mabramov

Karma: 641

mabramov 14 May 2026 15:51 UTC
1 point
0
in reply to: SatvikBeri’s comment on: How the AI Labs Make Profit (Maybe, Eventually)
I agree with all of this and matches my experience in quant trading (though ive been out of the game for a while)

mabramov 14 May 2026 5:41 UTC
1 point
2
in reply to: leogao’s comment on: How the AI Labs Make Profit (Maybe, Eventually)
I don’t think it matters, but I’m not sure that’s true. I think the major quant firms are already using LLMs in their trading and plan to use more.
In terms of making full use of frontier models, the models aren’t currently good enough to send forth, and trade, and you have the problem of adverse selection (if you start putting bad quotes, they get snapped up). Firms are definitely making use of the models in building their systems. I think quant firms are perhaps the 2nd-most AI-pilled segment of society.
But my point is that I think there are a lot of what you might call “LLM-based trading strategies”. One example is using LLMs to read press wires or earnings reports/filings. Another might just be that LLMs allow you to MM on markets much more easily that you wouldn’t have bothered with before to set up the infrastructure. For example, if there are some 100 markets in Chile that have $10k of volume a day that nobody currently bothers with, all of a sudden, you can throw your LLM at it and make 1% on that volume, maybe. Not worth paying a quant trader to actively MM and get adversely selected against. But worth $20 of tokens,

mabramov 11 May 2026 20:40 UTC
4 points
2
in reply to: Petropolitan’s comment on: How the AI Labs Make Profit (Maybe, Eventually)
Quant trading is the one I know the best because I’ve been a quant trader. There are real skills that are required, other than just having great trading strategies or w/e but they can all be hired for. It’s also hard to overstate how many traders work at these labs. I think OAI and Anthropic probably have more former quants than any trading firm currently has. They can hire a lot of other necessary skills. They already have SWEs. I think the labs could spin up internal trading firms that are profitable, using their frontier AI, in under a year and be making $1B or more, profitably (after all expenses, including compute, salaries, etc.)

mabramov 11 May 2026 20:38 UTC
3 points
0
in reply to: pjohn’s comment on: How the AI Labs Make Profit (Maybe, Eventually)
I’m not claiming that everything is of this shape. There are gains to specialization. In the shopping centres case, your core competency is probably the construction of real estate, or your big moat is all in owning the valuable real estate, so you can charge very high rents where most of the profits come from.
You would, in fact, get a discount on using your own real estate for other purposes, but others have more and better purposes, and you don’t specialize in this. This is because most things in shopping centres are either relatively low margins, all things considered, or have fairly low total markets ($<50M/year or w/e). The ability to make coffees is fairly commoditized. You can either implicitly pay the rent and run the business where you expect lots of revenue, or you can charge it out to someone else to do that.
There is a widespread joke about companies saying they are going to “make a bunch of alpha and sell it to hedge funds”. This is incredibly hard to do and basically never makes sense. If you have alpha, you should just use it yourself because it is more valuable that way.
Suppose you found an arbitrage between bitcoin across two exchanges that can make you $1M/year because there is $100M of volume and the arbitrage is for 1%. If you tell me about this strategy, I will be willing to close this spread further, and market make such that the edge is maybe 0.5% now. As more people enter the space, there is still $100M of volume, but the arbitrage between the exchanges is going to reduce further and further towards $0.
I’m not saying that all businesses are of this form. There are, of course, things you need other than AIs to run a lot of businesses. I’m saying there are some with extreme profit margin potential, such that the incentive is to keep it internally as opposed to sell it and widely distribute it. Perhaps they will still sell models for use by the public, but it’ll be 2nd-best models or models without all the intelligence needed for LLM-based trading on earnings reports or presswires.
If frontier models are only 12 months ahead of open models, how would the frontier labs get around the “If we can do it now the whole world can do it in 12 months” problem? Could a frontier lab build up enough of a running start in 12 months that you could never be caught? They couldn’t do this with AI development despite that being their speciality.
I see what you are getting at. I think it is closer to 6 months. I think if you try to charge too much, you are simply going to run into the problem that you simply do not need that much intelligence for most use cases, and so you won’t be able to charge 10x as much for Opus 4.7>4.6 or w/e. You get to charge like 20% more, maybe.
Finally—how much would the supply-demand equation for frontier AIs have to change for the labs to expect they could increase their value more by spending whatever resources they have on business ventures other than “developing frontier AI”?
I think Phil Tramell should get involved here. But “developing frontier AI” is not a business that makes money. Selling the frontier AI through API is the business currently. I’m saying that there is a new line of business that makes a lot of sense. Keeping your AI internally and using it to make money in a few specific industries, particuarly where having the best model all to yourself really pays dividends.

