vbs_redlof

Next up: let's vibe code a pacemaker.

Something more like a TEE inside the browser of sorts. Not sure if there is anything like this.

And something like Hoodmaps to discern safe/unsafe suburbs in a city (quality of life differs a lot within a city, often more than between cities)

Fun fact: many ZK identity solutions run centralized provers and can be subpoenaed. Need to use something that generates proofs client-side.

I'm currently building an e-commerce platform like Etsy, and tossing up some ideas of what kind of features to provide for sellers with respect to their brand, email list, and analytics, paywalled content etc.

Deflationary money can theoretically work, its just that instead of having the vendor adjust menu prices every year for inflation, consumers would have to discount their purchases. For instance, during the 2017 boom, I noticed friends often paid each other for dinner with Ethereum at large discounts.

Obviously this isn't price efficient, and the mental calculus isn't a great user experience, but it can work. We would just live in a much more frugal society which saved a little more. We could have lower defaults as we underconsume. A credit system probably wouldn't work however as we're destroyed the concept of time value of money.

Imagine a thirsty tourist in a desert might be unwilling to part with his Bitcoin for a meal, but willing to do so for a bottle of water as his instantaneous discount rate for water is far higher at that point in time and state.

Whether a coin is inflationary or deflationary is a little more nuanced than simple changes in money supply, and has to do with whether these changes are unanticipated and how users form inflation expectations. Imagine if Satoshi's account suddenly awoke and moved, only to burn those coins in another address. There would be momentary hysteria and selloffs, before inflation expectations readjusted back to before.

You'll see that price levels are relatively indeterminate without strong commitments to target inflation rates. In that sense a bank may be better than a non-sovereign currency at maintaining price stability.

Selection bias explains why they held even even after a 90% correction.

When are beliefs common knowledge? when both agents can directly observe one another's beliefs. I.e. Bob must know Alice knows that Bob knows that .... ad inifinitum that XYZ is true. Mutually witnessing an event is sufficient for common knowledge.

I feel this is not a useful day-to-day heuristic since the theorem was intended to highlight deficiencies within the Bayesian rational paradigm (specifically the common prior assumption since game theorists weren't ready to abandon rationality in the 70's).

Beliefs are common knowledge if I know that you know that I know .... (and so) on that something is true. This occurs anytime there is trade between two agents, such as in stock markets. If I can see that you can see that this is the price we're trading at, then the traded price is common knowledge.

One of the curious implications of this theorem is that no rational agent in any market would ever agree to trade with another rational agent.

So Aumann's agreement theorem is really a warning against applying game theory to every scenario. Specifically, the common prior assumption limits the usefulness of game theory in real settings. He makes no mention of "goals" or "values", only the assumptions that the priors beliefs of the two agents are the same and their posteriors are common knowledge.

In the context of the article, disagreement means either: 1) one of you is not Bayesian rational or cannot update probabilities properly (bounded rationality) or 2) both of you must have different priors (subjective beliefs).

Both points are likely to be the case in reality, although we dislike the the second point since once we begin to entertain the idea that agents have subjective priors, you can rationalize anything and "anything goes".

It gives some insight on how we can design bidding and pricing systems to ensure that people only ever attempt to bid what they truly think an item is worth, given what they know and what they think other bidders know.

The broader goals are to establish when these systems might be "incentive compatible" (truthful bidding) and whether or not these results are robust to variations on the assumed information structure (assumptions governing what agents know, what they think other agents know, and so on).

For the HN crowd, it seems like the related field of algorithmic game theory is more practical. It focuses mainly on the implementation and complexity of various auction pricing mechanisms.

The section on 'coordination games and conventions' is also quite interesting and related to problems in distributed computing. For instance, byzantine fault tolerance and common knowledge of global state shares many similarities with economic systems in which many dispersed agents with subjective beliefs about the 'true state' of the world wish to come to some consensus over some market equilibria or economic fundamentals such as interest rates or market prices in the presence of faulty communication and/or strategic trading behaviours.

In these cases, game theory may provide insights on more robust fault tolerant designs, and economic policies that lead to stabler, and more efficient markets.

With advertising, it's not so clear whether people derive value from buying the same beer everyone is buying (although for certain products, sure). Is someone more inclined to buy a Corona or a bag of Doritos from merely knowing that others have seen the ad?

Then again, if the ad is particularly funny or surprising then knowing that others know about the ad certainly makes it easier to casually converse about the ad with others. Maybe then I'll buy a corona just for shits and giggles, who knows. If this is what is meant by 'entering the culture', then maybe this theory holds water. It just seems like a really expensive way to do it.

Includes withdrawn, priced and filed IPOs. Very clean data, straight from SEC Edgar filings.

My favourite explanation: http://vudlab.com/simpsons/

Stata is great for drag and drop data manipulation from what I remember, an excellent excel replacement. Nothing beats dragging and dropping in variables and typing: reg y x1 x2 for immediate regression results.