The fact that Alameda could and did “borrow” (much) more than any other account on FTX due to the allow_negative flag is consistent with Levine’s description, but I agree a fuller accounting of events would include this piece of information and the accusations you cite.
Could you say a bit more about why the allow_negative flag, which was unique to Alameda accounts, is consistent with Levine's references to borrowing "in the ordinary course of business . . . based on their crypto positions"? A special exception for a customer owned by FTX's CEO, which allowed said customer to go over $10B in the red when no other customer was allowed a similar privilege, does not sound "in the ordinary course of business" to me. That doesn't sound "based on their crypto positions" either.
Source for over $10B: this summary of recent testim...
Matt Levine had an especially clear exposition recently I thought:
...A simple version of the charges against Sam Bankman-Fried would be something like “people deposited money at his crypto exchange, FTX, and he stole it and gave it to his crypto trading firm, Alameda Research, which squandered it on dumb crypto trades and endorsement deals.”
But this story is not exactly right. There was not money sitting in customer accounts that was then transferred to Alameda accounts and squandered. FTX was a futures exchange; it did not keep money in a box for customers.
As others have commented, this strikes me as a misleading summary.
...But this story is not exactly right. There was not money sitting in customer accounts that was then transferred to Alameda accounts and squandered. FTX was a futures exchange; it did not keep money in a box for customers. The money in your FTX account was just money that FTX owed you. Nor did Alameda need to steal the money; FTX was a leveraged futures exchange, and traders like Alameda could, in the ordinary course of business, borrow money from FTX based on their crypto positions. The prob
This is not at all what happened. Alameda's "borrows" were not made via the normal margin lending program. You can see Caroline Ellison admitting so in a contemporaneous meeting that was recorded and played in court. Nishad Singh and Gary Wang explicitly wrote code to allow Alameda specifically to take customer funds from FTX via the "allow_negative" flag, according to their own sworn testimonies. It seems like Matt Levine is confusing this collapse with the Mango Markets collapse that happened around the same time, his description fits Mango much better t...
Thanks for this, this is a topic I am very interested in -- to the the killer feature missing in Speechify is the ability to highlight and sync those highlights. Or more broadly, annotating in a multimodal way is difficult.
I instead use Goodreader, where you can have e.g. a Dropbox folder of all your PDFs synced across desktop and mobile; and you can annotate those PDFs while listening, then sync to Dropbox.
The downside of Goodreader is that the voice is pretty bad, and also that you can't reflow the text to make it easier to read on mobile while in audio ...
If you haven't seen, a long analysis of this:
Forgive me if I'm just being dumb, but -- does anyone know if there is a way in settings to revert to the old font/CSS? I'm seeing a change that (for me) makes things harder to read/navigate.
Levered ETFs exhibit path dependency, or "volatility drag", because they reset their leverage daily, which means you can't calculate the return without knowing what the interest rate does in between the 3% rise
The entire section is based on a first-order approximation, as explicitly noted in the post (which is also why we set aside e.g. the important issue of convexity). This point is of course correct!
...A related point: The US stock market has averaged 10% annual returns over a century. If your style of reasoning worked, we should instead buy a 3x levered S
Thanks for these comments!
For what it's worth, I suspect many readers do think there's some chance of stagnation (i.e. put 5% credence or more). Will MacAskill devotes an entire chapter to growth stagnation in What We Owe the Future. In fact he thinks it's the most likely of the four future trajectories discussed in the book, giving it 35% credence (see note 22 to chapter 2, p. 273-4).
The Samotsvety forecasters think this is too high, but each still puts at least 1% credence on the scenario and their aggregated forecast is 5%. Low, but suggesting it's worth considering.
Yes, to emphasize, the post is meant to define the situation under consideration as: "something close to a 10x increase in growth; or death". We're interested in this scenario only because it's the modal scenario in the particular world of LW/EA/AI safety.
The logic of the argument does not apply as forcefully to "smaller" changes (which could potentially still be quite large), and would not apply at all if AI did not increase growth (ie did not decrease marginal utility of consumption)!
To summarise, the effect on equities seems ambiguous to you, but it's clearly negative on bonds, so investors would likely tilt towards equities.
