Posts in category: nVidia AI

A Swedish physician who helped pioneer chemistry 200 years ago just got another opportunity to innovate.

A supercomputer officially christened in honor of Jöns Jacob Berzelius aims to establish AI as a core technology of the next century.

Berzelius (pronounced behr-zeh-LEE-us) invented chemistry’s shorthand (think H₂0) and discovered a handful of elements including silicon. A 300-petaflops system now stands on the Linköping University (LiU) campus, less than 70 kilometers from his birthplace in south-central Sweden, like a living silicon tribute to innovations yet to come.

“Many cities in Sweden have a square or street that bears Berzelius’s name, but the average person probably doesn’t know much about him,” said Niclas Andersson, technical director at the National Supercomputer Centre (NSC) at Linköping University, which is home to the system based on the NVIDIA DGX SuperPOD.

The BerzeLiUs system will be twice as fast as Sweden’s current top computer and would rank among the top 10 percent on the latest list of the world’s TOP500 supercomputers.

An Ambitious AI Agenda

Andersson and others hope many people will feel ripples from the ambitious work planned for the BerzeLiUs supercomputer. For starters, it may initially tackle as many as seven two-year projects that aim to make leaps forward in areas like wireless communications, cybersecurity, large-scale IoT and efficient programming.

In addition, Swedish researchers can use the system to collaborate with their longstanding research colleagues at Singapore’s Nanyang Technical University (NTU) on six new efforts. They include finding new ways to enhance data analytics with visualization, developing more secure AI algorithms and orchestrating multiple AI models to work as one to schedule the NTU’s campus bus network.

It’s all part of Sweden’s largest private research initiative focused on AI innovation. Known simply as WASP, the Wallenberg Artificial Intelligence, Autonomous Systems and Software Program is a 15-year effort that’s already recruited a faculty of more than three dozen international researchers and engaged 40 companies.

Backing Science for a Better World

The effort is spearheaded by the Knut and Alice Wallenberg Foundation, Sweden’s largest private financier of research. It contributed most of the 5.5 billion kronor ($650 million) for WASP. In a separate gift, the foundation donated 300 million kronor ($36 million) last October to Linköping University to build and run the BerzeLiUs supercomputer for WASP and other researchers.

WASP hosted a virtual event in December that attracted speakers from Ericsson, IKEA, Volvo and SEB Group, one of Sweden’s largest banks. At the event, the foundation’s vice chair, Marcus Wallenberg — scion of the country’s best-known family of industrialists — noted the collaboration between academia and industry is vital for research that makes a positive impact on society. In addition, Wallenberg spoke with NVIDIA CEO Jensen Huang at the inauguration of the BerzeLiUs system (see video below).

There’s little doubt that, like early advances in chemistry, AI is becoming part of our daily lives.

“AI will be everywhere, it will get into many places we can’t imagine at this point,” said Andersson, whose 25-year career at NSC has been devoted to work in high performance computing.

The New Formula: HPC+AI

“HPC traditionally is mostly about simulation; and now, with the advent of AI, simulation becomes an input to new kinds of data analytics that will drive computing to much wider use — it’s a big trend shift,” he said.

Specifically, the BerzeLiUs system will help researchers scale their work to handle the larger datasets and models that power discoveries with AI.

“Most people have been working with single machines that are not as powerful as DGX systems, so our most important task in the coming years is to help develop algorithms that can scale; and there are very large problems that can use many GPU nodes,” he said.

Inside the New Machine

The BerzeLiUs system consists of 60 NVIDIA DGX A100 systems, linked on a 200 Gbit/second NVIDIA Mellanox InfiniBand HDR network. The same network links the processors to 1.5 petabytes of flash memory on four storage servers from DataDirect Networks.

The single InfiniBand network ensures data gets into the system fast, and AI is all about data. “Buying more storage might be the first upgrade we will need because 60 DGX A100 systems can suck up a lot of data fast,” Andersson said.

To get started quickly, NSC asked NVIDIA and Atos, who managed the build and integration, to configure the system’s software. The stack will include the Atos Codex AI Suite as well as access to NGC, NVIDIA’s hub for GPU-optimized software for AI and HPC.

In the end, all the bits and bytes come down to people who, like Berzelius, create advances that drive society forward.

“We need many new explorers in the universe of AI because it will infiltrate and transform all disciplines of research,” said Andersson.

As GeForce NOW enters its second year and rapidly approaches 10 million members, we’re setting our sights on fresh milestones and adding new membership offerings.

