Fairness alternatives to selling below market clearing prices (or community sentiment, or fun)
When a seller has a limited supply of an item in high (or uncertain and possibly high) demand, they frequently set a price far below what "the market will bear." As a result, the item sells out quickly, with lucky buyers being those who tried to buy first. This has happened in the Ethereum ecosystem, particularly with NFT sales and token sales/ICOs. But this phenomenon is much older; concerts and restaurants frequently make similar choices, resulting in fast sell-outs or long lines.
Why do sellers do this? Economists have long wondered. A seller should sell at the market-clearing price if the amount buyers are willing to buy exactly equals the amount the seller has to sell. If the seller is unsure of the market-clearing price, they should sell at auction and let the market decide. So, if you want to sell something below market value, don't do it. It will hurt your sales and it will hurt your customers. The competitions created by non-price-based allocation mechanisms can sometimes have negative externalities that harm third parties, as we will see.
However, the prevalence of below-market-clearing pricing suggests that sellers do it for good reason. And indeed, as decades of research into this topic has shown, there often are. So, is it possible to achieve the same goals with less unfairness, inefficiency, and harm?
Selling at below market-clearing prices has large inefficiencies and negative externalities
An item that is sold at market value or at an auction allows someone who really wants it to pay the high price or bid high in the auction. So, if a seller sells an item below market value, some people will get it and others won't. But the mechanism deciding who gets the item isn't random, and it's not always well correlated with participant desire. It's not always about being the fastest at clicking buttons. Sometimes it means waking up at 2 a.m. (but 11 p.m. or even 2 p.m. elsewhere). Sometimes it's just a "auction by other means" that's more chaotic, less efficient, and has far more negative externalities.
There are many examples of this in the Ethereum ecosystem. Let's start with the 2017 ICO craze. For example, an ICO project would set the price of the token and a hard maximum for how many tokens they are willing to sell, and the sale would start automatically at some point in time. The sale ends when the cap is reached.
So what? In practice, these sales often ended in 30 seconds or less. Everyone would start sending transactions in as soon as (or just before) the sale started, offering higher and higher fees to encourage miners to include their transaction first. Instead of the token seller receiving revenue, miners receive it, and the sale prices out all other applications on-chain.
The most expensive transaction in the BAT sale set a fee of 580,000 gwei, paying a fee of $6,600 to get included in the sale.
Many ICOs after that tried various strategies to avoid these gas price auctions; one ICO notably had a smart contract that checked the transaction's gasprice and rejected it if it exceeded 50 gwei. But that didn't solve the issue. Buyers hoping to game the system sent many transactions hoping one would get through. An auction by another name, clogging the chain even more.
ICOs have recently lost popularity, but NFTs and NFT sales have risen in popularity. But the NFT space didn't learn from 2017; they do fixed-quantity sales just like ICOs (eg. see the mint function on lines 97-108 of this contract here). So what?
That's not the worst; some NFT sales have caused gas price spikes of up to 2000 gwei.
High gas prices from users fighting to get in first by sending higher and higher transaction fees. An auction renamed, pricing out all other applications on-chain for 15 minutes.
So why do sellers sometimes sell below market price?
Selling below market value is nothing new, and many articles, papers, and podcasts have written (and sometimes bitterly complained) about the unwillingness to use auctions or set prices to market-clearing levels.
Many of the arguments are the same for both blockchain (NFTs and ICOs) and non-blockchain examples (popular restaurants and concerts). Fairness and the desire not to exclude the poor, lose fans or create tension by being perceived as greedy are major concerns. The 1986 paper by Kahneman, Knetsch, and Thaler explains how fairness and greed can influence these decisions. I recall that the desire to avoid perceptions of greed was also a major factor in discouraging the use of auction-like mechanisms in 2017.
Aside from fairness concerns, there is the argument that selling out and long lines create a sense of popularity and prestige, making the product more appealing to others. Long lines should have the same effect as high prices in a rational actor model, but this is not the case in reality. This applies to ICOs and NFTs as well as restaurants. Aside from increasing marketing value, some people find the game of grabbing a limited set of opportunities first before everyone else is quite entertaining.
But there are some blockchain-specific factors. One argument for selling ICO tokens below market value (and one that persuaded the OmiseGo team to adopt their capped sale strategy) is community dynamics. The first rule of community sentiment management is to encourage price increases. People are happy if they are "in the green." If the price drops below what the community members paid, they are unhappy and start calling you a scammer, possibly causing a social media cascade where everyone calls you a scammer.
