SoftBank Group, NVIDIA CEOs on What’s Next for AI

Good news: AI will soon be everywhere. Better news: it will be put to work by everyone.

Sharing a vision of AI enabling humankind, NVIDIA CEO Jensen Huang Wednesday joined Masayoshi Son, Chairman and CEO of SoftBank Group Corp. as a guest for his keynote at the annual SoftBank World conference.

“For the first time, we’re going to democratize software programming,” Huang said. “You don’t have to program the computer; you just have to teach the computer.”

Son is a legendary entrepreneur, investor and philanthropist who pioneered the development of the PC industry, the internet and mobile computing in Japan.

A Technological Jewel

The online conversation comes six weeks after NVIDIA agreed to acquire Arm from SoftBank in a transaction valued at $40 billion. Huang described Arm as “one of the technology world’s great jewels” in his conversation with Son.

“The reason why combining Arm and NVIDIA makes so much sense is because we can then bring NVIDIA’s AI to the most popular edge CPU in the world,” Huang said while seated beside the fireplace of his Silicon Valley home.

Arm has long provided its intellectual property to many chipset vendors, who deploy it on many different applications, in many different systems-on-a-chip, or SoCs, Son explained.

Huang said the combined company would “absolutely” continue this.

An Ecosystem Like No Other

“Of course the CPU is fantastic, energy-efficient and it’s improving all the time, thanks to incredible computer scientists building the best CPU in the world,” Huang said. “But the true value of Arm is in the ecosystem of Arm — the 500 companies that use Arm today.”

That ecosystem is growing fast. Son said it won’t be long until a trillion Arm-based SoCs have been shipped. Making NVIDIA AI available to those trillion chipsets “will be an amazing combination,” Son said.

“Our dream is to bring NVIDIA’s AI to Arm’s ecosystem, and the only way to bring it to the Arm ecosystem is through all of the existing customers, licensees and partners,” Huang said. “We would like to offer the licensees more, even more.”

Arm, Son said, provides toolsets to enable companies to create SoCs for very different applications, from game machines and home appliances to robots that fly or run or swim. These devices will, in turn, communicate with cloud AI “so each of them become smarter.”

“That’s the reason why combining Arm and NVIDIA makes so much sense because we can then bring NVIDIA AI to the most popular edge CPU in the world,” Huang said.

‘Intelligence at Scale’

That will allow even more companies to participate in the AI boom.

“AI is a new kind of computer science; the software is different, the chips are different, the methodology is different,” Huang said.

It’s a huge shift, Son agreed.

First, Son said, computers enabled advancements in calculation; next, came the ability to store massive amounts of data; and “now, finally, computers are the ears and the eyes, so they can recognize voice and speech.”

“It’s intelligence at scale,” Huang responded. “That’s the reason why this age of AI is such an important time.”

Extending Human Capabilities

Son and Huang spoke about how enterprises worldwide — from AstraZeneca and GlaxoSmithKline in drug discovery, to American Express in banking, to Walmart in retail, to Microsoft in software, to Kubota in agriculture — are now adopting NVIDIA AI tools.

Huang cited a new generation of systems, called recommender systems, that are already helping humans sort through vast array choices available online in everything from what clothes they wear to what music they listen to.

Huang and Son describe such systems — and AI more broadly — as a way to extend human capabilities.

“Humans will always be in the loop,” Huang said.

“We have a heart, a desire to be nice to other humans,” Son said. “We will utilize AI as a tool, for our happiness, for our joy — humans will choose which recommendations to take.”

‘Perpetually Learning Machines’

Such intelligent systems are being woven into the world around us, through smart, connected systems, or “edge AI,” Son said, which will work hand in hand with powerful cloud AI systems able to aggregate input from devices in the real world.

The result will be a “learning loop,” or “perpetually learning machines,” Huang said.

“The cloud side will aggregate information from edge AI, it will become smarter and smarter,” Son said.

Democratizing AI

One result: computing will finally be democratized, Huang said. Only a small number of people want to pursue a career as a computer programmer, but “everyone can teach,” Huang said.

“You [will] just ask the computer, ‘This is what I want to do, can you give me a solution?,’” Son responded. “Then the computer will give us the solution and the tools to make it happen.”

Such tools will amplify Japan’s strengths in precision engineering and manufacturing.

“This is the time of AI for Japan,” Huang said.

Huang described how, in tools such as NVIDIA Omniverse, a digital factory can be continually optimized.

