Who is on this subjectordered by the date of their first quote here
6 of 7 lanes rest on fewer than 5 quotes and are marked thin. Offsets are days from the middle first-quote date, 22 May 2025 — a date, and nothing else. It is not a claim about who reached a view first.
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Brad Gerstner
8
28 Sep 2023 – 20 Jun 2025
-602 d
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Howard Marks
4
thin
21 Feb 2024 – 21 Feb 2026
-456 d
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Marc Rowan
3
thin
5 May 2025 – 10 Dec 2025
-17 d
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David Friedberg
1
thin
22 May 2025 – 22 May 2025
+0 d
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Bill Gurley
1
thin
20 Jun 2025 – 20 Jun 2025
+29 d
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Chamath Palihapitiya
3
thin
10 Oct 2025 – 11 Jul 2026
+141 d
- Dylan Patel 1 thin 22 Jul 2026 – 22 Jul 2026 +426 d
The chronologysourced and dated, oldest first
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Brad Gerstner
Gerstner cites Kashkari's June 2021 forecast of no rate hikes until 2024 as evidence of Fed miscalculation.
“He says we're not gonna have rate hikes until 2024. That's how wrong the Fed's forecast was in June 2021 because they were making the argument that inflation was transient.”
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Brad Gerstner
Gerstner recalls NVIDIA data center revenue forecasts shifted from -6% to +25% last year.
“Think about NVIDIA at the start of last year. Data center revenues were expected to shrink by 6%. Right?”
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Brad Gerstner
Gerstner highlights NVIDIA data center grew over 25% versus consensus forecast of minus 6%.
“Data center revenues were expected to shrink by 6%. Right? We thought we we had huge variant perception by being up 16%, and it ended up over 25%.”
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Brad Gerstner
Gerstner says Altimeter's NVIDIA numbers remain well above Street consensus for this year.
“Our numbers are still well above the street for this year. I think there's a lot of doubt. You know, the the common, discussion at the end of last year”
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Brad Gerstner
Gerstner cites Morgan Stanley research showing super cycles are systematically underestimated by about 40% at their start.
“When I think about what's going on here of course they show they went back and did some math against initial estimates and said, you know, super cycles are about 40% underestimated at the start.”
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Howard Marks
Marks criticizes daily market commentary writers who predict the future and are only right half the time on average.
“And if if they ever kept a scorecard on the things that they wrote about what's gonna happen tomorrow, they would see that on average they get it right half the time”
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Brad Gerstner
Gerstner notes NVIDIA consensus data center revenue estimate was $22B but actual came in at $96B.
“at the start of last year, the consensus estimate of the smartest people covering NVIDIA day to day was that the data center revenue was going to be 22,000,000,000 for the year.”
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Brad Gerstner
Gerstner says NVIDIA EPS was forecast at $5.70 but ended up at $25, far exceeding expectations.
“The EPS at the beginning of last year, the earnings per share was expected to be $5.70, and now it looks like it's gonna be $25.”
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Marc Rowan
Rowan predicts two quarters of negative growth if tariff uncertainty is not resolved.
“They do not hire. They do not make moves. We likely will cause two quarters of negative growth if we, in fact, don't resolve the uncertainty.”
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“I can design a project plan to get me to the moon in five years for less than a billion dollars.”
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Bill Gurley
Gurley discusses slide comparing AI trajectory to reach 75% of total US market cap against historical industrial and transport precedents.
“when will AI reach 75% of total US market cap, which I think is incredibly provocative how you compare that to industrials and transport because everybody's saying it's so big already it can't get any bigger.”
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Brad Gerstner
Gerstner notes 1990s experts wrongly predicted debt-to-GDP would rise to 80%; instead it fell from 60 to 40.
“in 1993, debt to GDP was supposed to go from 40 to or 60 to 80 by experts, it in fact went from 60 to 40. Yes. So experts can be wrong by a lot.”
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Howard Marks
Marks cites JPMorgan chart showing negative correlation between S&P 500 PE ratios and subsequent ten-year returns.
“And it was a negative correlation, which means the higher the PE ratio you pay, the lower the return you should expect.”
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Chamath Palihapitiya
Palihapitiya predicts nuclear, natural gas, and solar will create electron abundance that diminishes oil demand within ten to twenty years.
“In the meantime, you have an abundance of electrons from nat gas. You have an abundance of electrons, frankly, from solar. And all of these things will ultimately diminish the net long bid to oil.”
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Marc Rowan
Rowan says consulting firms' 2030 energy projections are wildly inconsistent, showing experts have no clear view on data center future.
“I have a chart on the wall in my office, which is just about energy usage in the year 2030, not that far away.”
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Marc Rowan
Rowan says consulting firms' 2030 energy forecasts are wildly inconsistent, resembling a scattered plot.
“And each of the good and the great consulting firms have weighed in, and it looks like a child scattered dark plot.”
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Howard Marks
Marks cites Dimson saying the future is a probability distribution, not a single outcome that can be predicted.
“The future is not a set single thing that if you're smart enough, you can figure it out what it's going to be and it's going to materialize and make you right.”
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Howard Marks
Marks argues the future is a probability distribution of possibilities, not a single predictable outcome.
“It's a probability distribution. It's a range of possibilities in each thing, whether it's GDP growth next year or inflation next year, or who's going to win the next election,”
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Chamath Palihapitiya
Palihapitiya cites Verizon CEO's forecast that 30% of white collar jobs will disappear by 2030.
“He put out this very public forecast. You know, very smart guy, well regarded in business. And I think he said something like 30% of all white collar jobs will be gone by 2030.”
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Chamath Palihapitiya
Palihapitiya's analysis shows U.S. faces energy shortage equivalent to three Californias by 2050 from expected load growth.
“If you just look at the load growth that's expected between now and 2050, we are about three entire California's worth of energy short.”
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Dylan Patel
Patel claims AI task length is doubling every seven months, leaving no time for companies to wait.
“AI task length, right? The amount of time that an AI model can work on any specific job is increasing by 2x every seven months.”
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Where they overlapsame programme, same subject
- Bill Gurley and Brad Gerstner — BG2 Pod, 1 appearance together