This effect can only be avoided by pricing low enough that post-launch market prices will almost certainly be higher. But how do you do this without creating a rush for the gates that leads to an auction?
Interesting solutions
It's 2021. We have a blockchain. The blockchain is home to a powerful decentralized finance ecosystem, as well as a rapidly expanding set of non-financial tools. The blockchain also allows us to reset social norms. Where decades of economists yelling about "efficiency" failed, blockchains may be able to legitimize new uses of mechanism design. If we could use our more advanced tools to create an approach that more directly solves the problems, with fewer side effects, wouldn't that be better than fiddling with a coarse-grained one-dimensional strategy space of selling at market price versus below market price?
Begin with the goals. We'll try to cover ICOs, NFTs, and conference tickets (really a type of NFT) all at the same time.
1. Fairness: don't completely exclude low-income people from participation; give them a chance. The goal of token sales is to avoid high initial wealth concentration and have a larger and more diverse initial token holder community.
2. Don’t create races: Avoid situations where many people rush to do the same thing and only a few get in (this is the type of situation that leads to the horrible auctions-by-another-name that we saw above).
3. Don't require precise market knowledge: the mechanism should work even if the seller has no idea how much demand exists.
4. Fun: The process of participating in the sale should be fun and game-like, but not frustrating.
5. Give buyers positive expected returns: in the case of a token (or an NFT), buyers should expect price increases rather than decreases. This requires selling below market value.
Let's start with (1). From Ethereum's perspective, there is a simple solution. Use a tool designed for the job: proof of personhood protocols! Here's one quick idea:
Mechanism 1 Each participant (verified by ID) can buy up to ‘’X’’ tokens at price P, with the option to buy more at an auction.
With the per-person mechanism, buyers can get positive expected returns for the portion sold through the per-person mechanism, and the auction part does not require sellers to understand demand levels. Is it race-free? The number of participants buying through the per-person pool appears to be high. But what if the per-person pool isn't big enough to accommodate everyone?
Make the per-person allocation amount dynamic.
Mechanism 2 Each participant can deposit up to X tokens into a smart contract to declare interest. Last but not least, each buyer receives min(X, N / buyers) tokens, where N is the total sold through the per-person pool (some other amount can also be sold by auction). The buyer gets their deposit back if it exceeds the amount needed to buy their allocation.
No longer is there a race condition based on the number of buyers per person. No matter how high the demand, it's always better to join sooner rather than later.
Here's another idea if you like clever game mechanics with fancy quadratic formulas.
Mechanism 3 Each participant can buy X units at a price P X 2 up to a maximum of C tokens per buyer. C starts low and gradually increases until enough units are sold.
The quantity allocated to each buyer is theoretically optimal, though post-sale transfers will degrade this optimality over time. Mechanisms 2 and 3 appear to meet all of the above objectives. They're not perfect, but they're good starting points.
One more issue. For fixed and limited supply NFTs, the equilibrium purchased quantity per participant may be fractional (in mechanism 2, number of buyers > N, and in mechanism 3, setting C = 1 may already lead to over-subscription). With fractional sales, you can offer lottery tickets: if there are N items available, you have a chance of N/number of buyers of getting the item, otherwise you get a refund. For a conference, groups could bundle their lottery tickets to guarantee a win or a loss. The certainty of getting the item can be auctioned.
The bottom tier of "sponsorships" can be used to sell conference tickets at market rate. You may end up with a sponsor board full of people's faces, but is that okay? After all, John Lilic was on EthCC's sponsor board!
Simply put, if you want to be reliably fair to people, you need an input that explicitly measures people. Authentication protocols do this (and if desired can be combined with zero knowledge proofs to ensure privacy). So we should combine the efficiency of market and auction-based pricing with the equality of proof of personhood mechanics.
Answers to possible questions
Q: Won't people who don't care about your project buy the item and immediately resell it?
A: Not at first. Meta-games take time to appear in practice. If they do, making them untradeable for a while may help mitigate the damage. Using your face to claim that your previous account was hacked and that your identity, including everything in it, should be moved to another account works because proof-of-personhood identities are untradeable.
Q: What if I want to make my item available to a specific community?
A: Instead of ID, use proof of participation tokens linked to community events. Another option, also serving egalitarian and gamification purposes, is to encrypt items within publicly available puzzle solutions.
Q: How do we know they'll accept? Strange new mechanisms have previously been resisted.
