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 6 resolved? a statement only gets an assessment when the public record can support or contradict it. opinions and what-ifs never can, and 0 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
Gerstner: The US should sell AI chips to China to protect the CUDA ecosystem
“Are we better off selling to those countries, those companies, keeping companies like ByteDance and Tencent, et cetera, in the CUDA ecosystem, rather than allowing all of that data, all of those profits to flow right into the Huawei ecosystem and benefit the C…”
Madra: NVIDIA's CUDA moat does not exist for inference workloads
“There is no
Tie into CUDA that's required to go faster.
That's required to get the models running, right?
Obviously none of the three companies run CUDA.
And so that moat doesn't exist around inference.”
Gurley: DeepSeek bypassed Nvidia's CUDA framework for low-level optimization
“One, it's validated now that they went around CUDA, and I just think that's interesting.”
Madra: Fewer developers will touch CUDA long-term, weakening NVIDIA's software moat
“I think there's going to be fewer people touching that. And I do think that's a point where they're the moat is not as strong as a longer term, as you say, and think about like, you know, the way the analogy that I would go with is like, think about the number…”
Gurley: NVIDIA's competitive advantage is strongest at massive system scale
“NVIDIA's competitive advantage is strongest where the size of the system is largest, which is another way of saying what Renee said. It's flipping it on its head. It's not to say it's weak on the edge, but it's super powerful when you put a whole bunch of them…”
Gerstner: NVIDIA's CUDA library has over 300 industry-specific acceleration algorithms
“The CUDA library now has over 300 industry specific acceleration algorithms, right? Where they deeply learn the industry, right? So whether this is synthetic biology or this is image generation, or this is autonomous driving, they learn the needs of that indus…”