Dwarkesh Podcast / episode intelligence
Speakers in the public record
Claim mix
Evidence policy
Every row below preserves an exact excerpt. Identified speakers are linked; unresolved voices are labeled and excluded from people counts.
Claim ledger
17 published records
01 / observation
“We’ve seen the valuations of a bunch of software companies crash because people are expecting AI to commoditize software.”
02 / evaluation
“With post-training and reinforcement learning, that entire area is just exploding. So if you want to build on an architecture, building on CUDA makes the most sense because you know the ecosystem is great.”
03 / commitment
“Your argument starts from extremes. That if we give them any compute at all in this narrow moment, we will lose everything.”
04 / belief
“Listen, I just think you speak in absolutes. I think the United States ought to be ahead.”
05 / belief
“I think in your latest filings, you had almost a $100 billion in purchase commitments with foundries, memory, and packaging.”
06 / belief
“I would say my mistake is I didn’t deeply internalize that they really had no other options, that a VC would never put in $5-10 billion of investment into an AI lab with the hopes of it turning out to be Anthropic.”
07 / belief
“I think the concern, going back to the flop difference in the hacking, is yes, they have compute, but there’s some estimates that because they’re at 7nm—they don’t have EUVs because of chip-making export controls—the amount of flops they’re able to actually produce, they have one tenth the amount of flops that the US has.”
08 / evaluation
“But I think having a dialogue and having research dialogue is probably the safest thing to do. This is an area that is glaringly missing because of our current attitude about China as an adversary.”
09 / preference
“Because the customers make so much money—for example, our software engineers—if I can give them much more responsive tokens so that they’re even more productive than they are today, I would pay for it.”
10 / recommendation
“If you want to operate it for yourself, we obviously have the ability to help you operate it yourself, like we did for Elon with xAI. And because we can enable operators in any company and any industry, you could use it to build a supercomputer for scientific research and drug discovery at Lilly.”
11 / commitment
“We’re developing all kinds of new techniques so that we drive efficiency in addition to increasing capacity.”
12 / prediction
“The only way to really get 10x or 100x leaps is to fundamentally change the algorithm and how it’s computed every single year.”
13 / evaluation
“For example, the United States is scarce on energy, which is the reason why Nvidia has to keep advancing our architecture and do this extreme co-design so that with the few chips that we ship—with the few chips, because the amount of energy is so limited—our throughput per watt is off the charts.”
14 / commitment
“You can count on us. I prefer to be dependable, to be the foundation of the industry.”
15 / preference
“I actually don’t know what I think about whether it’s good to sell chips to China or not, but I like to play devil’s advocate against my guests.”
16 / prediction
“That’s fantastic. But in a few years time, I’m making you the prediction that when we want the American tech stack, when we want American technology to be diffused around the world—out to India, out to the Middle East, out to Africa, out to Southeast Asia—when our country would like to export, because we would like to export our technology, we would like to export our standards, on that day, I want you and I to have that same conversation again.”
17 / evaluation
“On first principles, it makes no sense. So I think the reason why we’re so successful is simply because our TCO is so great.”