A: Having economists write screeds about how they "should" accept a new mechanism that they find strange is difficult (or even "equity"). However, abrupt changes in context effectively reset people's expectations. So the blockchain space is the best place to try this. You could wait for the "metaverse", but it's possible that the best version will run on Ethereum anyway, so start now.
More on Web3 & Crypto

Marco Manoppo
3 years ago
Failures of DCG and Genesis
Don't sleep with your own sister.
70% of lottery winners go broke within five years. You've heard the last one. People who got rich quickly without setbacks and hard work often lose it all. My father said, "Easy money is easily lost," and a wealthy friend who owns a family office said, "The first generation makes it, the second generation spends it, and the third generation blows it."
This is evident. Corrupt politicians in developing countries live lavishly, buying their third wives' fifth Hermès bag and celebrating New Year's at The Brando Resort. A successful businessperson from humble beginnings is more conservative with money. More so if they're atom-based, not bit-based. They value money.
Crypto can "feel" easy. I have nothing against capital market investing. The global financial system is shady, but that's another topic. The problem started when those who took advantage of easy money started affecting other businesses. VCs did minimal due diligence on FTX because they needed deal flow and returns for their LPs. Lenders did minimum diligence and underwrote ludicrous loans to 3AC because they needed revenue.
Alameda (hence FTX) and 3AC made "easy money" Genesis and DCG aren't. Their businesses are more conventional, but they underestimated how "easy money" can hurt them.
Genesis has been the victim of easy money hubris and insolvency, losing $1 billion+ to 3AC and $200M to FTX. We discuss the implications for the broader crypto market.
Here are the quick takeaways:
Genesis is one of the largest and most notable crypto lenders and prime brokerage firms.
DCG and Genesis have done related party transactions, which can be done right but is a bad practice.
Genesis owes DCG $1.5 billion+.
If DCG unwinds Grayscale's GBTC, $9-10 billion in BTC will hit the market.
DCG will survive Genesis.
What happened?
Let's recap the FTX shenanigan from two weeks ago. Shenanigans! Delphi's tweet sums up the craziness. Genesis has $175M in FTX.
Cred's timeline: I hate bad crisis management. Yes, admitting their balance sheet hole right away might've sparked more panic, and there's no easy way to convey your trouble, but no one ever learns.
By November 23, rumors circulated online that the problem could affect Genesis' parent company, DCG. To address this, Barry Silbert, Founder, and CEO of DCG released a statement to shareholders.
A few things are confirmed thanks to this statement.
DCG owes $1.5 billion+ to Genesis.
$500M is due in 6 months, and the rest is due in 2032 (yes, that’s not a typo).
Unless Barry raises new cash, his last-ditch efforts to repay the money will likely push the crypto market lower.
Half a year of GBTC fees is approximately $100M.
They can pay $500M with GBTC.
With profits, sell another port.
Genesis has hired a restructuring adviser, indicating it is in trouble.
Rehypothecation
Every crypto problem in the past year seems to be rehypothecation between related parties, excessive leverage, hubris, and the removal of the money printer. The Bankless guys provided a chart showing 2021 crypto yield.
In June 2022, @DataFinnovation published a great investigation about 3AC and DCG. Here's a summary.
3AC borrowed BTC from Genesis and pledged it to create Grayscale's GBTC shares.
3AC uses GBTC to borrow more money from Genesis.
This lets 3AC leverage their capital.
3AC's strategy made sense because GBTC had a premium, creating "free money."
GBTC's discount and LUNA's implosion caused problems.
3AC lost its loan money in LUNA.
Margin called on 3ACs' GBTC collateral.
DCG bought GBTC to avoid a systemic collapse and a larger discount.
Genesis lost too much money because 3AC can't pay back its loan. DCG "saved" Genesis, but the FTX collapse hurt Genesis further, forcing DCG and Genesis to seek external funding.
bruh…
Learning Experience
Co-borrowing. Unnecessary rehypothecation. Extra space. Governance disaster. Greed, hubris. Crypto has repeatedly shown it can recreate traditional financial system disasters quickly. Working in crypto is one of the best ways to learn crazy financial tricks people will do for a quick buck much faster than if you dabble in traditional finance.
Moving Forward
I think the crypto industry needs to consider its future. This is especially true for professionals. I'm not trying to scare you. In 2018 and 2020, I had doubts. No doubts now. Detailing the crypto industry's potential outcomes helped me gain certainty and confidence in its future. This includes VCs' benefits and talking points during the bull market, as well as what would happen if government regulations became hostile, etc. Even if that happens, I'm certain. This is permanent. I may write a post about that soon.