"Negative for bonds" does not imply "shift investment from bonds to stocks", though. It could mean "shift toward short bonds" or "shift investment from bonds, to just invest less overall".
In addition, the sharpe ratio of the optimal portfolio is decreased (since one of the main asset classes is worse)
I would push back on this too, for a related reason -- the optimal portfolio can include "go short bonds", wh...
Here's another way of putting things, that I'll post here for reference:
Suppose I think Google is undervalued, because it is going to have a $1T dividend in 2030, and the market doesn't realize this.
1. I buy Google today at some cheap price.
2. Possibility 1: before 2030, the market "corrects" and realizes that it was undervaluing Google. The stock price rises, and I receive capital gains.
3. Possibility 2: the market does not "correct" before 2030. I still get the big dividend in 2030, and was able to get it for a cheap price in 2023.
---
The abov...
1. Very interesting, thanks, I think this is the first or second most interesting comment we've gotten.
2. I see that you are suggesting this as a possibility, rather than a likelihood, but I'll note at least for other readers that -- I would bet against this occurring, given central banks' somewhat successful record at maintaining stable inflation and desire to avoid deflation. But it's possible!
3. Also, I don't know if inflation-linked bonds in the other countries we sample -- UK/Canada/Australia -- have the deflation floor. Maybe they avoid this issue.
4....
Thanks for these comments. In short, to all of your questions, the answer is "yes". Some specific comments:
1. This is perhaps already clear, but it might be worth emphasizing that the economic logic is: real rates are particularly use for forecasting, since the sign of the effect is rather unambiguous for the TAI scenario; but it's possible the expected returns could be higher for trading on other bets, if you're willing to make stronger assumptions (e.g. "compute will be important").
2. Re: equities, the appendix post (especially #4 there) summarizes how w...
I'll just pop back in here briefly to say that (1) I have learned a lot from your writing over the years, (2) I have to say I still cannot see how I misinterpreted your comment, and (3) I genuinely appreciate your engagement with the post, even if I think your summary misses the contribution in a fundamentally important way (as I tried to elaborate elsewhere in the thread).
Thanks for this interesting exercise. The one caveat I'd note is that the multiplier you use is based on annual revenue -- if the remittances from OpenAI to MSFT occur over a number of years, we would need to divide the $1T number that you calculate by that number of years.
(PS: amazing tiktoks)
Thanks Seth, we'll read your paper carefully. I'll just highlight that really the purpose of the analysis above is to engage specifically with the extreme scenario you mention at the end
what the effect would be today of a giant anticipated increase in automation in 30 years, or of everyone dying with certainty in 30 years [...] we could try if anyone thinks it would be interesting
Also note we briefly allude to demographic trends, but in the (blog post!) analysis here, we want to ignore them because they seem plausibly swamped by the huge growth/morta...
1. We would welcome engagement from you regarding our argument that stock prices are not useful for forecasting timelines (the sign is ambiguous and effect noisy).
2. You offer what is effectively a full general argument against market prices ever being swayed by anything -- a bit more on this point here. Price changes do not need to be driven by volume! (cf the no-trade theorem, for the conceptual idea)
3. I'm not sure if this is exactly your point about prediction markets (or if you really want to talk about total capital, on which see again #2), but: ...
Sorry, I stand by my comment 110%.
If you already knew that belief in AGI soon was a very contrarian position (including amongst the most wealthy, smart, and influential people), I don't think you should update at all on the fact that the market doesn't expect AGI.
I want to maximally push back on views like this. The economic logic for the informational efficiency of markets has nothing to do with consensus or 'non-contrarianness'. Markets are informationally efficient because of the incentive for those who are most informed to trade.
The argument here...
If investors with $1T thought AGI soon, and therefore tried to buy up a portfolio of semiconductor, cloud, and AI companies (a much more profitable and capital-efficient strategy than betting on real interest rates) they could only a buy a small fraction of those industries at current prices. There is a larger pool of investors who would sell at much higher than current prices, balancing that minority.
Yes, it's weighted by capital and views on asset prices, but still a small portion of the relevant capital trying to trade (with risk and years in advance) o...
^This is an extremely, extremely important point!