“This robotic factory will be filled with robots that will build robots in virtual reality,” Huang said. “The whole thing will be simulated … and when you come in in the morning the whole thing will be optimized more than it was when you went to bed.”

Once it’s ready, a physical twin of the digital factory can be built and continually optimized with lessons learned in the virtual one.

“It’s the concept of the metaverse” Son said, referring to the shared, online world of imagined in Neal Stephensen’s 1992 cyberpunk classic, “Snow Crash.”

“… and it’s right in front of us now,” Huang added.

Connecting Humans with One Another

In addition to extending human capabilities with AI, it will help humans better connect with one another.

Video conferencing will soon be the vast majority of the world’s internet traffic, Huang said. Using AI to reconstruct a speaker’s facial expressions can “reduce bandwidth” by a factor of 10.

It can also unleash new capabilities, such as the ability for a speaker to make direct eye contact with 20 different people watching simultaneously, or real-time language translation.

“So you can speak to me in the future in Japanese and I can speak to you in English, and you will hear Japanese and I will hear English,” Huang said.

Enabling Big Dreams

Melding human judgment and AI, adaptive, autonomous machines and tightly connected teams of people will give entrepreneurs, philanthropists and others with “big wishes and big dreams” the ability to tackle ever more ambitious challenges, Huang said.

Son said AI is playing a role in the development of technologies that can detect heart attacks before they happen, speed the discovery of new treatments for cancer, and eliminate car accidents, among others.

“It is a big help,” Son said. “So we should be having a big smile, and big excitement, welcoming this revolution in AI.”

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At GTC, Educators and Leaders Focus on Equity in AI, Developer Diversity

Not everyone needs to be a developer, but everyone will need to be an AI decision maker.

That was the message behind a panel discussion on Advancing Equitable AI, which took place at our GPU Technology Conference last week. It was one of several GTC events advancing the conversation on diversity, equity and ethics in AI.

This year, we strengthened our support for women and underrepresented developers and scientists at GTC by providing conference passes to members of professional organizations supporting women, Black and Latino developers. Professors at historically Black colleges and universities — including Prairie View A&M University, Hampton University and Jackson State University — as well as groups like Black in AI and LatinX in AI received complimentary access to training from the NVIDIA Deep Learning Institute.

A Forbes report last year named GTC as one of the U.S.’s top conferences for women to attend to further their careers in AI. At this month’s event, women made up better than one in five registered attendees — doubling last year’s count and an almost 4x increase since 2017 — and more than 100 of the speakers.

And in a collaboration with the National Society of Black Engineers that will extend beyond GTC, we created opportunities for the society’s collegiate and professional developers to engage with NVIDIA’s recruiting team, which provided guidance on navigating the new world of virtual interviewing and networking.

“We’re excited to be embarking on a partnership with NVIDIA,” said Johnnie Tangle, national finance chairman of NSBE Professionals. “Together, we are both on the mission of increasing the visibility of Blacks in development and showing why diversity in the space enhances the community as a whole.”

Panel Discussions: Paving Pathways for Equitable AI

Two power-packed, all-female panels at GTC focused on a roadmap for responsible and equitable AI.

In a live session that drew over 250 attendees, speakers from the University of Florida, the Boys and Girls Club of Western Pennsylvania and AI4All — a nonprofit working to increase diversity and inclusion in AI — discussed the importance of AI exposure and education for children and young adults from underrepresented groups.

When a broader group of young people has access to AI education, “we naturally see a way more diverse and interesting set of problems being addressed,” said Tess Posner, CEO of AI4All, “because young people and emerging leaders in the field are going to connect the technology to a problem they’ve seen in their own lives, in their own experience or in their communities.”

The conversation also covered the role parents and schools play in fostering awareness and exposure to STEM subjects in their children’s schools, as well as the need for everyone — developers or not — to have a foundational understanding of how AI works.

“We want students to be conscious consumers, and hopefully producers,” said Christina Gardner-McCune, associate professor and director of the Engaging Learning Lab at the University of Florida, and co-chair of the AI4K12 initiative. “Everybody is going to be making decisions about what AI technologies are used in their homes, what AI technologies their children interact with.”

Later in the week, a panel titled “Aligning Around Common Values to Advance AI Policy” explored ideas to pave the way for responsible AI on a global scale.

The webinar featured representatives from the U.S. National Institute of Standards and Technology, Scotland-based innovation center The Data Lab, and C Minds, a think tank focused on AI initiatives in Latin America. Speakers shared their priorities for developing trustworthy AI, and defined what success would like to them five years in the future.

