Nvidia CEO Jensen Huang weighs in on the metaverse, blockchain, and chip shortage

Elevate your enterprise data technology and strategy at Transform 2021.

Conversations with Nvidia CEO Jensen Huang are always blunt and illuminating because he still likes to have freewheeling chats with the press. During the recent online-only Computex event, he held an briefing with the press where he talked about the company’s recent announcements and then took a lot of questions.

I asked him about the metaverse, the universe of virtual worlds that are all interconnected, like in novels such as Snow Crash and Ready Player One. And he gave a detailed answer. Huang addressed a wide range of issues. He talked about Nvidia’s pending bid to buy Arm for $40 billion, as well as Nvidia’s effort to create Grace, an Arm-based CPU.

He also addressed progress on Nvidia’s own Omniverse, dubbed a “metaverse for engineers.” Huang talked about Nvidia’s presence in the Chinese market, the company’s efforts to discourage miners from buying all of its GPUs, Nvidia’s data processing units (DPUs), and Moore’s Law’s future and building fabs, competition from Advanced Micro Devices in graphics processing units (GPUs), and Nvidia’s reaction to the global semiconductor shortage.

I was part of a group of journalists who quizzed Huang. Here’s an edited transcript of the group interview.

Nvidia GeForce RTX 3080 Ti.

Above: Nvidia GeForce RTX 3080 Ti is its new card.

Image Credit: GamesBeat

Jensen Huang: Today I’m coming to you from Nvidia’s new building, called Voyager. This is our new facility. It was started about 2-and-a-half years ago. For the last year-and-a-half, I’ve not seen it. Today’s my first day on campus. Literally, for our event today, this is my first day on campus. It’s beautiful here. This facility is going to be the home of 3,500 Nvidians. It’s designed as a city inside a building. If you look behind me, it’s a sprawling city, and it’s a very large open space. It’s largely naturally lit. In fact, right now, as we speak, there’s a light in front of me, but everything behind us is barely lit. The reason for that is because there are all these panels in the sky that let light in.

We simulated this entire building using raytracing on our supercomputer DGX. The reason we did that is so we can balance the amount of light that comes in and the amount of energy, or otherwise heat, that we have to remove with air conditioning. The more light you bring in, the more AC you have to use. The less light you bring in, the more lighting you have to use. We have to simulate that fine balance.

The roof of this building is angled in just the right way such that the morning sun doesn’t come straight in, and the afternoon sun doesn’t come straight in. The slope of the roof line, the slope of the windows along the side, you’ll see everything was designed in such a way as to balance between natural light, which is comfortable for the eyes, and not having to use as much air conditioning as otherwise necessary. At the moment, no AC at all. This is the first day we’ve been in here. It’s incredibly comfortable.

Using a supercomputer to simulate architecture, I think this is going to happen for all buildings in the future. You’re going to design a building completely in virtual reality. The building is also designed to accommodate many robots. You’ll notice the hallways are very wide. In the future we imagine robots roaming the hallways carrying things to people, but also for telepresence, virtual presence. You can upload yourself into a robot and sit at your desk in your VR or AR headset and roam around the campus.

You’re the first in the world to be here. Welcome all of you, and I thank you for joining me today. I also want to send my thoughts and recognize that in Taiwan, COVID cases are growing again. I’m very sorry about that. I hope all of you are safe. I know that Taiwan was so rigorous in keeping the infection rates down, and so I’m terribly sorry to see it go up now. I know they can get it under control, and soon all of us will be able to see each other in person.

GeForce ecosystem

Let me say a couple of words about the announcement. We announced two basic things. In GeForce gaming, where Taiwan is the central hub of where our add-in card partners and many of our leading laptop partners are based, and the home of, the epicenter if you will, the GeForce ecosystem. It all starts there. It’s manufactured and assembled and integrated and it goes to the market through our add-in card partners and laptop builders.

Nvidia's RTX is used in more than 130 games.

Above: Nvidia’s RTX is used in more than 130 games.

