The Best of 2024 with Sarah Guo and Elad Gil
episode
No Priors: Artificial Intelligence | Technology | Startups
27 min
4 speakers
8 chapters
transcribed 1 month ago
Transcript
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Transcript generated automatically by AI and may contain errors.
How is NVIDIA redefining AI by building entire data‑center ecosystems?
Hi no priors listeners. I hope it's been an amazing 2024 for you all. Looking back on this year, we wanted to bring you highlights from some of our favorite conversations. First up, we have a clip with the one and only Jensen Huang, CEO of NVIDIA, the company powering the AI revolution.
What does Andrej Karpathy say about the shift to smaller AI models and the AI exo‑cortex?
Since our 2023 No Priors chat with Jensen, NVIDIA's tripled in stock price, adding almost 100 billion of value each month of 2024 and entering the $3 trillion club. More recently, Jensen shared his perspective again with us, this time on why NVIDIA is no longer a chip company, but a data center ecosystem. Here's our conversation with Jensen.
Why does Bret Taylor believe company agents will replace traditional websites?
NVIDIA has moved into larger and larger, let's say, like unit of support for customers. I think about it going from single chip to, you know, server to rack and VL seventy two. How do you think about that progression? Like what what's next?
How is OpenAI’s Sora team using video models to move toward AGI?
Like should NVIDIA do full data center?
Uh, in fact we built full data centers. The way that we build everything, unless you're building If you're developing software, you need the computer in its full manifestation.
What are the biggest challenges Waymo faces in achieving 100 % autonomous driving?
Um we don't we don't build PowerPoint slides and ship the chips. And we build a whole data center. And until we get the whole data center built up, how do you know the software works? Until you get the whole data center built up, how do you know you're, you know?
How does Dylan Field envision the future of user interfaces and multimodal AI?
your fabric works and all the things that you expect it the efficiencies to be, how do you know it's going to really work at the scale? And and that's the reason why that's the reason why it's not unusual to see somebody's actual performance be dramatically lower than their peak performance as shown in PowerPoint slides. And and and it's
What is Scale AI’s roadmap for data flywheels that could enable AGI?
Computing is just not used to it's not what it used to be. You know, I say that the new unit of computing is the data center. That's to us.
What key takeaways wrap up the best moments of 2024 on No Priors?
So that's what you have to deliver. That's what we build. Now we build a whole thing like that. And then we for every single thing that every combination, uh air cooled, x86, liquid cooled, grace, Ethernet, InfiniBand, MV Link, no MV Link, you know what I'm saying? We build every single configuration. We have five supercomputers in our company today. Next year we're going to build easily five more. So if you're serious about software, you build your own computers. If you're serious about software, then you're going to build your whole computer and we build it all at scale. This is the part that that is really interesting. We build it at scale and we build it very vertically integrated. We optimize it full stack.
And then and then we disaggregate everything. And we sell it in parts. That's the part that is completely utterly remarkable about what we do. The complexity of of that is just insane. And the reason for that is we want to be able to graft our infrastructure into GCP, AWS, Azure, OCI. All of their control planes, security planes are all different. And all of the way they think about their cluster sizing, all different. And um uh but yet we make it possible for them to all accommodate NVIDIA's architecture so that CUDA could be everywhere. That's really, really in the end, the the singular thought, you know, that we would like to have a computing platform that developers could use that's largely consistent.
Modulo, you know, 10% here and there because people's infrastructure are slightly optimized differently. And modulo 10% here and there, but but everything they they build This is kind of the one of the principles of software that it should never be given up. And it and and we we we protect it quite dearly. It makes it possible for our software engineers to build once run everywhere. And and that's because we recognize uh that the investment of software is the most expensive investment. And it's easy to test. Uh look at the size of the whole hardware industry. And then look at the size of the world's industries. It's a hundred trillion dollars on top of this one trillion dollar industry. And that tells you something.
The software that you build, you have to You know, you basically maintain for as long as you shall live.
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Chapters
8 chapters
1
How is NVIDIA redefining AI by building entire data‑center ecosystems?
0:05–0:21
2
What does Andrej Karpathy say about the shift to smaller AI models and the AI exo‑cortex?
0:21–0:40
3
Why does Bret Taylor believe company agents will replace traditional websites?
0:40–0:54
4
How is OpenAI’s Sora team using video models to move toward AGI?
0:54–1:07
5
What are the biggest challenges Waymo faces in achieving 100 % autonomous driving?
1:07–1:23
6
How does Dylan Field envision the future of user interfaces and multimodal AI?
1:23–1:47
7
What is Scale AI’s roadmap for data flywheels that could enable AGI?
1:47–1:54
8
What key takeaways wrap up the best moments of 2024 on No Priors?
1:54–27:03
Speakers
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