The Ledger
Every statement that passed quotation and attribution checks. Mix any filter with any other: certainty 1/5, debate potential 5/5, or both at once.
why aren't all 63 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 1 checkable ones are still open, waiting for their date. predictions held up or didn't; assertions are supported or contradicted. on every card: ▮▮▮▮▮ certainty · ▮▮▮▮▮ debate potential. speakers are clickable
Huang: NVIDIA plans to build at least five more supercomputers in 2025
“Next year, we're going to build easily five more.”
Davis: NVIDIA's Mellanox buyout is among the best acquisitions in history
“And their acquisition of Mellanox was one of the better of all time, arguably, from a market cap creation perspective.”
Srivastava: Securing H100s still requires weeks of provider negotiations and escalations
“I think customers are still struggling with availability for the most premium chips. And I think, you know, whether that's eight, 108, 100, I think even when there is availability, you're oftentimes looking for like three to six weeks of negotiating with cloud…”
Gil: Advanced semiconductor markets historically produce only one leader and one runner-up
“If you look at many of the most advanced chip markets, historically at least, there's tended to be a leader, and then there's been, there's tended to be a second place party, and that was
You know, during the microprocessor world, that was Intel, and then AMD …”
Guo: Has not yet found a compelling AI chip startup to fund
“I would love to meet companies in this area and still haven't, haven't seen something that's gotten me over the edge, even in a place that it's so
Obviously, economically fertile.”
Henry: Nvidia will lose AI chip monopoly as a number two emerges
“I obviously NVIDIA is selling the most GPUs. That's fun. Yeah. That's driving, you know, a lot of AI, but I think there's still room. I don't think it's going to be a monopoly on the area. And you know, I do think there will be a clear number two. And right no…”
Biewald: Nvidia Chips Forced ML Researchers To Become Software Developers
“When NVIDIA came along and these chips worked for deep learning, it just, like, broke the entire stack. Like, it was, like, a first time in my career where I'm, like, running into, like, linker errors. I'm like, what the fuck is a linker error? Like, I vaguely…”
Huang: Geoffrey Hinton's lab first trained deep neural networks on GeForce gaming cards
“The first GPU that Jeff Hinton got for his lab, you know Hila would tell you that, that Jeff came in and said, here's a couple of GPUs, it's called GeForce, and you guys should try to use that for DNN, and so it was a gaming card.”
Huang: NVIDIA maintains only one instruction set and computer architecture
“We have one instruction set. We have one computer architecture, and we're super disciplined about that.”
Huang: Andrew Ng contacted NVIDIA around 2012 to train neural nets on GPUs
“Around 20 12, I guess, and it was because simultaneously Andrew Eng reached out to Bill Daly, our chief scientist to work on a way to get the neural network model that they were working on onto GPU so that they could, instead of using thousands of CPU servers,…”
Huang: NVIDIA Bought Mellanox to Treat Data Center Networks as Compute Fabrics
“That, that's the reason why we bought Mellanox and started fusing InfiniBand and MVLink in such an aggressive way.”
Guo: Meta Added $197B in Largest Single-Session Gain Pre-NVIDIA
“They had this one day ad of a hundred and ninety seven billion of market cap. Biggest single session ad before NVIDIA.”
Huang: NVIDIA Operates Two Parallel Systems for Long-Term Innovation and Perfect Execution
“Our company actually has two different ways of working. One of them is rather organic, shape-shifting all the time. If a particular investment is not working out, we give up on it, move the resources somewhere else. And so that's the agile part of the company.…”