Posted by kscarlet 3 hours ago
The author looks credible:
https://philipmaymin.com/about-philip
Thank you for sharing this on HN.
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To the mods: The title needs to be edited to replace the equal sign with not-equal.
But, both free markets and supply/demand are useful enough concepts to talk loosely about processes to understand the interest that I'll enjoy digging into this.
The behavioral economics/Freakonomics thing was like "Hey, here's this thing that might if you squint real hard fall outside of efficient market theory" and then for a decade people took that to mean that that the base concepts were worthless, which was a severe overcorrection from people that didn't understand economics.
Nothing to do with ideology, but with the nature of the field. Take epidemiological research in the areas of food and medicine: incredibly hard and expensive to get right and even then with often tenuous results. Now try doing that with ridiculously heterogeneous nations influenced by potentially almost everything on the planet.
It's a small miracle that economists manage to get some useful insights out of the data, but we should definitely be aware of how weakly most of them are supported (don't start talking about "error bars" with economists).
“=“ <> “!=“Most filters are to avoid sensational titles, AFAIK.
BASIC[1] came out in 1964, and Pascal[2] came out in 1970.
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[1] https://en.wikipedia.org/wiki/Dartmouth_BASIC
[2] https://en.wikipedia.org/wiki/Pascal_(programming_language)
Markets are efficient if and only if P = NP https://arxiv.org/abs/1002.2284
:)
> Combined with Maymin (2011), who proved that market efficiency requires P = NP, this yields a fundamental impossibility: markets can be informationally efficient or competitive, but not both.
"Markets are competitive if and only if P != NP"
Seems that HN's auto-headline rewriting in this case has made a critical error :)
>Artificial intelligence, by expanding firms' computational capabilities, is pushing markets from the competitive regime toward the collusive regime, explaining the empirical emergence of algorithmic collusion without explicit coordination.
I have to dig more into the paper but I don't see how this follows, except in the most straightforward way. Basically, if everyone uses the same methods to derive price, of course there will be "collusion", or in other words, everyone will have the same price. But this doesn't seem like a result of compute per se, but simply better communication networks and information flows. You could have gotten the same result in medieval England by having everyone post their selling prices on the town square board.
Again, I haven't dug into the paper yet, but it seems like what really matters for firms is "compute"/$ (if the "compute" is an LLM or an assistant that has to go walk the 10 minutes down to the square makes little difference)
Edit: Isn't another implication of this, that increased compute -> collusion imply that increased compute -> communism becomes feasible?
I think this goes to my point above though, the primary problem preventing fully automated luxury communism isn't compute per se, but actually observing the information flows to make it possible. Capitalism famously solves this information problem through the pricing mechanism. So in effect, he's arguing that extra compute makes information gathering more efficient, and at the limit you get perfect information. Which, yeah, I guess so. Assuming everything can be perfectly measured, even theoretically.
YieldStar was technically an “AI” product, but I don’t really think the computational abilities were what enabled the collusion. RealPage’s employees (according to the DoJ[0]) would actively monitor whether companies were following their pricing recommendations and call up companies that defected. And the software itself used dark patterns to make it easier to simply follow the YieldStar pricing suggestions, rather than set a lower rental rate and be more competitive. The algorithmic pricing I think did allow people to launder their own judgement and simple “trust the process” in a way that in the past would have required knowing complicity with the cartel, but I don’t think it required substantial compute capacity.
(This isn’t a comment on the paper by the way, which I glanced at but did not have the background knowledge to fully comprehend)
[0] See the section labeled “RealPage Uses Multiple Mechanisms To Increase Compliance With Price Recommendations” https://www.federalregister.gov/documents/2026/01/21/2026-01...
You could imagine the exact same scheme without the use of a computer.
I'm eagerly awaiting the day someone proves that P != NP and HN edits the title of the announcement post in this exact same way.
“Markets are competitive if and only if P ≠ NP”
It’s 2026, people, you don't have to use crude ASCII approximations of mathematical symbols any more.
For whatever reason, the OS documentation lacks a list of allowed compose key sequences. But they are intuitive enough that you can find many of them through experimentation. For example:
Musical sharp ("♯"): compose + "#" + "#".
Interrobang ("‽"): compose + "!" + "?".
Letter "ñ" as in "jalapeño": compose + "n" + "~".
Copyright ("ⓒ"): compose + "(" + c + ")".