Dinner with Strangers: Developer Diversity in AI

In a virtual edition of the popular Dinner with Strangers networking events at GTC, experts from NVIDIA and NSBE partnered to moderate two conversations with GTC attendees. NVIDIA employees shared their experiences and tips with early-career attendees, offering advice on how to build a personal brand in a virtual world, craft a resume and prepare for interviews.

For more about GTC, watch NVIDIA founder and CEO Jensen Huang’s keynote below.

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AI in Schools: Sony Reimagines Remote Learning with Artificial Intelligence

Back to school was destined to look different this year.

With the world adapting to COVID-19, safety measures are preventing a return to in-person teaching in many places. Also, students learning through conventional video conferencing systems often feel the content is difficult to read, or teachers block the words written on presentation boards.

Faced with these challenges, educators at Prefectural University of Hiroshima in Japan envisioned a high-quality remote learning system with additional features not possible with traditional video conferencing.

They chose a distance-learning solution from Sony that links lecturers and students across their three campuses. It uses AI to make it easy for presenters anywhere to engage their audiences and impart information using captivating video. Thanks to these innovations, lecturers at Prefectural University can now teach students simultaneously on three campuses linked by a secure virtual private network.

Sony’s remote learning solution in action, with Edge Analytics Appliance, remote cameras and projectors.

AI Helps Lecturers Get Smarter About Remote Learning

At the heart of Prefectural’s distance learning system is Sony’s REA-C1000 Edge Analytics Appliance, which was developed using the NVIDIA Jetson Edge AI platform. The appliance lets teachers and speakers quickly create dynamic video presentations without using expensive video production gear or learning sophisticated software applications.

Sony’s exclusive AI algorithms run inside the appliance. These deep learning models employ techniques such as automatic tracking, zooming and cropping to allow non-specialists to produce engaging, professional-quality video in real time.

Users simply connect the Edge Analytics Appliance to a camera that can pan, tilt and zoom; a PC; and a display or recording device. In Prefectural’s case, multiple cameras capture what a lecturer writes on the board, questions and contributions from students, and up to full HD images depending on the size of the lecture hall.

Managing all of this technology is made simple for the lecturers. A touchscreen panel facilitates intuitive operation of the system without the need for complex adjustment of camera settings.

Teachers Achieve New Levels of Transparency

One of the landmark applications in the Edge Analytics Appliance is handwriting extraction, which lets students experience lectures more fully, rather than having to jot down notes.

The application uses a camera to record text and figures as an instructor writes them by hand on a whiteboard or blackboard, and then immediately draws them as if they are floating in front of the instructor.

Students viewing the lecture live from a remote location or from a recording afterward can see and recognize the text and diagrams, even if the original handwriting is unclear or hidden by the instructor’s body. The combined processing power of the compact, energy-efficient Jetson TX2 and Sony’s moving/unmoving object detection technology makes the transformation from the board to the screen seamless.

Handwriting extraction is also customizable: the transparency of the floating text and figures can be adjusted, so that characters that are faint or hard to read can be highlighted in color, making them more legible — and even more so than the original content written on the board.

Create Engaging Content Without Specialist Resources

 

Another innovative application is Chroma key-less CG overlay, using state-of-the-art algorithms from Sony, like moving-object detection, to produce class content without the need for large-scale video editing equipment.

Like a personal greenscreen for presenters, the application seamlessly places the speaker in front of any animations, diagrams or graphs being presented.

Previously, moving-object detection algorithms required for this kind of compositing could only be run on professional workstations. With Jetson TX2, Sony was able to include this powerful deep learning-based feature within the compact, simple design of the Edge Analytics Appliance.

A Virtual Camera Operator

Numerous additional algorithms within the appliance include those for color-pattern matching, shape recognition, pose recognition and more. These enable features such as:

• PTZ Auto Tracking — automatically tracks an instructor’s movements and ensures they stay in focus.
• Focus Area Cropping — crops a specified portion from a video recorded on a single camera and creates effects as if the cropped portion were recorded on another camera. This can be used to generate, for example, a picture-in-picture effect, where an audience can simultaneously see a close-up of the presenter speaking against a wide shot of the rest of the stage.
• Close Up by Gesture — automatically zooms in on and records students or audience members who stand up in preparation to ask a question.

