Nvidia’s keynote at the GTC brought some surprises | Top Vip News

SAN JOSE – “I hope you realize this is not a concert,” Nvidia President Jensen Huang said to an audience so large it filled the SAP Center in San Jose. So he presented what is perhaps the complete opposite of a concert: the company’s GTC event. “You’ve arrived at a developer conference. There will be a lot of science describing algorithms, computer architecture and mathematics. I feel a very heavy weight in the room; “Suddenly, you’re in the wrong place.”

It may not have been a rock concert, but the 61-year-old CEO who wore a leather jacket the third most valuable company in the world by market cap it certainly had a good number of fans among the audience. The company was founded in 1993 with the mission of taking general computing beyond its limits. “Accelerated computing” became Nvidia’s motto: wouldn’t it be great to make specialized chips and boards, rather than general-purpose ones? Nvidia chips give graphics-hungry gamers the tools they need to play at higher resolution, with higher quality and higher frame rates.

Perhaps it’s not a big surprise that the Nvidia CEO drew parallels with a concert. The place was, in a word, very concert-like. Image credits: TechCrunch / Haje Kamps

Monday’s keynote was, in some ways, a return to the company’s original mission. “I want to show you the soul of Nvidia, the soul of our company, at the intersection of computer graphics, physics and artificial intelligence, all intertwined inside a computer.”

Then, for the next two hours, Huang did something strange: he got nerdy. Hard. Anyone who had come to the keynote expecting him to do a Tim Cook, with a slick, audience-focused speech, would surely be disappointed. Overall, the keynote was tech-heavy, acronym-ridden, and unapologetically a developer conference.

We need bigger GPUs

Graphics processing units (GPUs) are where Nvidia started. If you’ve ever built a computer, you’re probably thinking about a graphics card that goes in a PCI slot. That’s where the journey began, but since then we’ve come a long way.

The company announced its new Blackwell platform, which is an absolute monster. Huang says the processor core was “pushing the limits of physics on how big a chip could be.” It uses combines the power of two chips, offering speeds of 10 Tbps.

“I have about $10 billion worth of equipment here,” Huang said, holding up a Blackwell prototype. “The next one will cost $5 billion. Luckily for all of you, it gets cheaper from there.” Putting a bunch of these chips together can generate some truly impressive power.

The previous generation of AI-optimized GPUs was called Hopper. Blackwell is between 2 and 30 times faster, depending on how you measure it. Huang explained that it took 8,000 GPUs, 15 megawatts, and 90 days to create the GPT-MoE-1.8T model. With the new system, you could use only 2000 GPUs and use 25% of the power.

These GPUs are generating a fantastic amount of data, which is a very good segue into another topic that Huang talked about.

Whats Next

Nvidia launched a new set of tools for automakers working on autonomous vehicles. The company was already a major player in robotics, but it doubled down with new tools for roboticists to make their robots smarter.

The company also introduced Nvidia NIM, a software platform aimed at simplifying the deployment of AI models. NIM leverages Nvidia hardware as a foundation and aims to accelerate enterprises’ AI initiatives by providing an ecosystem of AI-ready containers. It supports models from a variety of sources, including Nvidia, Google, and Hugging Face, and integrates with platforms such as Amazon SageMaker and Microsoft Azure AI. NIM will expand its capabilities over time, including tools for generative AI chatbots.

“Anything that can be digitized: As long as there is some structure that we can apply some patterns to, it means we can learn the patterns,” Huang said. “And if we can learn the patterns, we can understand the meaning. When we understand meaning, we can also generate it. And here we are, in the generative AI revolution.”