A more capable actor can anticipate the actions of other participants to a greater degree. Imagine that all sellers are such actors. Consider that collusion happens (and is bad) because it enables sellers to extract much higher prices than the market would otherwise set. When all sellers are such "hyper rational" actors they can act cooperatively to maximize their profits without the need to explicitly coordinate in secret. The same end result without the illegal step sure feels like an end run around the spirit of the law.
> Edit: Isn't another implication of this, that increased compute -> collusion imply that increased compute -> communism becomes feasible?
That depends on what you think the problem that communism faced was. AI increases our ability to centrally plan but it probably doesn't do much in and of itself to combat various forms of corruption. Human greed is an invariant; by glorifying and directly making use of it capitalism is hardened against a number of otherwise pathological behaviors.
> If P != NP, the collusion detection problem is computationally infeasible for markets satisfying a natural instance-hardness condition on their demand structure, rendering punishment threats non-credible and collusion unstable.
...and then from the paper:
> Stigler (1964) famously argued that the “chief difficulty” of collusion is detecting “secret price-cutting.”
The thing is that Stigler's insight is far from proven, and indeed, the primary difficulty in collusion is often not the detection of defection. Firms know they're being undercut all the time. The problem is that very often, there is nothing they can do about it. Markets are specifically structured as firm-to-firm transactions, where competing firms have no leverage over what your firm can do or what sort of transactions you can conduct, and as long as this condition holds it doesn't matter if you know that a competitor is fucking you over, you can't do anything about it.
I'd argue that the increase in collusion and anticompetitive behavior lately is because these conditions increasingly don't hold. When you intersperse another party in the transaction, eg. a regulatory agency, permitting body, or exclusive distribution deal, you introduce a leverage point for incumbents to punish competitors who choose to undercut them.
Examples of the former: cutting prices yourself; increasing product quality; differentiating yourself; spending more on advertising to get the word out about your product.
Examples of the latter: crafting exclusive deals with your distributors to prevent your competitors from getting shelf space; politically influencing regulatory bodies to declare your competitors' existence illegal; making direct agreements with the leadership of opposing firms to not drop prices or hike wages; assassinating, extorting, or kidnapping rival business leaders.
Basically it comes down to "control yourself, because you cannot control others". In a functioning market, you have no control over what rival firms offer. Your only legal reaction to competition is to improve your own offering until it is the best it can be. In pathological markets where the assumption is (as in the paper) that you can punish rivals for not colluding, you actively make your competitor's offering worse.
Those pathological markets exist today, but if you're analyzing markets economically, your root assumption should not be that pathology is normal and only the lack of information keeps it in check, it should be that information is abundant and it is the lack of ability that keeps it in check.
The term ‘perfect information’ is a bit of a mirage, and has been shown to be impossible in physics (uncertainty principle).
What really matters is information advantage: Does your inexact expected value function consistently beat others’ calculations in the market. Here, the true value - value really is just a word and is dependent on people - is irrelevant.
NP problems gets solved with heuristics every day.
You don't know that!
You do realise that you'll never work in this town again? \s :)
Really interesting conclusion, but I can't help but feel this is overly reductive, as stated. Surely market efficiency is a sliding scale and so is market competitiveness.
Okay, so a perfectly competitive market cannot also be a perfectly efficient market. Interesting! But I'm confused about how this may work when efficiency and competitiveness are a sliding scale. Should we think of this as one axis (with a spectrum from efficiency to competitiveness) or as two separate axes that just happen to have an exclusive relationship between their extremes?
NP-Completeness is the norm, not the exception. Any system that's complex enough is almost surely NP-Complete. For similar reasons, Turing Machine Equivalence is also the norm, not the exception.
These results are interesting but not unexpected. A more interesting question is under what conditions is the problem difficult to find solutions for. Many NP-Complete instance ensembles turn out to effectively have polynomial time solutions (3-SAT w/ uniform clause variable choice, Hamilton Cycles in Erdos-Renyi random graphs), so proving NP-Completeness is not a death knell for approximation.
If P!=NP then it is arbitrarily smaller, for the same reason that e^x > Cx^N for any constants C and N, as long as x grows big enough. There is no epsilon in that can overcome that, no matter how big you make it, because x will eventually dominate the equation.
There are a lot of cases where pragmatically x remains small enough that it doesn't matter, and a P algorithm will give you an answer more quickly. (For the same reason I only ever write bubble sorts: I would only write my own at all if I knew that the list would never be bigger than 10. Even then it's only when using the library is too much trouble for some reason.)
But we care about P and NP when the number can potentially be very, very large.
So I'm not talking about the number of steps needed to prove optimality with a correct P algorithm versus an exponential one.
I'm only talking about how this applies to the efficient market hypothesis.