Sincerely,
M.

CNET
3 years ago
How a $300K Bored Ape Yacht Club NFT was accidentally sold for $3K
The Bored Ape Yacht Club is one of the most prestigious NFT collections in the world. A collection of 10,000 NFTs, each depicting an ape with different traits and visual attributes, Jimmy Fallon, Steph Curry and Post Malone are among their star-studded owners. Right now the price of entry is 52 ether, or $210,000.
Which is why it's so painful to see that someone accidentally sold their Bored Ape NFT for $3,066.
Unusual trades are often a sign of funny business, as in the case of the person who spent $530 million to buy an NFT from themselves. In Saturday's case, the cause was a simple, devastating "fat-finger error." That's when people make a trade online for the wrong thing, or for the wrong amount. Here the owner, real name Max or username maxnaut, meant to list his Bored Ape for 75 ether, or around $300,000. Instead he accidentally listed it for 0.75. One hundredth the intended price.
It was bought instantaneously. The buyer paid an extra $34,000 to speed up the transaction, ensuring no one could snap it up before them. The Bored Ape was then promptly listed for $248,000. The transaction appears to have been done by a bot, which can be coded to immediately buy NFTs listed below a certain price on behalf of their owners in order to take advantage of these exact situations.
"How'd it happen? A lapse of concentration I guess," Max told me. "I list a lot of items every day and just wasn't paying attention properly. I instantly saw the error as my finger clicked the mouse but a bot sent a transaction with over 8 eth [$34,000] of gas fees so it was instantly sniped before I could click cancel, and just like that, $250k was gone."
"And here within the beauty of the Blockchain you can see that it is both honest and unforgiving," he added.
Fat finger trades happen sporadically in traditional finance -- like the Japanese trader who almost bought 57% of Toyota's stock in 2014 -- but most financial institutions will stop those transactions if alerted quickly enough. Since cryptocurrency and NFTs are designed to be decentralized, you essentially have to rely on the goodwill of the buyer to reverse the transaction.
Fat finger errors in cryptocurrency trades have made many a headline over the past few years. Back in 2019, the company behind Tether, a cryptocurrency pegged to the US dollar, nearly doubled its own coin supply when it accidentally created $5 billion-worth of new coins. In March, BlockFi meant to send 700 Gemini Dollars to a set of customers, worth roughly $1 each, but mistakenly sent out millions of dollars worth of bitcoin instead. Last month a company erroneously paid a $24 million fee on a $100,000 transaction.
Similar incidents are increasingly being seen in NFTs, now that many collections have accumulated in market value over the past year. Last month someone tried selling a CryptoPunk NFT for $19 million, but accidentally listed it for $19,000 instead. Back in August, someone fat finger listed their Bored Ape for $26,000, an error that someone else immediately capitalized on. The original owner offered $50,000 to the buyer to return the Bored Ape -- but instead the opportunistic buyer sold it for the then-market price of $150,000.
"The industry is so new, bad things are going to happen whether it's your fault or the tech," Max said. "Once you no longer have control of the outcome, forget and move on."
The Bored Ape Yacht Club launched back in April 2021, with 10,000 NFTs being sold for 0.08 ether each -- about $190 at the time. While NFTs are often associated with individual digital art pieces, collections like the Bored Ape Yacht Club, which allow owners to flaunt their NFTs by using them as profile pictures on social media, are becoming increasingly prevalent. The Bored Ape Yacht Club has since become the second biggest NFT collection in the world, second only to CryptoPunks, which launched in 2017 and is considered the "original" NFT collection.
David Z. Morris
3 years ago
FTX's crash was no accident, it was a crime
Sam Bankman Fried (SDBF) is a legendary con man. But the NYT might not tell you that...
Since SBF's empire was revealed to be a lie, mainstream news organizations and commentators have failed to give readers a straightforward assessment. The New York Times and Wall Street Journal have uncovered many key facts about the scandal, but they have also soft-peddled Bankman-Fried's intent and culpability.
It's clear that the FTX crypto exchange and Alameda Research committed fraud to steal money from users and investors. That’s why a recent New York Times interview was widely derided for seeming to frame FTX’s collapse as the result of mismanagement rather than malfeasance. A Wall Street Journal article lamented FTX's loss of charitable donations, bolstering Bankman's philanthropic pose. Matthew Yglesias, court chronicler of the neoliberal status quo, seemed to whitewash his own entanglements by crediting SBF's money with helping Democrats in 2020 – sidestepping the likelihood that the money was embezzled.
