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.
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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