Image Credit: Nvidia

The GeForce business is doing incredibly well. The invention of RTX has been a home run. It has reset and redefined computer graphics, completely reinvented modern computer graphics. It’s a journey that started more than 10 years ago, and a dream that started 35 years ago. It took that long for us to invent the possibility of doing realtime raytracing, which is really hard to do. It wasn’t until we were able to fuse our hardware accelerated raytracing core with the Tensor core GPU, AI processing, and a bunch of new rendering algorithms, that we were able to bring realtime raytracing to reality. RTX has reinvented computer graphics in the marketplace. RTX 30, the 30 family, the Ampere architecture family, has been fantastic.

We announced several things. We announced that we upgraded the RTX 30 family with the 3080Ti and the 3070Ti. It’s our regularly planned once per year upgrade to our high end GPUs. We also, with the partnership with all of our laptop partners, our AICs, launched 140 different laptops. Our laptop business is one of the fastest growing businesses in our company. This year we have twice as many notebooks going into the marketplace as we did with Turing, our last generation, RTX 20. This is one of the fastest growing businesses. The laptop business is the fastest growing segment of PCs. Nvidia laptops are growing at seven times the rate of the overall laptop business. It gives a sense of how fast RTX laptops are growing.

If you think about RTX laptops as a game console, it’s the largest game console in the world. There are more RTX laptops shipped each year than game consoles. If you were to compare the performance of a game console to an RTX, even an RTX 3060 would be 30-50 percent faster than a PlayStation 5. We have a game console, literally, in this little thin notebook, which is one of the reasons it’s selling so well. The same laptop also brings with it all of the software stacks and rendering stacks necessary for design applications, like Adobe and AutoDesk and all of these wonderful design and creative tools. The RTX laptop, RTX 3080Ti, RTX 3070Ti, and a whole bunch of new games, that was one major announcement.

Nvidia in the enterprise

The second thrust is enterprise, data centers. As you know, AI is software that can write software. Using machines you can write software that no human possibly can. It can learn from an enormous amount of data using an algorithm in an approach called deep learning. Deep learning isn’t just one algorithm. Deep learning is a whole bunch of algorithms. Some for image recognition, some for recognizing 2D to 3D, some for recognizing sequences, some for reinforcement learning in robotics. There’s a whole bunch of different algorithms that are associated with deep learning. But there’s no question that we can now write software that we’ve not been able to write before. We can automate a bunch of things that we never thought would be possible in our generation.

One of the most important things is natural language understanding. It’s now so good that you can summarize an entire chapter of a book, or the whole book. Pretty soon you can summarize a movie. Watch the movie, listen to the words, and summarize it in a wonderful way. You can have questions and answers with an NLU model.

AI has made tremendous breakthroughs, but has largely been used by the internet companies, the cloud service providers and internet services. What we announced at GTC initially a few weeks ago, and then what we announced at Computex, is a brand new platform that’s called Nvidia Certified AI for Enterprise. Nvidia Certified systems running a software stack we call Nvidia AI Enterprise. The software stack makes it possible to achieve world class capabilities in AI with a bunch of tools and pre-trained AI models. A pre-trained AI model is like a new college grad. They got a bunch of education. They’re trained. But you have to adapt them into your job and to your profession, your industry. But they’re pre-trained and really smart. They’re smart at image recognition, at language understanding, and so on.

We have this Nvidia AI Enterprise that sits on top of a body of work that we collaborated on with VMware. That sits on top of Nvidia Certified servers from the world’s leading computer makers, many of them in Taiwan, all over the world, and these are high-volume servers that incorporate our Ampere generation data center GPUs and our Mellanox BlueField DPUs. This whole stack gives you a cloud native–it’s like having an AI cloud, but it’s in your company. It comes…

Read More: Nvidia CEO Jensen Huang weighs in on the metaverse, blockchain, and chip shortage

Notify of
Inline Feedbacks
View all comments

Get more stuff like this
in your inbox

Subscribe to our mailing list and get interesting stuff and updates to your email inbox.

Thank you for subscribing.

Something went wrong.