Many outlets have called what happened to FTX a "bank run" or a "run on deposits," but Bankman-Fried insists the company was overleveraged and disorganized. Both attempts to frame the fallout obscure the core issue: customer funds misused.
Because banks lend customer funds to generate returns, they can experience "bank runs." If everyone withdraws at once, they can experience a short-term cash crunch but there won't be a long-term problem.
Crypto exchanges like FTX aren't banks. They don't do bank-style lending, so a withdrawal surge shouldn't strain liquidity. FTX promised customers it wouldn't lend or use their crypto.
Alameda's balance sheet blurs SBF's crypto empire.
The funds were sent to Alameda Research, where they were apparently gambled away. This is massive theft. According to a bankruptcy document, up to 1 million customers could be affected.
In less than a month, reporting and the bankruptcy process have uncovered a laundry list of decisions and practices that would constitute financial fraud if FTX had been a U.S.-regulated entity, even without crypto-specific rules. These ploys may be litigated in U.S. courts if they enabled the theft of American property.
The list is very, very long.
The many crimes of Sam Bankman-Fried and FTX
At the heart of SBF's fraud are the deep and (literally) intimate ties between FTX and Alameda Research, a hedge fund he co-founded. An exchange makes money from transaction fees on user assets, but Alameda trades and invests its own funds.
Bankman-Fried called FTX and Alameda "wholly separate" and resigned as Alameda's CEO in 2019. The two operations were closely linked. Bankman-Fried and Alameda CEO Caroline Ellison were romantically linked.
These circumstances enabled SBF's sin. Within days of FTX's first signs of weakness, it was clear the exchange was funneling customer assets to Alameda for trading, lending, and investing. Reuters reported on Nov. 12 that FTX sent $10 billion to Alameda. As much as $2 billion was believed to have disappeared after being sent to Alameda. Now the losses look worse.
It's unclear why those funds were sent to Alameda or when Bankman-Fried betrayed his depositors. On-chain analysis shows most FTX to Alameda transfers occurred in late 2021, and bankruptcy filings show both lost $3.7 billion in 2021.
SBF's companies lost millions before the 2022 crypto bear market. They may have stolen funds before Terra and Three Arrows Capital, which killed many leveraged crypto players.
FTT loans and prints
CoinDesk's report on Alameda's FTT holdings ignited FTX and Alameda Research. FTX created this instrument, but only a small portion was traded publicly; FTX and Alameda held the rest. These holdings were illiquid, meaning they couldn't be sold at market price. Bankman-Fried valued its stock at the fictitious price.
FTT tokens were reportedly used as collateral for loans, including FTX loans to Alameda. Close ties between FTX and Alameda made the FTT token harder or more expensive to use as collateral, reducing the risk to customer funds.
This use of an internal asset as collateral for loans between clandestinely related entities is similar to Enron's 1990s accounting fraud. These executives served 12 years in prison.
Alameda's margin liquidation exemption
Alameda Research had a "secret exemption" from FTX's liquidation and margin trading rules, according to legal filings by FTX's new CEO.
FTX, like other crypto platforms and some equity or commodity services, offered "margin" or loans for trades. These loans are usually collateralized, meaning borrowers put up other funds or assets. If a margin trade loses enough money, the exchange will sell the user's collateral to pay off the initial loan.
Keeping asset markets solvent requires liquidating bad margin positions. Exempting Alameda would give it huge advantages while exposing other FTX users to hidden risks. Alameda could have kept losing positions open while closing out competitors. Alameda could lose more on FTX than it could pay back, leaving a hole in customer funds.
The exemption is criminal in multiple ways. FTX was fraudulently marketed overall. Instead of a level playing field, there were many customers.
Above them all, with shotgun poised, was Alameda Research.
Alameda front-running FTX listings
Argus says there's circumstantial evidence that Alameda Research had insider knowledge of FTX's token listing plans. Alameda was able to buy large amounts of tokens before the listing and sell them after the price bump.
If true, these claims would be the most brazenly illegal of Alameda and FTX's alleged shenanigans. Even if the tokens aren't formally classified as securities, insider trading laws may apply.
In a similar case this year, an OpenSea employee was charged with wire fraud for allegedly insider trading. This employee faces 20 years in prison for front-running monkey JPEGs.