With the high-performance Jetson platform, the Edge Analytics Appliance can easily handle a wide range of applications like these. The result is like a virtual camera operator that allows people to create engaging, professional-looking video presentations without the expertise or expense previously required to do so.

Officials at Prefectural University of Hiroshima say the new distance learning initiative has already led to greater student and teacher satisfaction with remote learning. Linking the university’s three campuses through the system is also fostering a sense of unity among the campuses.

“We chose Sony’s Edge Analytics Appliance for our new distance learning design because it helps us realize a realistic and comfortable learning environment for students by clearly showing the contents on the board and encouraging discussion. It was also appealing as a cost-effective solution as teachers can simply operate without additional staff,” said Kyousou Kurisu, director of public university corporation, Prefectural University of Hiroshima.

Sony plans to continually update applications available on the Edge Analytics Appliance. So, like any student, the system will only get better over time.

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Meet the Maker: Mr. Fascinate Encourages Kids to Get on the Cool Bus and Study STEM

STEM is dope. That’s the simple message that Justin “Mr. Fascinate” Shaifer evangelizes to young people around the world.

Through social media and other platforms, Shaifer fascinates children with STEM projects — including those that can be created using AI with NVIDIA Jetson products — in hopes that more students from underrepresented groups will be inspired to dive into the field. NVIDIA Jetson embedded systems allow anyone to create their own AI-based projects.

Growing up on Chicago’s South Side, Shaifer didn’t know anyone with a career in STEM he could look up to — at least no one he could relate to. Now, he’s become that role model for thousands of kids, working to prove that STEM is cool and attainable for anyone who has a passion for it.

About the Maker

Shaifer is a STEM advocate, animator and TV host who educates students about the importance of STEM and diversity within it. He has a YouTube channel, gives keynote speeches and hosts the Escape Lab live science show on Twitch.

He’s also the founder of Fascinate Inc., a nonprofit with the mission of exciting underrepresented students about careers in STEM and providing schools and after-school programs with fun science curricula.

The organization also launched the Magic Cool Bus project, filling a real-life bus with cutting-edge tech gadgets and bringing it to schools so students can hop on board and explore.

Growing up in a single-parent home, Shaifer was fascinated by science, earning scholarships from NASA and NOAA that covered his expenses to study marine and environmental science at Hampton University. He’s currently working toward a Ph.D. in science education at Columbia University.

His Inspiration

Shaifer was inspired to transition from being a scientist in a lab to a science educator for others in 2017, while volunteering at a museum in Washington.

“I was freestyle rapping about a carbon cycle exhibit, and this nine-year-old Black kid came up to me and said, ‘What do you do, man?’” said Shaifer.

When Shaifer told him he was a scientist, the child said, “That’s so cool. When I grow up, I want to be a scientist just like you!”

“That made me reflect on the fact that at nine years old, I’d never seen an example of a scientist that looked like me,” said Shaifer. “I realized that students need to be exposed to a role model in STEM that they can identify with, at scale.”

Later that year, Shaifer founded Fascinate Inc.

His Favorite Jetson Projects

Shaifer is passionate about exposing students to the world of AI, and he says using NVIDIA Jetson platform is a great way to do so.

Watch him highlight Jetson products:

NVIDIA Jetson Xavier NX Unboxing and Impression

NVIDIA SparkFun JetBot AI Kit Unboxing and Impression

One of Shaifer’s favorite real-world applications that uses the NVIDIA Jetson Nano developer kit is Qrio. The bot, created by Agustinus Nalwan, recognizes a toddler’s toy and plays a relevant YouTube video.

“Especially since I work with young kids, I think that’s a really cool application that allows a child to be engaged, interactive and always learning as they play with their toys,” said Shaifer.

Where to Learn More 

Get fascinated by STEM on Shaifer’s website and YouTube channel.

Discover tools, inspiration and three easy steps to help kickstart your project with AI on our “Get AI, Learn AI, Build AI” page.

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Letter From Jensen: Creating a Premier Company for the Age of AI

NVIDIA founder and CEO Jensen Huang sent the following letter to NVIDIA employees today:

Hi everyone, 

Today, we announced that we have signed a definitive agreement to purchase Arm. 

Thirty years ago, a visionary team of computer scientists in Cambridge, U.K., invented a new CPU architecture optimized for energy-efficiency and a licensing business model that enables broad adoption. Engineers designed Arm CPUs into everything from smartphones and PCs to cloud data centers and supercomputers. An astounding 180 billion computers have been built with Arm — 22 billion last year alone. Arm has become the most popular CPU in the world.   