First up is a new premium offering, Priority membership, which receives the same benefits as Founders members. These include priority access to gaming sessions, extended session lengths and RTX ON for beautifully ray-traced graphics and DLSS in supported games.

Monthly memberships are available at $9.99 a month. A new annual membership option, at $99.99, provides the best value.

GeForce NOW wouldn’t be what it is today without our Founders members. That’s why we’re adding the Founders for Life benefit, which continues the special $4.99 introductory rate as long the account is in good standing. (For more details, click here.)

Whether it’s a short time, a long time or a lifetime, we want our Founders members, who’ve supported GeForce NOW from the start, to stay a part of the family.

The Next Level

We’re grateful for the feedback we receive from all our members. We use it to improve the service and plan for the future. In the last year, that included:

• Supporting day-and-date launches, like Cyberpunk 2077, and top free-to-play games
• Increasing the game library, which now includes more than 800 games
• Opening new data centers, giving us more than 20 around the world
• Expanding capacity in existing data centers, allowing us to grow the service further
• Improving quality of service, with even more optimizations on the way.

As GeForce NOW continues to grow, we’re working to improve streaming quality and ease of use, and to add more games.

With the 2.0.28 update, currently rolling out to members and available to all in about a week, streaming quality takes the next step.

One of the ways we do this is with a unique adaptive Vsync technology. The feature synchronizes frame rates at 60 or 59.94 Hz server-side to match the display client-side, reducing stutter and latency on supported games. A new adaptive de-jitter technology will enable us to increase bit rates for improved quality over choppy networks, too.

We’re also passionate about making GeForce NOW easier to use, including updates that get members into the game even faster. The first phase of these improvements includes account linking for key games on the platform, coming in the next 1-2 months, as well as updates to game preloading that should cut load times by about half.

Additionally, we’re adding capacity in our busiest data centers along with new server locations. Next up is Phoenix, Arizona, with our first Canadian data center, in Montreal, to follow. We expect both to be operational later this year, helping reduce wait times for Priority and Founders members.

We also get tons of questions from our community about bringing GeForce NOW to new regions. We just launched with a new partner in Turkey, with Saudia Arabia and Australia on the horizon.

GeForce NOW Alliance partners operate regional data centers and offer GeForce NOW in local currencies and local language support. That means reduced latency, significantly better ping times and less waiting. Expect additional GeForce NOW Alliance partners expanding into new territories soon.

Speedrunning Your GFN Thursday

Finally, we’re upgrading GFN Thursday, our ongoing commitment to bringing great PC games and service updates to members each week.

In 2020, we onboarded and released an average of 10 games a week. With a new express onboarding pipeline, our goal is to increase that by about half by year-end.

We’ve continued to add support for additional digital game stores. In case you missed it, last week we released GOG.COM versions of four CD PROJEKT RED games, including The Witcher 3: Wild Hunt Game of the Year Edition.

And since it’s Thursday, we can’t leave without giving our members their weekly dose of new games.

In addition to the service updates rolling out with this week’s 2.0.28 release, we’re streaming 7 new games on GeForce NOW. Members can look for:

• Do Not Feed the Monkeys (Steam)
• GoNNER (Steam)
• Loop Hero (Epic Games Store)
• Monopoly Plus (Steam)
• Snooker 19 (Steam)
• System Shock: Enhanced Edition (Steam)
• Wanba Warriors (Steam)

New memberships, improved streaming, more games — GeForce NOW year two is just getting started.

The world of bicycle racing has changed. Aggressive cyclists expect their bikes to meet their every need, no matter how detailed and precise. And meeting these needs requires an entirely new approach.

Predator Cycling engineers and manufactures high-end custom-built carbon fiber bicycles that have garnered praise from championship cyclists around the world. For the past 15 years, the Predator team has designed every aspect of their frames and conducted intensive engineering simulation, rendering and manufacturing processes in-house.

“I had been following Predator for over a decade, and knew there was only one guy, Aram, who could take my raw idea, refine it, and turn it into a finished product worthy of use on track cycling’s biggest stage,” said Olympic cyclist Bobby Lea.

Recently, Predator Cycling worked on its most innovative project to date — the new RF20 frame. With increasing costs of materials and the complexity of production requirements, the RF20 spent extended time in research and development.

To bring the RF20 to market at a competitive price and minimize the build time of each bicycle, Predator Cycling knew it needed to maximize performance and efficiency. The team found the exact solution it needed with the Lenovo ThinkStation P620, powered by the NVIDIA RTX A6000 GPU.

