“The estimate for doing that migration for Google was seven staffed millennia.”
quote is from the automated transcript, cleaned for reading:
filler sounds and stutters are removed, nothing is rephrased. names can be misheard
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More from Amin Vahdat
AssertionNot checkable as stated
Vahdat: AI infrastructure build-out is 100x larger than 1990s internet boom
“The internet in the late nineties, early 2000 was big, and we felt like, oh my gosh, can't believe the Build out the rate. This makes it, I mean, 10 X is an understatement. It's a hundred X what the internet was.”
Amin VahdatOct 29, 2025▶ 0:24Building the Real-World Infrastructure for AI, with Google, Cisco & a16z
PredictionNot checkable as stated
Vahdat: AI infrastructure deployment bottlenecks will persist for 3 to 5 years
“Like, in other words, literally, you all have some money, you can't spend it all as fast as you want. I think that's going to extend for three, four, five years.”
Amin VahdatOct 29, 2025▶ 5:22Building the Real-World Infrastructure for AI, with Google, Cisco & a16z
PredictionNot checkable as stated
Vahdat: AI hardware supply will lag behind demand in short term
“So one worry I have is that the supply isn't actually going to catch up to the demand as quickly as we'd all like.”
Amin VahdatOct 29, 2025▶ 5:03Building the Real-World Infrastructure for AI, with Google, Cisco & a16z
AssertionSupported
Vahdat: Google TPUs are 10x to 100x more energy efficient than CPUs
“TPU, I'll use that example again because I know it best for certain computation, is somewhere between 10 and a hundred times more efficient per watt, and it's this watt that really matters than a CPU.”
Amin VahdatOct 29, 2025▶ 12:52Building the Real-World Infrastructure for AI, with Google, Cisco & a16z
AssertionNot checkable as stated
Vahdat: Bringing a specialized chip to production takes at least 2.5 years
“For the best teams in the world, really from concept to in live in production, the speed of light is two and a half years.”
Amin VahdatOct 29, 2025▶ 13:35Building the Real-World Infrastructure for AI, with Google, Cisco & a16z
AssertionSupported
Vahdat: Gigawatt-scale AI workloads create power fluctuations visible to utilities
“We've written about this power utilities notice when we're doing network communication relative to computation at the scale of 1000 of megawatts. Right, like massive demand for power, stop all of a sudden and do some network communication, and then burst back …”
Amin VahdatOct 29, 2025▶ 17:16Building the Real-World Infrastructure for AI, with Google, Cisco & a16z
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