mabramov 11 May 2026 20:20 UTC
3 points
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in reply to: Vladimir_Nesov’s comment on: How the AI Labs Make Profit (Maybe, Eventually)
If they go public, this level of funding can continue. There is a lot of demand for exposure to AI.
I think it’s possible, but I don’t think it’s likely that we could have the most valuable companies in the world by market cap, raise trillions of dollars without being profitable, or have a plan to become profitable very soon. There is only so much capital, and particularly risk capital. The dynamic changes a lot when there isn’t much room for growth. In particular, there is about $100T of total revenue per year in the world right now, and so even if you capture all of it, with 100% gross margins and a P/E ratio of 20, you are only looking at a market cap of a quadrillion or a 200x at MC of $5T. Larger amounts of capital are much more risk-averse than smaller amounts of capital.
If Anthropic is making $44bn in annualized revenue
I think people are over-indexing on this here, every month they get insane growth and think this will occur forever. I wish these numbers were audited. There is also more to spend money on than raw compute but I do agree this is the bulk of it. They did just make a deal with SpaceX for a lot of compute they could feasibly spend a lot of money on. I don’t see how this negates any of my analysis above.
I suppose I would ask, do you think Anthropic is currently profitable (or was in April)?

mabramov 11 May 2026 7:56 UTC
11 points
6
in reply to: Mitchell_Porter’s comment on: How the AI Labs Make Profit (Maybe, Eventually)
I think, like a lot of what gets said on the All-In Podcast, this doesn’t make much sense.
The models aren’t yet making money. These companies are still cash-flow negative, and I am not expecting that to change for a while, at least another few months.
As for the tokens themselves making money, I think this is pretty ridiculous, but even taking them at their word, the companies that are buying tokens are already making money from them. Claude Code usage thus far has been incredibly subsidized by VC dollars and companies wouldn’t be paying for the tokens if they weren’t helping them make money. Companies aren’t paying for tokens just to get their employees used to coding with them. They are already making money from using AI (allbeit, a little).

mabramov 11 May 2026 7:52 UTC
5 points
0
in reply to: anaguma’s comment on: How the AI Labs Make Profit (Maybe, Eventually)
https://x.com/OHatTartine/status/2003910041649532983
I think this is the first public report of it, but I’ve heard it many times.
I should note, I think the major labs would be nuts if they aren’t spending time getting better at trading. There are a myriad of reasons to want to use LLMs in trading.

How the AI Labs Make Profit (Maybe, Eventually)

mabramov11 May 2026 7:09 UTC

61 points

16 comments3 min readLW link

mabramov 7 May 2026 2:34 UTC
5 points
1
in reply to: habryka’s comment on: Matrice Jacobine’s Shortform
You actually wouldnt know if it was less than 1% due to interest rates

mabramov 7 May 2026 2:33 UTC
4 points
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in reply to: habryka’s comment on: Matrice Jacobine’s Shortform
The accuracy of this market is dwarfed by the interest rate involved.