Huge loans to executives
Alameda Research reportedly lent FTX executives $4.1 billion, including massive personal loans. Bankman-Fried received $1 billion in personal loans and $2.3 billion for an entity he controlled, Paper Bird. Nishad Singh, director of engineering, was given $543 million, and FTX Digital Markets co-CEO Ryan Salame received $55 million.
FTX has more smoking guns than a Texas shooting range, but this one is the smoking bazooka – a sign of criminal intent. It's unclear how most of the personal loans were used, but liquidators will have to recoup the money.
The loans to Paper Bird were even more worrisome because they created another related third party to shuffle assets. Forbes speculates that some Paper Bird funds went to buy Binance's FTX stake, and Paper Bird committed hundreds of millions to outside investments.
FTX Inner Circle: Who's Who
That included many FTX-backed VC funds. Time will tell if this financial incest was criminal fraud. It fits Bankman-pattern Fried's of using secret flows, leverage, and funny money to inflate asset prices.
FTT or loan 'bailouts'
Also. As the crypto bear market continued in 2022, Bankman-Fried proposed bailouts for bankrupt crypto lenders BlockFi and Voyager Digital. CoinDesk was among those deceived, welcoming SBF as a J.P. Morgan-style sector backstop.
In a now-infamous interview with CNBC's "Squawk Box," Bankman-Fried referred to these decisions as bets that may or may not pay off.
But maybe not. Bloomberg's Matt Levine speculated that FTX backed BlockFi with FTT money. This Monopoly bailout may have been intended to hide FTX and Alameda liabilities that would have been exposed if BlockFi went bankrupt sooner. This ploy has no name, but it echoes other corporate frauds.
Secret bank purchase
Alameda Research invested $11.5 million in the tiny Farmington State Bank, doubling its net worth. As a non-U.S. entity and an investment firm, Alameda should have cleared regulatory hurdles before acquiring a U.S. bank.
In the context of FTX, the bank's stake becomes "ominous." Alameda and FTX could have done more shenanigans with bank control. Compare this to the Bank for Credit and Commerce International's failed attempts to buy U.S. banks. BCCI was even nefarious than FTX and wanted to buy U.S. banks to expand its money-laundering empire.
The mainstream's mistakes
These are complex and nuanced forms of fraud that echo traditional finance models. This obscurity helped Bankman-Fried masquerade as an honest player and likely kept coverage soft after the collapse.
Bankman-Fried had a scruffy, nerdy image, like Mark Zuckerberg and Adam Neumann. In interviews, he spoke nonsense about an industry full of jargon and complicated tech. Strategic donations and insincere ideological statements helped him gain political and social influence.
SBF' s'Effective' Altruism Blew Up FTX
Bankman-Fried has continued to muddy the waters with disingenuous letters, statements, interviews, and tweets since his con collapsed. He's tried to portray himself as a well-intentioned but naive kid who made some mistakes. This is a softer, more pernicious version of what Trump learned from mob lawyer Roy Cohn. Bankman-Fried doesn't "deny, deny, deny" but "confuse, evade, distort."
It's mostly worked. Kevin O'Leary, who plays an investor on "Shark Tank," repeats Bankman-SBF's counterfactuals. O'Leary called Bankman-Fried a "savant" and "probably one of the most accomplished crypto traders in the world" in a Nov. 27 interview with Business Insider, despite recent data indicating immense trading losses even when times were good.
O'Leary's status as an FTX investor and former paid spokesperson explains his continued affection for Bankman-Fried despite contradictory evidence. He's not the only one promoting Bankman-Fried. The disgraced son of two Stanford law professors will defend himself at Wednesday's DealBook Summit.
SBF's fraud and theft rival those of Bernie Madoff and Jho Low. Whether intentionally or through malign ineptitude, the fraud echoes Worldcom and Enron.
The Perverse Impacts of Anti-Money-Laundering
The principals in all of those scandals wound up either sentenced to prison or on the run from the law. Sam Bankman-Fried clearly deserves to share their fate.
Read the full article here.
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Mark Schaefer
2 years ago
20 Fun Uses for ChatGPT
Our RISE community is stoked on ChatGPT. ChatGPT has countless uses.
Early on. Companies are figuring out the legal and ethical implications of AI's content revolution. Using AI for everyday tasks is cool.
So I challenged RISE friends... Let's have fun and share non-obvious uses.
Onward!
1. Tweet
Jim MacLeod requested a design-themed Twitter thread from ChatGPT.
2. Novelize
Giuseppe Fratoni writes novels.