The RTX A6000 enables Predator Cycling to process more complex models, and render and run engineering simulations in real time. With the ThinkStation P620, the team can easily handle real-time computing and multitasking, allowing them to accelerate production workflows.

RTX Hammers to the Front in Every Stage 

Since using the RTX A6000-powered ThinkStation P620, Predator Cycling has streamlined their manufacturing processes significantly. This allowed them to speed up production workflows and bring the RF20 frame out of R&D and get it out on the road. Overall, the company estimates it has shrunk its go-to-market timelines by 12-16 weeks.

“The NVIDIA RTX A6000 GPU and ThinkStation P620 deliver cutting-edge performance and speed to accelerate design processes and production times,” said Aram Goganian, co-founder of Predator Cycling. “We’re able to do complex wind drag simulations, mechanical and structural testing, and topology optimizations with AI in near real time, enabling us to show customers design changes with minimal delay.”

And it’s not just projects like the RF20 frame that have been significantly accelerated — Predator Cycling’s relationships and interactions with customers have also been enhanced. 

Each of Predator Cycling’s bikes is custom-built, so customers need real-life representations to help them select the components and finishes they want. Previously, this meant building physical prototypes that took months to complete.

Now, the powerful RTX A6000 has allowed the Predator team to provide customers with realistic bike renders long before they create physical prototypes. Clients can provide instant feedback on the photorealistic renders, which allows Predator Cycling to skip continuous iteration cycles and go from prototyping to testing fast.

Predator Cycling has also notably improved internal workflows when it comes to running simulations, and they’ve seen performance gains of 2-6x across a number of applications such as Luxion KeyShot, ANSYS Discovery, ANSYS Fluent and Autodesk Fusion 360.

Discover More Breakthroughs at GTC

Learn about more advanced technologies in manufacturing and product design at the GPU Technology Conference, running from April 12-16. Predator Cycling (S31226) will be at GTC to share more details about their 3D print production experience with NVIDIA technologies.

Check out some featured GTC sessions by customers and partners below:

• Rimac Automobili (E31424) will share their experience in accelerating the design of the world’s fastest electric car.
• Polaris (S31512) will discuss locally streaming VR content for automotive design.
• nTopology (S32033) will present a new approach to mechanical engineering with real-time feedback, thanks to GPU acceleration.
• BMW (S31367) will share a simulation-first approach with leveraging robots for inspecting BMW vehicles.
• AWS, Dassault Systèmes, NVIDIA and Renault Group (E31274) will discuss balancing peak rendering needs in the cloud and accurately simulating vehicle designs using a cluster of 4,000 GPUs.

And don’t miss our special keynote address on April 12, when NVIDIA CEO Jensen Huang will share exciting news and announcements.

Register now for free and explore other manufacturing sessions at GTC.

Call it Moneyball for deep learning.

New York Times writer Cade Metz tells the funny, inspiring — and ultimately triumphant — tale of how a dogged group of AI researchers bet their careers on the long-dismissed technology of deep learning.

In his new book, Genius Makers: The Mavericks Who Brought AI to Google, Facebook, and the World, Metz reveals the human personalities behind the rise of AI, with a cast of well-known characters that includes Geoffrey Hinton, Yann Lecun, Yoshua Bengio and more.

The book begins with Metz’s favorite anecdote — how Hinton, a professor at the University of Toronto, and two students, Alex Kruszewski and Ilya Sutskever, moved into Google as large technology companies began to see the merits of AI.

Another fascinating story focuses on UC Berkeley professor Sergey Levine’s work on reinforcement learning at Google. He helped set up the “arm farm” — multiple robotic arms that learn how to successfully pick up items by trying and failing repeatedly.

Levine left the arms to do their work over the weekend, and came back Monday to what looked like a crime scene — one of the arms had failed to pick up lipstick correctly, resulting in what looked like bloodstains all over the room.

For more stories about the minds behind today’s technology, Genius Makers is out now.

Key Points From This Episode:

• Metz’s book captures the nuance and contradictions within the AI community, where experts can have polarizing viewpoints on emerging technology. Metz gives the example of scientists Frank Rosenblatt and Marvin Minsky, who firmly disagreed on what potential neural networks held.
• One recurring theme throughout Genius Makers is that of “old ideas or new” — a mantra at Hinton’s university lab. It represented his belief that, if a scientist believed an idea could work, even if it seemed like a slim chance, they should keep trying until proven wrong. It’s a belief that’s served him well throughout his long career.