mabramov 5 May 2026 20:41 UTC
1 point
−2
in reply to: Aryan64’s comment on: Forecasting is Way Overrated, and We Should Stop Funding It
On the solution seeking a problem, I think proponents of blockchain say similar things about how useful it would be if our financial system were predominantly on the blockchain and how much benefit there would be, in particular to the unbanked. They do, in fact, say this.
I never said that forecasting cannot be useful. I think it hasn’t been useful to the tune of the money thrown at it, and I’m skeptical that further investment is going to pay off in usefulness. I was somewhat expecting the defenses of forecasting to be better than they have been. The best one was probably this one by @habryka or another reply by Eva Vivalt on the EA forum.
It’s possible we haven’t been funding the right thing within forecasting. Maybe this weekend I will tally up every grant and investment made into forecasting, but I think it is ~$100m. That said, I think basically any poor funding decision will have people saying something similar to this:
This would still mean that existing funding that is focused on improving the resolution and quality of forecasts needs to re-prioritise and focus on the distribution more, but would not go so far as to say we should stop funding it altogether.
When a startup says that their product hasn’t taken off and all they really need is better marketing to do so, you should run. I think we should say the same thing here, too. If you need to focus on distribution and try to force your product into being used, it probably isn’t that useful. When something is very useful, it gets adopted at extreme speed. The AI companies aren’t spending a lot on marketing. For example, people adopted LLMs, chatbots, and other products extremely quickly, and they were more or less just announced.
Furthermore, prediction markets have been adopted, so it’s hard to say it’s an issue of marketing. Almost everyone important has heard of Polymarket and Kalshi at this point and know how PMs work. And none of them has decided that they would be very useful. It just so happens that they are useful for sports gambling primarily and not for making better decisions.

mabramov 3 May 2026 1:21 UTC
4 points
0
in reply to: Ben S.’s comment on: Forecasting is Way Overrated, and We Should Stop Funding It
1. Manifold I think had $6M or so of investment and given the state of Manifold, clearly the market disagrees with you that this was money well spent. Perhaps they will turn things around but this is Manifold DAUs.
1. I agree that investing in Polymarket or Kalshi in the early days would have been a good investment. I think its really hard to make the case that they have been good for society; we basically got more sports betting.
2. I’m saying that if you were to compute the amount the EA community has spent on forecasting and the amount donated that got into the community through forecasting, I think the ROI would be very negative.
3. 25 is not that many people for this and I was being very generous saying 25. I think a more fair number is like 5-10.
4. .
5. I did the forecasting stuff to show that I could do it, yes. I remain unconvinced it has been very useful to the world.
I feel like above all, I want to stress that EA dollars should meet a really high bar. You can save a child’s life for about $5000. You can get a chicken out of a cage for 10 years for about $1. You can apparently build a play money prediction market website for about $6000/DAU.

mabramov 2 May 2026 13:55 UTC
3 points
0
in reply to: Nathan Young’s comment on: Forecasting is Way Overrated, and We Should Stop Funding It
I’ll ask a different question than I did on the EA forum.
Do you think you work in and are interested in prediction markets/forecasting because they are interesting or because they are the best thing you can do for the world?

mabramov 1 May 2026 8:01 UTC
1 point
0
in reply to: tenthkrige’s comment on: Forecasting is Way Overrated, and We Should Stop Funding It
They will still be funding lots of forecasting, just not through a dedicated fund.

mabramov 1 May 2026 8:00 UTC
2 points
0
in reply to: AnthonyC’s comment on: Forecasting is Way Overrated, and We Should Stop Funding It
I think this is a good point. I don’t think it makes up for the ~$125M or so that EA has put into forecasting.

mabramov 1 May 2026 7:59 UTC
2 points
0
in reply to: Austin Chen’s comment on: Forecasting is Way Overrated, and We Should Stop Funding It
I agree that forecasting is an ok way to find talent but not much of this has been done.
I agree that in chaos, they are useful but I don’t think they hit the bar for EA funding.
Sure, it’s speculative. If the AIs will use them, then they will also make them and we can just relax for now on the forecasting and let them do it in the future.

