Nvidia’s CEO Jen-Hsun Huang Keynote Speech at CES 2017
Titi Mary Tran/ Nguoi-Viet
Las Vegas, Nevada (NV) – The Chief Executive Officer and Co-founder of Nvidia Jen-Hsun Huang delivered an impressive keynote speech at the Consummer Technology Show (CES) 2017 at the Venetian Las Vegas on January 4th, 2017, focusing on the four fronts of technology today: Visual and Artificial Intelligence computing, games, virtual reality, and augmented reality (or mixed reality).
According to Gary Shapiro, the president of CTA (Consumer Technology Association), “Jen-Hsun Huang started Nvidia in 1993 as a personal computer graphic company. He wanted to create a PC gaming market that did not yet even exist. Now, gaming is the largest entertainment industry in the world. Nvidia’s invention of GPU in 1999 defined modern computer graphics. Later it brought the power of parallel computing to science’s grand challenges. The Nvidia’s CPU is conjuring up the amazing world of Hollywood films and accelerating the cancer moon-shoot research initiative. It is the brain solving the most complex problems in computer science. And today, Nvidia is at the center of greatest computing challenge of all time: Artificial Intelligence. Next year, Tesla cars will hit the road with fully autonomous capabilities powered by Nividia AI car computer. Now Jen-Hsun is recently ranked by Havard business review as one of the world top performance CEO, and Nvidia was last year top top number one performance company in the S&P 500 with the share price of more than tripling. He visited the CTA headquarter in 2008 and he spoke to us staff at our staff meeting. He was also profiled that year on the cover story of the CTA I3 magazine. He is focus, engaging, and certainly visionary.”
Dressed in black leather jacket and jean, Jen-Hsun Huang came out the stage of around 3500 attendees. He started with a video highlighting his company Nvidia and said, “We are going through unquestionably the most exciting time in the computer industry that all of us had ever witnessed. What we thought were going to be science fiction for years to come is becoming reality as we speak.”
Spearheading Nvidia toward technology innovation and advancement, Huang continued, “Our work at Nvidia dedicated toward computing models focus on visual and Artificial Intelligence computing. It’s built on top of the GPU that we pioneered. This computing model is able to solve problems that normal computing is not able to solve and we dedicate ourselves to tackle the most challenging computing problems in the world. There are four areas that we focus on. Surprisingly for many, over the year we dedicate ourselves to video games, not the mention the fact that it’s credibly fun, it’s credibly beautiful, and we love it. Video games is also the highest volume, most computationally intensive application the world has ever known. It is about achieving virtual reality, and now, all of the sudden, all of technologies are coming together for us to finally achieve virtual reality, augmented reality, mixed reality, and bring together the experiences of the Holographs for real for the first time.
Computer graphic technology, computer vision technology and artificial intelligence will come together to realize this exciting new computing platforms that we call VR, AR, or mixed reality. Our technology is also used in cloud. AI super computers are being built all over the world today so that all of you when you talking to the internet, you’re making queries, those searches are passed through artificial intelligence, so that the query that you made the assistance that you seek for is much more helpful to you, and lastly, some of the most exciting things we are working toward today, the most impactful work that we’re doing for society, for the industry: self-driving cars and autonomous vehicles.
These four areas we have been deepen for sometime, and all of the sudden, in the last several years, an enormous breakthrough happened. Researchers all around the world are working on a new field, a new technique of machine learning called deep learning, met the GPU, and the big bang of artificial intelligence happened. This technique allows software to write software, allow computers to learn from experience and data, and allow computers to recognize complex patterns that are easy for you and I, but incredibly hard for computers, and it does so by hierarchically building up feature representation to represent very complex information complex pattern, but building up from hierarchies of simpler patterns.
The ability to recognize a face for example with infinite variability, build on layers and layers and layers of artificial networks. The lowest layer can just be edges, edges made up by pixels, layer above that could be contours, shapes, textures, motifs, the layer above that could be parts of human face and eventually it will be able to understand the representation of face. And understand the reputation of a face in an incredible variability. You could be wearing your hair a little bit differently, you could be wearing a hat, you could be looking away partly, and somehow, somehow we human can recognize that person.