Tweetables:

“Part of my mission on earth is to show people that engineers, like my father, are real, interesting, fascinating people.” — Cade Metz [1:37]

“These technologies are continuing to progress at an incredibly fast rate and the questions that they raise have not been solved.” — Cade Metz [31:22]

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Fun fact: Thursday is named for Thor, the hammer-wielding Norse god associated with lightning and thunder. We like to think he’d endorse GFN Thursday as the best day of the week, too.

This is a special Thursday, as we’re happy to share that our cloud-streaming service has added more support for GOG. As part of our continuing open-platform strategy, members who own games from The Witcher series on GOG can now play those versions across their devices. It’s all powered by GeForce NOW’s streaming servers — they’re so powerful that Vikings would have called it magic.

And we’re planning even more events in cooperation with GOG in the future. But first, let’s talk GOG and Geralt.

This Is Your Story

CD PROJEKT RED’s The Witcher series has sold more than 50 million copies, and gamers around the world have joined Geralt on his adventures. Additionally, GOG is a digital distribution platform created with utmost care about customers and we’re big fans of their PC-focused philosophy. They also built GOG GALAXY, an application that combines multiple libraries into one and connects you with friends across all gaming platforms.

We’ve been working with the GOG team to add support for more games ever since the launch of CDPR’s Cyberpunk 2077, the first GOG-enabled game on GFN. With that quest complete, we worked with our partners at GOG on phase two.

That phase begins today. Members who own the following titles on GOG can stream the games across their devices straight from our cloud-gaming servers.

Members can also easily capture their best gameplay moments in The Witcher 3: Wild Hunt – Game of the Year Edition, thanks to GeForce NOW’s sharing tools. Capture your best monster takedowns using our in-game overlay, or apply your signature look using NVIDIA Freestyle. And with Ansel, you can compose the perfect photo of Geralt from any angle of CDPR’s beautiful open world.

More to Play

This week, members can look for the following GeForce NOW library additions, including GOG.com support for games from The Witcher series:

• Thronebreaker: The Witcher Tales (GOG.COM)
• The Witcher Adventure Game (GOG.COM)
• The Witcher 2: Assassins of Kings Enhanced Edition (GOG.COM)
• The Witcher 3: Wild Hunt – Game of the Year Edition (GOG.COM)
• Stronghold: Warlords (new release on Steam)
• Monster Energy Supercross – The Official Videogame 4 (day-and-date release on Steam, March 11)
• Pascal’s Wager: Definitive Edition (day-and-date release on Steam, March 12)
• Uno (Steam)
• Workers & Resources: Soviet Republic (Steam)

With GeForce NOW, there’s always another game to play. We’ll see you next GFN Thursday!

For all the attention devoted to self-driving cars, there’s another, often-overlooked, aspect to transportation efficiency and safety: smarter roads.

Derq, a startup operating out of Detroit and Dubai, has developed an AI system that can be installed on intersections and highways. Its AI edge appliance uses NVIDIA GPUs to process video and other data from cameras and radars to predict crashes before they happen and to warn connected road users. It can also understand roadways better, with applications ranging from accurate traffic counts to predicting spots on roads that are most prone to crashes.

Derq CEO and co-founder Georges Aoude says his fascination with automotive safety systems stretches back to long weekend drives with his family to visit relatives. He’d wonder why these fast-moving hunks of metal didn’t collide more often.

Time revealed to him that vehicles frequently do, sometimes to deadly effect. In fact, 1.35 million people around the globe perish in auto accidents every year, and millions more are seriously injured.

“Many of our team members have been touched by deadly road crashes,” said Aoude, who himself has lost two relatives on the roads. “This only makes us more determined to get our technology out there to make roadways safer for all.”

As a scholar at MIT, Aoude worked on autonomous satellites and then drone safety, before doing his Ph.D. work on autonomous vehicles. During his graduate work, he began to envision smart cities that work in tandem with autonomous vehicles, and the seed for Derq was planted. Along the way, he received a patent for AI systems that can predict dangerous behaviors.

Dissecting an Intersection

For its initial use case, Derq zeroed in on intersection and pedestrian safety. It chose to test its technology at a busy downtown street crossing considered one of Detroit’s most dangerous. The intersection had no cameras or radars, so Derq procured those and began its monitoring work.

For the past three years, it’s been capturing and training footage of tens of thousands of vehicles and road users a day, 24/7, at that intersection. In addition to predicted red-light violations and dangerous pedestrian movements, the company has been using that data to refine its AI models. As it monitors more intersections and roadways, Derq is constantly expanding its models. All data is anonymized, and no personal information from road users is ever collected or stored.