mabramov 1 May 2026 7:57 UTC
2 points
1
in reply to: Ben S.’s comment on: Forecasting is Way Overrated, and We Should Stop Funding It
1. I’m not sure I understand the point. A lot of people have donated money to Wikipedia and now they have a big war chest. I agree Wikipedia has been valuable but I’m not sure how you are computing the value. I don’t see any proof that hundreds of thousands of people are making incrementally better decisions though. My point is that this was the hope but it is sort of just asserted without evidence. I’m happy you’ve enjoyed Manifold, I don’t think that means EA money should go to it. There is a very very high bar to clear for EA money.
2. I’m not sure I understand your point. I agree that Kalshi and Polymarket are big and have attracted users and investment. My point is that they haven’t given this outpouring of social returns that people claim they are to have. They are just good businesses (charging fees on gambling).
3. I don’t think you can claim millions of dollars from community growth but I’m sure this ROI would then be negative.
4. I agree that forecasting has been somewhat useful for identifying talent/nerd-sniping. I don’t think very much of this has happened though. I think less than 25 people (to be conservative) have roles due to their forecasting prowess where they were unknown before.
5. This has been discussed elsewhere.
6. There is no proof here. Would you say today’s epistemic environment is much better than 20 years ago?

mabramov 1 May 2026 7:51 UTC
1 point
0
in reply to: Stephen Fowler’s comment on: Forecasting is Way Overrated, and We Should Stop Funding It
Anything in particular you want expanded upon? I think this is most of what I have to say on the matter. I’ve been saying some form of this opinion for about 3 years now and I’m happy this is finally out there.
Yea, my point is that the bar for EA money needs to be very very high.
It’s on the EA forum. Was posted at the same time!

mabramov 1 May 2026 7:47 UTC
7 points
0
in reply to: Josh Rosenberg’s comment on: Forecasting is Way Overrated, and We Should Stop Funding It
I’m not sure the norms here but I will just copy over my reply from the EA forum.
Hi Josh, thanks for the response.
I hate to do this, especially at the start, but I want to point out for you and others who have jobs related to forecasting that it’s difficult to convince someone of something when their job relies on them not believing it. I think you should assume that you will think forecasting is more useful than it is.
As for your points, I’ll respond to some of them.
1. If you want to DM me, I can sign an NDA, and I may update my opinion depending on what these non-public uses of forecasting are.
2. I don’t think this is all that relevant. I’m not sure what forecasting research has really elicited on AI timelines. I agree that talk about timelines creates a lot of “buzz” around AI but depending on your views, this is good or bad.
3. I agree that the impact of measurement-oriented research is difficult to measure, but importantly, not impossible. OWID for example should count how much their work is being cited and looked up. Conversely, I think it would be good to estimate, for FRI, how much $$ the change of the decision was worth and by what amount/percentage did FRI make that change more likely. I don’t think you really gave a good reason that FRI should be funded over anything else that simply has very diffuse benefits.
4. When do you think it’s reasonable, if ever, for the EA community to “give up” on funding more forecasting work?
5. If I’m being cynical, almost every field can say “AI will transform the field” though I’m not sure how much this is worth debating.

mabramov 1 May 2026 7:35 UTC
2 points
0
in reply to: elifland’s comment on: Forecasting is Way Overrated, and We Should Stop Funding It
Yeah, I just don’t agree that reality has played out like AI 2027 in any meaningful way that isn’t very obvious. It’s too early to say. Basically, no meaningful predictions are made until the end of 2026, so we are too early to say. It’s just too early to claim victory.
I have been meaning to write up my critiques of AI 2027 but I have too many of these kinds of posts to write up and I’m a slow writer.

mabramov

How the AI Labs Make Profit (Maybe, Even­tu­ally)

How the AI Labs Make Profit (Maybe, Eventually)