Finally for the very first time, using this technique of deep learning, we will be able to do the same with computers. This ability to perceive the word is just an enormous break through, and I will show you why, why this foundational technology and foundational capability was so important. It just had one incredible challenge, it has one incredible handicap, and that is the incredible amount of computation necessary, amount of computation necessary is absolutely enormous. And then one day, the AI researchers met the GPU that we invented. And the big bang of modern AI happened. The achievement has been fast and furious. Some of the things that we were able to accomplish in the last several absolutely mind blowing.
You have heard all about the alpha go achievement, demonstrate in deep mind team, has able to teach the computer how to play go, the most complex game we know how. More variability than all the atoms in the universe, more moves. And yet, this computer was able to learn go from the world masters and then played the masters of modern area and beat them. Networks have been able to play doom, which is a game of maze, maze findings, resources management while you stay away from monsters. A network was able to learn how to play go, a network has been able to learn the styles of artists, Van Gogh, Monet, Picasso, and apply that style to photographs. A network has been able to synthesize our voices instead of our voices stitched together from a whole bunch of little tiny chunks. This network has been able to learn the tonation of voices and from the words that we feed it, synthesize how we would speak. A network was able to learn to recognize an image and understand its context, and caption that image.
A network was able to turn images that it sees in computer cameras and translate directly through repeated trial and errors called enforcement learning to eventually adjust its motors and learn motor skills. A network was able to learn how to walk by itself, just by teaching the kinematic of the robot, a robot that was seating on the ground, after repeated trying, the robot was able to stand up and walk, and in fact we were able to a car how to drive, driving is a skill, its not mathematics, kids can learn how to drive, adults drive, and yet we do no computation whatsoever, we did no newtonion physics whatsoever, in our head, we just drive, we have been able to teach a car how to drive. The achievement that you see in front of you is impossible until just recently. It was impossible until recently, and all of a sudden we now been able to understand the complex nature of the world, to perceive the world through vision, through audial technology, through natural language.
We now able to apply artificial intelligence to solve problems that we had never conceived in the past. The enable behind all of these achievement is GPU computing, and that GPU has the benefit over 22 years to be fueled by the single largest simulation industry in the world, the largest entertainment industry in the world of video games. To many, it’s just for fun. To us, it’s incredibly fun, not to mention it propels the science of our company. PC gaming is thriving and vibrant. It has double in the last five years, to 31 billion dollars and it is the single largest platform today. GEforce is PC game. GEforce is also thriving vibrantly. In the last 5 year, it has also double in revenue. 200 millions GEforce game in the world. The dynamics that are driving this business is multi-dimensional. Of course, it is a global industry, and before anyone has a game consul, or even get a few consul, everyone has a PC, and almost every single human today is a gamer. There are several hundred million gamers today, and I expect to be several billions gamers someday. Our technology is also fueled, and this market is also fueled by the amazing production values of video games that continues to come out. In the last five years, gaming technology has increased its forment by a factor of 10. And now 4K, HDR, and virtual reality is coming. Gaming is no longer just about game. Gaming is now the world largest sporting event. In fact, it is very verbally likely that Eastward? will someday be the larger than all of the sport events combined. Eastward, 100 millions video games. When you watch them play video games, it’s a game of intelligence, it’s a game of tactic and strategy, it’s a game of team work, and it’s also a game of incredible hand-eye coordination. The trading is intense. The number of people who enjoyed it 325 millions spectator for each sport are now part of this every young sport.
Not only gaming is a game, a sport, it is now also social. There are more people than ever that watch video game, watch other people play video game. 600 millions video gamer viewers, 200 trillion minutes have been watched just in the last several years. This is now a 5 billion dollars advertising industry, one of the fastest growing area of internet videos that we know. PC gaming is thriving, GEforce is thriving, and all of that is propelling R&D budget that we’re able to support. “
At CES 2017 keynote, Jen-Hsun Huang announced that Nvidia will partner with Audi, ZF, Facebook, Amazon, Netflix, Google Play, Steam, and other game developers ( such as Aaryn Flynn of Mass Effect Andromeda to advance and implement to new technologies.
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