Those models can determine which actions have the potential to cause crashes and which don’t, and Derq strives for over 95 percent accuracy. Incidents considered high risk are uploaded to Derq’s GPU cloud instance for further analysis and documentation. Eventually, the system will be able to notify connected and autonomous cars and warn them of impending dangers.

“If the driver detects someone is running a red light, that’s too late,” Aoude said. “If you tell the driver two seconds in advance, they now have the chance to react and avoid the collision.”

The Detroit test demonstrated that the system was able to identify potential crashes effectively. Having seen the technology, the Michigan Department of Transportation has expanded its engagement with Derq, which was recently awarded a federal project to deploy its technology at 65 key intersections along 25 miles of connected roads in the Motor City.

Derq has also been deploying its technology in Dublin, Ohio, a suburb of Columbus, and in Las Vegas, and is running a pilot with California Department of Transportation. It’s in discussions with cities in Florida and Texas, as well as in Canada. Further afield, it’s deployed its systems in Dubai and is working with the road and transport agency there on expanding that deployment as well.

Choosing the Right GPU

Derq’s edge units are equipped with NVIDIA GPUs and hardware acceleration that enable them to process large amounts of internet of things data in real time. It’s developing for a variety of GPUs, including the NVIDIA RTX, T4, and Jetson Nano, AGX Xavier and TX2.

But GPUs are just one part of Derq’s relationship with NVIDIA. As a member of the NVIDIA Inception program for AI startups, Aoude said Derq has had an Inception team visit the company’s Dubai office to provide support such as how to optimize their use of GPUs. They’re also in the process of being incorporated into the NVIDIA Metropolis smart spaces AI platform, which Aoude said “will be a great platform to help us scale.”

The company has focused its product on two main unit sizes. A basic unit runs a single application — think of a box that’s deployed at a pedestrian crosswalk — a perfect pairing for a Jetson AGX Xavier. More elaborate boxes, which run more apps on more camera streams at complex and busy intersections, will rely on the more powerful NVIDIA T4 or RTX GPUs.

Derq will also provide traffic planners and engineers with valuable statistics and intelligence, such as real-time graphs, incident notifications and heatmaps, that can help them assess and improve road safety. The system also can provide forensics for government agencies and insurance companies investigating crashes, an area that the company is exploring with insurance providers.

Going forward, Aoude said Derq plans to scale quickly through partnerships with cities, smart infrastructure, and autonomous vehicle firms so that it can get its technology deployed as widely as possible before autonomous vehicles hit the roadways in large numbers.

“We can’t do it on our own,” he said. “We need forward-thinking cities and collaborative partners, and get ready to scale deployments together, to achieve vision zero – eliminating all road fatalities.”

Financial services companies are challenged with defining and executing their AI strategy.

AI solutions contribute to both the top and bottom line for firms by powering nearly every function, including customer service, cybersecurity, new account acquisition and regulatory compliance.

Everyone from executives to data scientists are involved with determining how much to invest, the most profitable use cases to pursue and the biggest challenges that must be overcome in 2021 and beyond.

These are some of the findings of NVIDIA’s recent survey of over 200 financial services professionals from around the world. To fill in a more complete picture of how financial services institutions are using AI, and where it’s headed, our “State of AI in Financial Services” survey consisted of questions covering a range of AI topics, such as deployment models, infrastructure spending, top use cases and biggest challenges. Respondents included C-suite leaders, managers, developers and IT architects from fintechs, investment firms and retail banks.

Getting a Pulse on AI in Financial Services

The survey results showed two consistent themes: AI provides a competitive advantage in financial services, and banks plan to invest significantly in AI infrastructure to unlock its full potential.

Among different roles and subsectors within the industry, the survey data showed finer differences in how AI can best be deployed and the specific challenges for business decision makers and technical implementers.

Three highlights stood out among the survey results:

AI-Enabled Services Grow Revenue and Cut Costs

Our respondents were in widespread agreement on the value of enterprise AI, as 83 percent agreed with the statement that “AI is important to my company’s future success.”

The survey results showed how financial services firms view AI as an enabler of growth opportunities. Over half of those surveyed who had an opinion stated AI will increase their company’s annual revenue by 10 percent or more. In contrast, only 12 percent of respondents — excluding those who marked “Don’t Know” — stated that AI is having no impact on their revenue growth.