"This is amazing!" Impotent. I asked about writing, mystery novels, and jazz.
"Develop a mystery novel plot in which a disillusioned homicide detective hunts a serial killer who targets jazz musicians who play Autumn Leaves."
"I have:
Detective James Thompson is a seasoned veteran of the Homicide department, but lately he’s been feeling burnt out and disillusioned. His latest case, the murder of a young jazz pianist who was found brutally killed in his home, only serves to deepen his sense of despair … (much more provided)
3. Question-and-answer sessions
Bliss recommends:
You have a guest speaker and want to ask audience questions.
Pre-generate questions with ChatGPT. "And here's a question from our AI?"
The conference is about Western water scarcity. Water management expert. My AI question was...
Which desalination-related questions should I ask an expert?
ChatGPT said...
How is desalination currently being used around the world, and in what types of locations is it most effective?
What are the potential advantages and disadvantages of using desalination to provide fresh water?
What are some of the key challenges and limitations of desalination technology, and how are they being addressed?
4. Game-making
Richard's a board game expert. He suggests using ChatGPT to plan games. Note: Some people have started getting help solving crossword puzzle clues.
5. Matchmaking
Tanya Thompson thinks it helps dating. ChatGPT:
Here are some flirty first-message ideas for dating apps:
I noticed you from afar. I had to say hi and see if we clicked.
Your profile picture is gorgeous. I'm obsessed with your [Feature] and want to know you better.
I don't usually message first, but I had to. You're [Attractive Quality] and I can't wait to talk.”
Hello. Your profile intimidates me. I'm starstruck by your [Attractiveness]. (Many instances)
5. Solitude/anxiety
ChatGPT excels at one-on-one conversations.
PepperBrooks: "I'm sad and lonely."
ChatGPT: I’m sorry to hear that you’re feeling sad and lonely. It’s natural to feel down sometimes, but it’s important to remember that you’re not alone. There are many people who care about you and want to help you. It can be helpful to talk to someone about your feelings, whether it’s a close friend, family member, or mental health professional.
Sometimes, just expressing your thoughts and emotions to someone else can help to alleviate your sadness and loneliness. It’s also important to take care of yourself and do things that make you happy, such as spending time with loved ones, pursuing a hobby, or exercising. These things can help to improve your mood and make you feel more connected to others. Remember that you are strong and capable, and that you can get through this difficult time.
Daniel Nestle asked ChatGPT to generate journal prompts to help him deal with anxiety.
Write down the things that are causing you anxiety at the moment.
Describe a situation in which you felt anxious and how you coped with it.
Reflect on how your thoughts and beliefs contribute to your anxiety.
Write a letter to your anxiety, expressing your feelings and concerns
Imagine yourself in a calm and peaceful place, and describe it in detail.
(many more items followed)
6. Names
Continued Daniel:
Also, naming ideas.
Me: Name this drink. Japanese gin, unsweetened tonic, lime, Szechuan pepper, grapefruit.
ChatGPT: How about “Sakura Sunrise?” The name incorporates the Japanese gin and the citrus flavors of grapefruit and lime, and the word “sunrise” suggests a fresh and invigorating start to the day. Alternatively, you could go with something like “Peppered Grapefruit Gin Fizz” to emphasize the unique flavor combination of Szechuan pepper and grapefruit.
7. Translation on the go
Monks recommends: ChatGPT is a perfect mobile translation tool. Say you need help in Italy.
ME: Translate to Italian
Where is the nearest gas station?
ChatGPT: “La mia auto sta per esaurire il carburante, mi puoi dire dove si trova la stazione di servizio più vicina?”
8. Fitness
Monks added:
ME: In 3 months, I want to run 5km. Plan out how I can do this.
ChatGPT: Here's a 3-month plan to run 5km.
Start by walking for 15–20 minutes each day to build up your endurance and get your body used to regular exercise.
After a week of walking, begin incorporating short jogs into your routine. Start by jogging for 1–2 minutes at a time, with walking breaks in between. Gradually increase the length of your jogs and reduce the amount of time you spend walking.
Once you can jog for 10 minutes without stopping, start increasing the distance of your runs. Aim to run 1km without stopping and then gradually increase the distance over time.
In addition to your regular runs, incorporate strength training and stretching into your routine to improve your overall fitness and reduce the risk of injury.
(more details continued on)
9. Integrations and coding
10. Teacher lesson plans
Spencer Crandall saved time.
This morning, I wondered who has the hardest job. Teachers.
