets them share screens and stream over Discord with reduced resources for video and results in better gaming performance.