AI can also improve the bottom line of financial services institutions through cost savings. For instance, banks, insurers and asset managers are creating significant efficiencies in their daily operations using technologies such as conversational AI, robotic process automation, optical character recognition and other machine learning and deep learning applications.

These AI services save time and reduce expenditures by automating insurance claims processing, augmenting call center agents via automated speech recognition for call transcription and carrying out other manually intensive services.

Passing AI Benefits to Customers

Survey respondents said the top three areas where AI affected their companies were yielding more accurate models (42 percent), creating a competitive advantage (41 percent) and building new products (34 percent).

Utilizing AI to create more accurate models means better outcomes for banks and their customers, particularly in protecting against fraud and maximizing investment returns. These benefits translate into competitive advantage that often leads to increased market share and greater shareholder value. New products from AI enable cross-sell opportunities through enhanced personalization, which generates higher customer retention.

Challenges to Achieving AI Goals

While the benefits of leveraging AI in financial services are unmistakable, the journey from research to enterprise-scale production for AI models within banks, insurers and asset managers is marked with potential pitfalls and challenges.

Our survey identified those barriers, starting with the biggest challenges to achieving a company’s AI goals. The top three cited by respondents were too few data scientists (38 percent), insufficient technology infrastructure (35 percent) and a lack of data (35 percent).

The C-suite is looking to overcome these challenges by building AI expertise across the enterprise. 60 percent of C-level executives responded that their largest focus moving forward is identifying additional AI use cases. One in two respondents from the C-suite noted that their company also plans to hire more AI experts — addressing the gap of too few data scientists.

These findings warrant further exploration, especially in the context of new AI frameworks and platforms for smarter banking.

Popular AI Use Cases for Financial Services

Survey respondents from fintechs and investment firms highlighted portfolio optimization and algorithmic trading as the top AI use cases their companies currently invest in. This data can be understood in the context of maximizing client returns on investment.

Respondents from commercial and retail banks, on the other hand, noted that their companies are mainly investing in AI for fraud detection through payments, transactions and anti-money laundering. These survey results reflect a primary focus on protecting sensitive financial data for their customers.

Powering the Future of Banking with Enterprise AI

With these top use cases for AI in financial services, and dozens if not hundreds more available to banks, insurers and asset managers, the industry is understandably looking to grow its investment in AI. Sixty-two percent of our survey respondents — excluding those who marked “Don’t Know” — agreed that their company should spend more on AI applications.

Financial services professionals not only see the potential in AI, but are willing to invest more to deliver on its promise. That potential is actively being realized by companies who see AI generating competitive advantage, creating new products, adding significant revenues to the top line, and reducing costs to grow the bottom line.

As new use cases are identified and AI becomes more pervasive across organizations, the next challenge for C-suite and IT leadership will be creating enterprise-level AI platforms that deliver the productivity, scalability and return on investment necessary to support the variety of AI teams across their companies.

And, instead of starting from scratch, data scientists building models for a variety of use cases can utilize containers from NGC, NVIDIA’s hub of GPU-optimized software. These include NVIDIA Jarvis for automated speech recognition and speech to text for call center transcription to NVIDIA Merlin for recommendation system application frameworks.

To learn more about AI in the future of finance, download the survey report for more in-depth results.

And join GTC 2021 for free to hear from industry experts at Citibank, Morgan Stanley, Munich Re, Scotiabank, Wells Fargo and other leading financial institutions.

The autonomous trucking industry is about to get a major new addition.

Self-driving truck company Plus announced that its upcoming autonomous vehicle platform will be built on NVIDIA DRIVE Orin. This software-defined system will continuously improve upon the safety and efficiency of the delivery and logistics industry with high-performance compute and AI algorithms that can be updated over the air.

The self-driving system, known as PlusDrive, can be retrofitted to existing trucks or added as an upfit option on new vehicles by manufacturers. The company plans to roll out the next-generation platform in 2022 and has already received more than 10,000 pre-orders.

With DRIVE Orin at the center, PlusDrive uses lidar, radar and cameras to provide a 360-degree view of the truck’s surroundings. Data gathered through the sensors helps the system identify objects nearby, plan its course, predict the movement of those objects and control the vehicle to make its next move safely.

Innovating an Industry

Trucking has played an increasingly vital role in the world economy. For example, commercial vehicles transport more than 70 percent of all freight in the U.S. as e-commerce and next-day delivery have skyrocketed in popularity.

These trends come as driver shortages accelerate. The American Trucking Association estimates the industry could be in need of 160,000 drivers by 2028, in addition to limits on the amount of hours drivers can consecutively work that restrict operation. With the ability to efficiently operate around the clock, autonomous trucks promise to ease much of these industry pressures.

