Chamath
Does his own confidence mean anything?
the same scored calls, split by how hard he was pushing at the mention that set his final stance. If credit rises with strength, his table-pounding carries information and you should weight it. If it's flat or inverted, his confidence is noise — treat a ×3 like a ×1. Cells under 5 calls are provisional and get no weight in the replay.
| he was | calls | credit | right/half/wrong | avg α | read |
|---|---|---|---|---|---|
| ×3 table-pounding | 166 | 0.43 | 56/30/80 | -21% | worse than coin flip |
| ×2 stated with reasoning | 263 | 0.46 | 102/40/121 | -12% | coin flip |
| ×1 offhand aside | 25 | 0.5 | 12/1/12 | +16% | coin flip |
Which kind of claim to trust
by the tier of the mention that set his final stance — a dated prediction is a different animal from a passing lean, and they don't have to score alike
| tier | calls | credit | right/half/wrong | avg α |
|---|---|---|---|---|
| annual_prediction | 2 | 0.5 prov. | 0/2/0 | +12% |
| explicit_prediction | 294 | 0.46 | 110/49/135 | -16% |
| positioning | 21 | 0.36 | 7/1/13 | -24% |
| sentiment | 137 | 0.46 | 53/19/65 | -7% |
What he's actually good at
his row of the scoreboard — these are the exact cells rescore.py uses to weight his mentions. w = clamp(2 × credit, 0.3, 1.5), applied only at n ≥ 5.
Live book — 42 positions
his latest stance on every ACTIVE idea. Expression = what he is effectively long or short: supporting a bearish idea is a SHORT, opposing one is a LONG.
Where his book points
net push per primary instrument across his live stances — conviction × his agreement × the idea's direction. This is his implied book, not a position he disclosed.
Best and worst calls
How he argues
Latest from him
I think the thing is we're in the early part of the euphoria ... I don't see this stopping. We're at the beginning of the beginning. I think it's going to be like this for another probably three years.
This Hugging Face thing will go down as one of the most important transactions in AI. Because you are creating now in the largest competitor and the largest most well-capitalized company a bulwark against all of this closed-source oligopoly insanity.
there's going to be a cascading set of decisions and reactions, and people will anchor into points of view on this topic and related topics around AI, which will look incredibly, incredibly dumb in six to nine months and a year from now ... That's my prediction.
these capabilities will be matched or close to matched by a handful of closed-source alternatives and open-source alternatives, probably within the next three or four months ... we are seeing the cost of that incremental unit of intelligence being driven further and further down
if these models can effectively code perfectly, then there is no exploit that it's not going to find. And we're on a shock clock to replace all the code that's been written in the last 50 or 60 years ... So for the next 10 years, we're going to have security issue after security issue.
I don't know, it was pretty obvious to me in May that Salesforce specifically was meaningfully oversold... the large systems of record, what I said before and what I'll double down on now is that those guys hold an incredibly special place in the ecosystem if they do it right... that's why his net dollar retention is strong, that's why his revenue is strong, that's why he's guiding up and that's why the stocks ripped, I think was like a 43% since I said it had bottomed.
I think the high end of the market where Mark operates, where the large monoliths operate is quite safe. What people are finding is, hey, hold on a second, this is a lot harder than we thought... I think we're a little oversold. Now, I think this consolidation and the rerating can happen in the opposite direction. So what is the opposite trade? The opposite trade is, who has constructive net dollar retention, who has negative churn that's been really predictable... Those guys, I think, are positioned to crush.
we are supposed to be in the middle of an enormous financial buildout to support AI... thank God, we have companies like Nvidia, and Google, and Microsoft, and Meta, and Amazon who take on that burden... there's so much chirping, by the way, on the internet about the balance sheet of Nvidia, and blah, blah, blah. And I think people completely missed that these guys are putting the entire US economy on their back.
you have the debt growing at 7% and you have GDP between 2 and 4%. So that's a recipe for disaster... if you see yields, if you see the 30, you're at 6 percent, it is the beginning of a death spiral. It's not going to be immediate. So don't freak out. But it is the beginning of some extreme pain, and that pain will last years.
That causes people to be less likely to invest in all the data centers. Data centers themselves are being shut down. Where does that leave frontier model companies? They're the most at risk. ... we are now in a very precarious situation that we could have frankly avoided.
wrap it in its own harness, it decays in capability. When you take an open source model and you use any other open source model, it improves ... there are all kinds of ways of using open source technologies that are meaningfully more performant and dramatically cheaper than the closed source alternative.
by the time any of these SMRs actually get near production, the TCO of solar will be like $10 or $12 per megawatt hour, and it will be 80% of all the power generation. It'll make no sense by the time SMRs get online. ... That reactor won't even get turned on until 2030 The entire world will be covered by solar by then, so it won't matter.
These models are getting commoditized much faster than anybody thought... there is no meaningful sustained advantage once a model publishes their performance criteria — within weeks, other models match and in some cases exceed the performance... I've never seen a sector absorb hundreds and hundreds of billions of dollars [where pricing power] effectively evaporates in months... the real business model is not in the foundational model anymore. It's at the application layer above and it's in the infrastructure below... if you're going to build a business model that tries to ascribe this layer as having a lot of terminal value, that is a mathematical mistake.
Google's 25 year average return on invested capital ... you give these guys the benefit of the doubt. ... an incredible silicon business. The best thing that can happen to them is 500 different models proliferate and they support all of them because they will make so much money at the silicon layer,
this is probably not the final clearing price. I think the price is probably another 10 to 15 percent higher from here. And I will say that there's a certain individual that must look very closely at putting in a competitive bid. ... a shot across the bow for Visa and MasterCard. ... They have enough of these things to go end to end on their own rails.