Simon Segars, its CEO, and the people of Arm have built a great company that has shaped the computer industry and nearly every technology market in the world. 

We are joining arms with Arm to create the leading computing company for the age of AI. AI is the most powerful technology force of our time. Learning from data, AI supercomputers can write software no human can. Amazingly, AI software can perceive its environment, infer the best plan, and act intelligently. This new form of software will expand computing to every corner of the globe. Someday, trillions of computers running AI will create a new internet — the internet-of-things — thousands of times bigger than today’s internet-of-people.   

Uniting NVIDIA’s AI computing with the vast reach of Arm’s CPU, we will engage the giant AI opportunity ahead and advance computing from the cloud, smartphones, PCs, self-driving cars, robotics, 5G, and IoT. 

NVIDIA will bring our world-leading AI technology to Arm’s ecosystem while expanding NVIDIA’s developer reach from 2 million to more than 15 million software programmers. 

Our R&D scale will turbocharge Arm’s roadmap pace and accelerates data center, edge AI, and IoT opportunities. 

Arm’s business model is brilliant. We will maintain its open-licensing model and customer neutrality, serving customers in any industry, across the world, and further expand Arm’s IP licensing portfolio with NVIDIA’s world-leading GPU and AI technology. 

Arm’s headquarter will remain in Cambridge and continue to be a cornerstone of the U.K. technology ecosystem. NVIDIA will retain the name and strong brand identity of Arm. Simon and his management team are excited to be joining NVIDIA.  

Arm gives us the critical mass to invest in the U.K. We will build a world-class AI research center in Cambridge — the university town of Isaac Newton and Alan Turing, for whom NVIDIA’s Turing GPUs and Isaac robotics platform were named. This NVIDIA research center will be the home of a state-of-the-art AI supercomputer powered by Arm CPUs. The computing infrastructure will be a major attraction for scientists from around the world doing groundbreaking research in healthcare, life sciences, robotics, self-driving cars, and other fields. This center will serve as our European hub to collaborate with universities, industrial partners, and startups. It will also be the NVIDIA Deep Learning Institute for Europe, where we teach the methods of applying this marvelous AI technology.  

The foundation built by Arm and NVIDIA employees has provided this fantastic opportunity to create the leading computing company for the age of AI. The possibilities of our combined companies are beyond exciting.   

I can’t wait. 

Jensen

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NVIDIA and Arm to Create World-Class AI Research Center in Cambridge

Artificial intelligence is the most powerful technology force of our time. 

It is the automation of automation, where software writes software. While AI began in the data center, it is moving quickly to the edge — to stores, warehouses, hospitals, streets, and airports, where smart sensors connected to AI computers can speed checkouts, direct forklifts, orchestrate traffic, and save power. In time, there will be trillions of these small autonomous computers powered by AI, connected by massively powerful cloud data centers in every corner of the world.

But in many ways, the field is just getting started. That’s why we are excited to be creating a world-class AI laboratory in Cambridge, at the Arm headquarters: a Hadron collider or Hubble telescope, if you like, for artificial intelligence.  

NVIDIA, together with Arm, is uniquely positioned to launch this effort. NVIDIA is the leader in AI computing, while Arm is present across a vast ecosystem of edge devices, with more than 180 billion units shipped. With this newly announced combination, we are creating the leading computing company for the age of AI. 

Arm is an incredible company and it employs some of the greatest engineering minds in the world. But we believe we can make Arm even more incredible and take it to even higher levels. We want to propel it — and the U.K. — to global AI leadership.

We will create an open center of excellence in the area once home to giants like Isaac Newton and Alan Turing, for whom key NVIDIA technologies are named. Here, leading scientists, engineers and researchers from the U.K. and around the world will come develop their ideas, collaborate and conduct their ground-breaking work in areas like healthcare, life sciences, self-driving cars and other fields. We want the U.K. to attract the best minds and talent from around the world. 