In contrast to lighter passenger vehicles, trucks can total 80,000 pounds with a fully loaded trailer and need a longer time to come to a stop. Developing autonomous commercial vehicles requires a system that can perceive long distances in real time to enable these trucks to safely maneuver.

By leveraging DRIVE Orin, Plus is building an intelligent, software-defined solution to address these challenges in the near term.

Big Brains for Big Rigs

Autonomous vehicles require high-performance compute for truly intelligent operation.

NVIDIA Orin is a system-on-a-chip born out of the data center. It achieves 254 TOPS — nearly 8x the performance of the previous generation Xavier SoC — and is designed to handle the large number of applications and deep neural networks that run simultaneously in autonomous trucks, while achieving systematic safety standards such as ISO 26262 ASIL-D.

This massive compute capability ensures the PlusDrive system is continuously learning, expanding the environments and situations in which it can operate autonomously.

“The greatest computing power is needed to process the trillions of operations that our autonomous driving system runs every second,” said Hao Zheng, Plus CTO and co-founder. “NVIDIA Orin is a natural choice for us.”

Plus is also a member of NVIDIA Inception, an accelerator program for startups in the AI and data science fields.

“The early access to NVIDIA’s autonomous vehicle technologies roadmap and solutions through the Inception program enables us to evaluate and adopt the latest hardware to provide the powerful real time performance required of our autonomous trucking system,” Zheng said.

Software-Defined Progress

Plus has already achieved significant self-driving milestones, and with a new software-defined platform, the company is giving itself plenty of room to excel further.

In 2019, Plus made history in the U.S. by successfully completing a cross-country autonomous trucking route in just three days. The company has conducted testing in 17 states and is currently operating commercial pilots with leading shipping companies in both the U.S. and China.

With the new Orin-based system, PlusDrive’s capabilities will continue to get better as AI technology advances. Orin’s massive compute headroom makes it easier to integrate and update advanced software features as they’re developed, enabling these intelligent trucks to continue down the open road of safer, more efficient delivery and logistics.

This April, learn about the future of AI-powered transportation from those who are building it.

The NVIDIA GPU Technology Conference returns to the virtual stage April 12-16, featuring autonomous vehicle leaders in a range of talks, panels and virtual networking events. Attendees will also have access to hands-on training for self-driving development and other deep learning topics. Registration is free of charge.

Experience the latest advancements in safer, more efficient transportation, from training in the data center, to high-fidelity simulation testing, to new robotaxi and autonomous trucking pilots around the world.

With digital networking events and sessions with live Q&A, GTC is the only place where it’s possible to interact with researchers, engineers, developers and technologists in the autonomous vehicle space, as well as healthcare, robotics, graphics and numerous other industries.

The week will kick off with a not-to-be-missed opening keynote from NVIDIA founder and CEO Jensen Huang that will be packed with the latest NVIDIA news and breakthroughs.

Here’s a sneak peek at the automotive offerings at this year’s event.

Expert Lineup

With rapid advances in AI technology, it can be difficult to follow the flurry of headlines and announcements surrounding autonomous vehicles. GTC provides the unique opportunity to hear about these innovations from those in the trenches of self-driving development — from global automakers and suppliers to startups and researchers.

Automotive session highlights include:

• Jesse Levinson, CTO and co-founder of Zoox, sits down for a fireside chat on the robotaxi startup’s recently unveiled vehicle and upcoming technology roadmap.
• Hildegard Wortmann, member of the board of management at Audi, discusses how the global automaker is addressing the largest transformation in the history of the automotive industry, driven by digitalization, electrification and sustainability.
• Mo ElShenawy, senior vice president of engineering at Cruise, covers the challenges and benefits of building an autonomous vehicle from the ground up.
• Raquel Urtasun, professor at University of Toronto and chief scientist at Uber ATG Toronto, outlines the upcoming autonomous future, where robotics and AI are intertwined in daily life, and the technological challenges that remain to achieve this new era.
• Gavriel State, senior director of system software at NVIDIA, showcases the NVIDIA DRIVE Sim platform on Omniverse, generating synthetic data to comprehensively train deep neural networks for autonomous vehicle applications.
• Cetin Mericli, CEO of Locomation, explains the technology as well as the challenges behind human-guided autonomous convoy systems for self-driving long-haul trucks.

Give AI a Try

Attendees don’t just hear about AI innovation at GTC, they can get hands on with new deep learning techniques to push technology further.