Market prices are not a democracy. The logic for the efficiency of markets is emphatically NOT 'wisdom of the crowds'. It's that the most knowledgeable traders have the most to gain from trading, and so do so, and determine the price. (I have a riff on this here)
Thanks for this -- I think you put really nicely the interpretation that we also are pushing for.
If you don't like the OpenAI example, consider the possibility that other non-public companies could develop AGI...!
Pasting some of my replies to this from twitter FWIW:
I think the claim is that with fast takeoff, the market will either never decide that you are right (we die before the market realizes), or will decide you are right and you get rich but have only a short time to live, so there's no value to being rich.
One crude metric: the number of forecasters has gone up 25% in the last month, from n=284 to n=354
It would be interesting if it were possible to disambiguate:
1. Previous forecasters moved up their forecasts to shorter timelines
vs.
2. New forecasters, who have shorter timelines, offered forecasts for the question when they hadn't forecasted previously
Both are informative, and in a real-money prediction market both are equally informative. But with a forecasting platform, this could "just" be a composition bias?
Cascading, systemic and GCRs typically aren’t priced into asset prices
I'm not sure that this is important to your arguments, but -- do you have any evidence that this is actually the case?
For diaphragmatic breathing, where are you getting the 27.05% number from? I didn't see it in the Hamasaki (2020) lit review you linked to.
Also, looking at that paper:
I like this writeup a lot, but I would say to anyone who's actually reading this should ignore the advice to not go into academia.
If you're reading this, you're probably selected (!) to be someone who is atypical and has a decent shot at succeeding in academia. (See also: SSC on 'reversing all advice you hear'.) i.e.: if you're someone who's taking the time out of your day to read this, you're probably (probably!) similar to "Anita" here.
Ugh. Shrug. That isn't supposed to be the point of this post. All my comments on this are to alert the reader that I happen to believe this and haven't tried to stop it from seeping into my writing. It felt disingenuous not to.
But since you raised, I feel like making it clear, if it isn't already, that I do not recommend reversing this advice. At least if you are considering cause areas/ academic domains that I might know about (see my preamble). I have no idea how applicable this is outside of longtermist technical-leaning work.
If you think you might be a...
Agreed re: "mispricing = restatement that this is a contrarian position" -- but to push back on your "lack of feedback" point:
If the market can't price 30-year cashflows, it can't price anything, since for any infinitely-lived asset (eg stocks!), most of the present-discounted value of future cash flows is far in the future.
See eg this Ralph Koijen thread and linked paper, "the first 10 years of dividends only make up ~20% of the value of the stock market. 80% is due to value of cash flows beyond 10 years"
(I wonder how big EMH proponents like Hanson and Yudkowsky explain the dissonance.)
Personally I agree with the economic forecasts and approximate timelines here, but I haven’t seen a way of reconciling the “accelerating growth” prediction with the efficient market hypothesis.
Low 30-year government bond rates in the US (and 50- or 100-year rates in some other countries!) imply the market expects low growth over this time horizon, not ever-accelerating economic growth rates.
If growth goes up and interest rates rise, these are massively overvalued. It’s possible, but, we’d have to tell some some more elaborate stories (AI-led growth is not broad-based? It’s all captured by one firm...? It FOOMs?) if we want to be consistent with EMH.
I I think the market just doesn't put much probability on a crazy AI boom anytime soon. If you expect such a boom then there are plenty of bets you probably want to make. (I am personally short US 30-year debt, though it's a very small part of my AI-boom portfolio.)
I think it's very hard for the market to get 30-year debt prices right because the time horizons are so long and they depend on super hard empirical questions with ~0 feedback. Prices are also determined by supply and demand across a truly huge number of traders, and making this trade locks up y...
This smells like a composition effect. Have you checked that this is not just due to e.g. aging of the population; or driven by the rise in immigration?
Raimondo and the Department of Commerce seem to have been remarkably effective on AI/China issues during the Biden administration. Is there any detailed reporting on how governance became (seemingly) so good there?
What are some of your favorite examples of their effectiveness?
This piece might have some of what you're looking for: https://www.washingtonpost.com/opinions/2023/10/31/ai-gina-raimondo-is-steph-curry/