The center in Cambridge will include: 

• An Arm/NVIDIA-based supercomputer. Expected to be one of the most powerful AI supercomputers in the world, this system will combine state-of-the art Arm CPUs, NVIDIA’s most advanced GPU technology, and NVIDIA Mellanox DPUs, along with high-performance computing and AI software from NVIDIA and our many partners. For reference, the world’s fastest supercomputer, Fugaku in Japan, is Arm-based, and NVIDIA’s own supercomputer Selene is the seventh most powerful system in the world.  
• Research Fellowships and Partnerships. In this center, NVIDIA will expand research partnerships within the U.K., with academia and industry to conduct research covering leading-edge work in healthcare, autonomous vehicles, robotics, data science and more. NVIDIA already has successful research partnerships with King’s College and Oxford. 
• AI Training. NVIDIA’s education wing, the Deep Learning Institute, has trained more than 250,000 students on both fundamental and applied AI. NVIDIA will create an institute in Cambridge, and make our curriculum available throughout the U.K. This will provide both young people and mid-career workers with new AI skills, creating job opportunities and preparing the next generation of U.K. developers for AI leadership. 
• Startup Accelerator. Much of the leading-edge work in AI is done by startups. NVIDIA Inception, a startup accelerator program, has more than 6,000 members — with more than 400 based in the U.K. NVIDIA will further its investment in this area by providing U.K. startups with access to the Arm supercomputer, connections to researchers from NVIDIA and partners, technical training and marketing promotion to help them grow. 
• Industry Collaboration. The NVIDIA AI research facility will be an open hub for industry collaboration, providing a uniquely powerful center of excellence in Britain. NVIDIA’s industry partnerships include GSK, Oxford Nanopore and other leaders in their fields. From helping to fight COVID-19 to finding new energy sources, NVIDIA is already working with industry across the U.K. today — but we can and will do more. 

We are ambitious. We can’t wait to build on the foundations created by the talented minds of NVIDIA and Arm to make Cambridge the next great AI center for the world. 

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2 Million Registered Developers, Countless Breakthroughs

Everyone has problems.

Whether they’re tackling challenges at the cutting edge of physics, trying to tame a worldwide pandemic, or sorting their child’s Lego collection, innovators join NVIDIA’s developer program to help them solve their most challenging problems.

With the number of registered NVIDIA developers having just hit 2 million, NVIDIA developers are pursuing more breakthroughs than ever.

Their ranks continue to grow by larger numbers every year. It took 13 years to reach 1 million registered developers, and less than two more to reach 2 million.

Most recently, teams at the U.S. National Institutes of Health, Scripps Research Institute and Oak Ridge National Laboratory have been among the NVIDIA developers at the forefront of efforts to combat COVID-19.

Every Country, Every Field

No surprise. Whether they’re software programmers, data scientists or devops engineers, developers are problem solvers.

They write, debug and optimize code, often taking a set of software building blocks — frameworks, application programming interfaces and other tools — and putting them to work to do something new.

These developers include business and academic leaders from every region in the world.

In China, Alibaba and Baidu are among the most active GPU developers. In North America, those names include Microsoft, Amazon and Google. In Japan, it’s Sony, Hitachi and Panasonic. In Europe, they include Bosch, Daimler and Siemens.

All the top technical universities are represented, including CalTech, MIT, Oxford, Cambridge, Stanford, Tsinghua University, the University of Tokyo, and IIT campuses throughout India. 

Look beyond the big names — there are too many to drop here — and you’ll find tens of thousands of entrepreneurs, hobbyists and enthusiasts.

Developers are signing up for our developer program to put NVIDIA accelerated computing tools to work across fields such as scientific and high performance computing, graphics and professional visualization, robotics, AI and data science, networking, and autonomous vehicles.

Developers are trained and equipped for success through our GTC conferences, online and in-person tutorials, our Deep Learning Institute training, and technical blogs. We provide them with software development kits such as CUDA, cuDNN, TensorRT and OptiX.

Registered developers account for 100,000 downloads a month, thousands participate each month in DLI training sessions, and thousands more engage in our online forums or attend conferences and webinars.

NVIDIA’s developer program, however, is just a piece of a much bigger developer story. There are now more than a billion CUDA GPUs in the world — each capable of running CUDA-accelerated software — giving developers, hackers and makers a vast installed base to work with.

As a result, the number of downloads of CUDA, which is free, without registration, is far higher than that of registered developers. On average, 39,000 developers sign up for memberships each month and 438,000 download CUDA each month.

That’s an awful lot of problem solvers.

Breakthroughs in Science and Research

The ranks of those who depend on such problem solvers include the team who won the 2017 Nobel Prize in Chemistry — Jacques Dubochet, Joachim Frank and Richard Henderson — for their contribution to cryogenic electron microscopy.

They also include the team that won the 2017 Nobel Prize in Physics — Rainer Weiss, Barry Barish and Kip Thorne — for their work detecting gravitational waves.