Courses hosted by the NVIDIA Deep Learning Institute provide a foundation for developing AI applications, including autonomous driving. In Deep Learning for Autonomous Vehicles — Perception, DLI attendees can learn how to design, train and deploy deep neural networks and optimize perception components for autonomous vehicles using the NVIDIA DRIVE development platform.

Additional topics include the fundamentals of deep learning, natural language processing and deep learning for multiple GPUs.

Take advantage of free GTC registration today. Short, hands-on DLI training sessions are available at no charge, while full-day workshops are priced at $249.

Don’t miss out on the only opportunity to meet, listen to and learn from the biggest stars in AI and autonomous vehicle technology.

With GeForce NOW, over 5 million gamers are playing their favorite games in the cloud on PC, Mac, Chromebook, NVIDIA SHIELD TV, Android and iOS devices.

With over 800 instantly available games and 80+ free-to-play games, there’s something for everyone. And there are multiple ways to build your library.

We’ll review how to sync your Steam game catalog, search for games, add games to your library, and explain the difference between Instant Access and Single Session games.

Start with a Steam Sync

GeForce NOW members, on average, have about 50 games in their Steam catalog. The quickest and easiest way to find all the instant access games you already own is by using the Game Sync option.

Simply launch GeForce NOW, select the Sync Your Games tile and log in to Steam. Now all your GeForce NOW supported Steam games appear in your GeForce NOW library.

Sync your entire Steam game library in about one minute.

Members can also sync their Steam library by going to Settings > Game Sync.

Once your Steam account is authorized, you can update your GeForce NOW library from Settings > Game Sync every time you purchase a new Steam game. It’s the easiest way to keep your games catalog up to date in the GeForce NOW app.

Discover Games on GeForce NOW

The complete GeForce NOW games list is available online, including the latest releases.

Members can also find games in GeForce NOW using the search function, a powerful tool that lets you search by game title, developer, publisher, genre or keyword. Try searching for “kittens” and see what you find.

GeForce NOW expands its games library each week. The latest games are available day-and-date, while back catalog games are added every Thursday. Check back regularly to see what’s new.

Add Your Games to Your GeForce NOW Library

Owners of games from Ubisoft Connect, Epic Games Store (looking at you, Fortnite fans) or custom game launchers can search for games and manually add them to My Library by clicking +LIBRARY.

After that, click PLAY and if it’s the first time playing that game, just sign in to your account, when prompted, and you’re ready to game.

Suddenly your games are available on all the devices you own.

Buying Games to Play with GeForce NOW

GeForce NOW is a powerful gaming PC in the cloud — not a store.

Even though it’s not a store, members can still buy Steam games while in the app. There are two ways to do this. Add the game to your library, click PLAY, log in to Steam and purchase as you normally would. Or launch Steam to browse and make purchases.

For other game stores, or custom game launchers, you can purchase a supported game through the respective store, then go back into the GeForce NOW app to add it as outlined above.

Discover a game you want to play? Find which store it’s supported on in the game page.

Featured GeForce NOW supported games are “Instant Access.” These appear within the app and can be added to your GeForce NOW library in less than a minute, all with streaming optimizations applied automatically for optimal graphics settings.

Don’t forget to check out weekly free games on the Epic Games Store, which are often supported on GeForce NOW.

Game Selection Explained

It’s important to remember how new cloud gaming is to NVIDIA and, especially, game publishers. Adding games to a new platform is a critical decision for publishers. Remember what Netflix was like when it first launched? Sending DVDs through the mail? Bold, but undeniably forward-thinking.

GeForce NOW uses an opt-in process to make it easy for developers and publishers to join the service. NVIDIA signs an agreement with every game developer before publishing their titles on GeForce NOW. There is no cost for developers — games just run without difficult porting requirements — helping them reach millions of players who don’t have game-ready PCs.

Now, Get YOUR Game On

GeForce NOW supports more than 800 games in total. More than 80 of those games are free-to-play. That’s a great way to start building your library, especially for members who are new to PC gaming.

Members can build their library with +80 (and counting) free-to-play games.

Sign up, download the app, browse a wide selection of titles, click the game of your choice and begin your cloud gaming journey with GeForce NOW.

Editor’s note: This is the second in a series on the GeForce NOW game-streaming service, how it works and where it’s going next. To learn more about cloud gaming, and the origins of GeForce NOW, read part one: GeForce NOW Explained: What is Cloud Gaming?

In our next blog, we’ll talk about latency, what it is and tips to improve your GeForce NOW experience.

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