More scientific breakthroughs are coming, as developers attack new HPC problems and, increasingly, deep learning.

William Tang, principal research physicist at the Princeton Plasma Physics Laboratory — one of the world’s foremost experts on fusion energy — leads a team using deep learning and HPC to advance the quest for cheap, clean energy.

Michael Kirk and Raphael Attie, scientists at NASA’s Goddard Space Flight Center — are among the many active GPU developers at NASA — relying on Quadro RTX data science workstations to analyze the vast quantities of data streaming in from satellites monitoring the sun.

And at UC Berkeley, astrophysics Ph.D. student Gerry Zhang uses GPU-accelerated deep learning to analyze signals from space for signs of intelligent extraterrestrial civilizations.

Top Companies

Outside of research and academia, developers at the world’s top companies are tackling problems faced by every one of the world’s industries.

At Intuit, Chief Data Officer Ashok Srivastava leads a team using GPU-accelerated machine learning to help consumers with taxes and help small businesses through the financial effects of COVID-19.

At health insurer Anthem, Chief Digital Officer Rajeev Ronanki uses GPU-accelerated AI to help patients personalize and better understand their healthcare information.

Arne Stoschek, head of autonomous systems at Acubed, the Silicon Valley-based advanced products and partnerships outpost of Airbus Group, is developing self-piloted air taxis powered by GPU-accelerated AI.

New Problems, New Businesses: Entrepreneurs Swell Developer Ranks

Other developers — many supported by the NVIDIA Inception program — work at startups building businesses that solve new kinds of problems.

Looking to invest in a genuine pair of vintage Air Jordans? Michael Hall, director of data at GOAT Group, uses GPU-accelerated AI to help the startup connect sneaker enthusiasts with Air Jordans, Yeezys and a variety of old-school kicks that they can be confident are authentic.

Don’t know what to wear? Brad Klingenberg, chief algorithms officer at fashion ecommerce startup Stitch Fix, leads a team that uses GPU-accelerated AI to help us all dress better.

And Benjamin Schmidt, at Roadbotics, offers what might be the ultimate case study in how developers are solving concrete problems: his startup helps cities find and fix potholes.

Entrepreneurs are also supported by NVIDIA’s Inception program, which includes more than 6,000 startups in industries ranging from agriculture to healthcare to logistics to manufacturing.

Of course, just because something’s a problem, doesn’t mean you can’t love solving it.

Love beer? Eric Boucher, a home brewing enthusiast, is using AI to invent new kinds of suds.

Love a critter-free lawn? Robert Bond has trained a system that can detect cats and gently shoo them from his grass by turning on his sprinklers to the amazement and delight of his grandchildren.

Francisco “Paco” Garcia has even trained an AI to help sort out his children’s Lego pile.

Most telling: stories from developers working at the cutting edge of the arts.

Pierre Barreau has created an AI, named AIVA, which uses mathematical models based on the work of great composers to create new music.

And Raiders of the Lost Art — a collaboration between Anthony Bourached and George Cann, a pair of Ph.D. candidates at the University College, London — has used neural style transfer techniques to tease out hidden artwork in a Leonardo da Vinci painting.

Wherever you go, follow the computing power and you’ll find developers delivering breakthroughs.

How big is the opportunity for problem solvers like these? However many problems there are in the world.

Want more stories like these? No problem. Over the months to come, we’ll be bringing as many to you as we can. 

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NVIDIA Partner Program Expands to 1,500 Members, Adds New Benefits

NVIDIA’s enterprise partner program has grown to more than 1,500 members worldwide and added new resources to boost opportunities for training, collaboration and sales.

The expanded NVIDIA Partner Network boasts an array of companies that span the globe and help customers across a variety of needs, from high performance computing to systems integration.

NPN partners span the globe.

The NPN has seen exponential growth over the past two years, and these new program enhancements enable future expansion as Mellanox and Cumulus partner programs are set to be integrated into NPN throughout 2021.

Mellanox and Cumulus bring strong partners into the NVIDIA fold. Focused on enterprise data center markets, they provide accelerated, disaggregated and software-defined networking to meet the rapid growth in AI, cloud and HPC.

In anticipation of this growth, the NPN has introduced educational opportunities, tools and resources for training and collaboration, as well as added sales incentives. These benefits include:

Educational opportunities:

• Industry-Specific Training Curriculums: New courses and enablement tools in healthcare, higher education and research, financial services and insurance, and retail. Additional courses in energy and telco are coming next year.
• NPN Learning Maps: These dramatically reduce the time partners need to get up and running. Partners can discover and build their NVIDIA learning matrix based on industry and cross-referenced by role, including sales, solution architect or data scientist.

New tools and resources:

• AI Consulting Network: New AI consulting services for data scientists and solution architects who are part of our Service Delivery Partner-Professional Services program to help build and deploy HPC and AI solutions.
• Enhanced NPN Partner Portal: Expanded to allow access to the vast storehouse of NVIDIA-built sales tools and data, including partner rebate history and registered opportunities. The simplified portal gives partners increased visibility and easy access to the information required to quickly track sales and build accurate forecasts.
• Industry-Specific Marketing Campaigns: Provides partners with the opportunity to build campaigns that more accurately target customers with content built from data-driven insights.

New incentives:

• A fixed backend rebate for Elite-level Solution Provider and Solutions Integration partners for compute, compute DGX, visualization and virtualization.
• An enhanced quarterly performance bonus program, incorporating an annualized goal to better align with sudden fluctuations in partner selling seasons.
• Expanded AI Champions Club to honor top NVIDIA DGX systems sellers.
• Dedicated market development funds for Elite-level providers and integration partners for most competencies.

NPN expanded categories:

• Solution advisors focused on storage solutions and mutual reference architectures
• Federal government system integrators

The NVIDIA Partner Network is dedicated to supporting partners that deliver world-class products and services to customers. The NPN collaborates with hundreds of companies globally, across a range of businesses and competencies, to serve customers in HPC, AI and emerging high-growth areas such as visualization, edge computing and virtualization.

Learn how to become a partner in the NPN.

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Teen’s Gambit: 15-Year-Old Chess Master Puts Blundering Laptop in Check with Jetson Platform

Only 846 people in the world hold the title of Woman International Master of chess. Evelyn Zhu, age 15, is one of them.

A rising high school junior in Long Island, outside New York City, Zhu began playing chess competitively at the age of seven and has worked her way up to being one of the top players of her age.

Before COVID-19 limited in-person gatherings, Zhu typically spent two to three hours a day practicing online for an upcoming tournament — if only her laptop could keep up.

Chess engines like Leela Chess Zero — Zhu’s go-to practice partner, which recently beat all others at the 17th season of the Top Chess Engine Championship — use artificial neural network algorithms to mimic the human brain and make moves.

It takes a lot of processing power to take full advantage of such algorithms, so Zhu’s two-year-old laptop would often crash from overheating.

Zhu turned to the NVIDIA Jetson Xavier NX module to solve the issue. She connected the module to her laptop with a MicroUSB-to-USB cable and launched the engine on it. The engine ran smoothly. She also noted that doing the same with the NVIDIA Jetson AGX Xavier module doubled the speed at which the engine analyzed chess positions.

This solution is game-changing, said Zhu, as running Leela Chess Zero on her laptop allows her to improve her skills even while on the go.

AI-based chess engines allow players like Zhu to perform opening preparation, the process of figuring out new lines of moves to be made during the beginning stage of the game. Engines also help with game analysis, as they point out subtle mistakes that a player makes during gameplay.

Opening New Moves Between Chess and Computer Science

“My favorite thing about chess is the peace that comes from being deep in your thoughts when playing or studying a game,” said Zhu. “And getting to meet friends at various tournaments.”

One of her favorite memories is from the 2020 U.S. Team East Tournament, the last she competed at before the COVID-19 outbreak. Instead of the usual competition where one wins or loses as an individual, this was a tournament where players scored points for their teams by winning individual matches.

Zhu’s squad, comprising three other girls around her age, placed second out of 318 teams of all ages.

“Nobody expected that, especially because we were a young all-girls team,” she said. “It was so memorable.”

Besides chess, Zhu has a passion for computer science and hopes to study it in college.

“What excites me most about CS is that it’s so futuristic,” she said. “It seems like we’re making progress in AI on a daily basis, and I really think that it’s the route to advancing society.”

Working with the Jetson platform has opened up a pathway for Zhu to combine her passions for chess and AI. After she posted online instructions on how she supercharged her crashing laptop with NVIDIA technology, Zhu heard from people all around the world.

Her post even sparked discussion of chess in the context of AI, she said, showing her that there’s a global community interested in the topic.

Find out more about Zhu’s chess and tech endeavors.

Learn more about the Jetson platform.

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