Many students, little time. ChatGPT could handle lesson planning. I tried it and got this.
Lesson Title: The History and Impact of Artificial Intelligence
Students will understand the history and development of AI and the potential positive and negative impacts on society.
AI timeline AI technologies and applications
Overview:
Introduce the topic of artificial intelligence, and explain that it refers to the development of computer systems and algorithms that can simulate human intelligence and behavior.
Show the timeline of significant events in the history of AI, and discuss the key milestones and developments in the field.
Show examples of AI technologies and applications, and explain how they are used in various industries and fields.
Discuss the potential positive and negative impacts of AI on society, including its potential to improve productivity, efficiency, and safety, as well as its potential to create new challenges and concerns, such as job displacement and ethical issues.
(many more details followed)
11. Find podcast guests.
Joeri Billast suggested:
Who should be on my Web3 podcast?
ChatGPT: Web3 marketing experts, influencers, and thought leaders make great podcast guests. These include Web3 marketers, content creators, business owners, entrepreneurs, and technologists. You could invite Web3 startups and organizations to your podcast.
Please give examples.
ChatGPT: Ideal Web3 marketing podcast guests include:
Tim Berner-Lee, inventor of the World Wide Web
Chris Dixon, general partner at Andreessen Horowitz
Vitalik Buterin, founder of Ethereum
Joe Lubin, founder of ConsenSys
Susan Fowler, author of Whistleblower
(many other suggestions)
12. Comments and reviews on social media
Lisa Monk thinks ChatGPT can help retail staff with social media.
She asked ChatGPT to "review this restaurant"
POSITIVE CUSTOMER REVIEW: I absolutely love this place. We eat out a lot however this place has topped it all. Perfect meals, amazing staff and the timing for it all was great! Special thanks to Sophie B (you rock) From your guests all the way from the Gold Coast, THANK YOU
ChatGPT REPLY: Thank you so much for your kind words and for taking the time to write a review. We are delighted to hear that you had such a great experience at our restaurant. We are thrilled that you enjoyed your meal and the service provided by Sophie. It’s always a pleasure to serve guests visiting from the Gold Coast and we are grateful for your support. We look forward to welcoming you back again soon. Thank you again for your positive review.
CUSTOMER REVIEW: Most average food, there is a nice view, But that’s about it
ChatGPT: Thank you for your review. We apologize if your dining experience was not up to your expectations. We strive to provide top-quality food and service to all of our customers, and we will take your feedback into consideration as we continue to improve. Thank you for letting us know about your experience.
13. Crime-fighting
Zack Seipert said, "I researched some famous unsolved murders, and ChatGPT laid out the crime, suspects, clues, and more." I bet experienced detectives could solve some of these cold cases.
14. Reduce bias
Joanne Taylor struggles to remove biases from her writing. She asked ChatGPT for ideas.
I asked ChatGPT to check a text for racial bias, and it did well.
15. Furnishings
I designed a small, unique table using ChatGPT and MidJourney. I edited ChatGPT's idea for clarity and brevity before entering it in MidJourney.
Results:
16. Serialize a novel
Scott Scowcoft led ChatCPT through iterations of a story text to create serialized novel frames. You can view this here.
17. Interview preparation
I was on a sales podcast. Although this is marketing-related, it's not my forte. I asked ChatGPT for help with a sales interview. Response:
Here are some interview questions about the future of sales and how to answer them.
How will technology affect sales in the future?
Technology will impact sales in the coming years. Automation and AI could be used to handle routine tasks, and data analysis and CRM could become more important. E-commerce and online sales channels are also reshaping the sales landscape.
How will the salesperson's role change?
Future sales roles may change in response to changing customer needs and expectations. Salespeople must be knowledgeable and consultative to help customers navigate complex products and services. Increasing importance of data analysis and CRM tools will require salespeople to understand and use technology effectively.
Future sales professionals will need what skills?
Future salespeople will need many skills. Sales professionals must have strong communication and interpersonal skills, as well as product and service knowledge and the ability to use data analysis and CRM tools effectively. Adapting to changing customer needs and staying current on industry trends will also be important for sales success.
18. Gift ideas
I need Christmas gift ideas for my wife. I asked:
Suggest a gift idea under $200 for a middle-aged woman who loves The Eagles.
A middle-aged woman who loves The Eagles might like a vinyl record of "Hotel California" or "The Long Run." Many music fans enjoy the unique sound and experience of vinyl records.
Pair the record with a high-quality record player for a complete gift. The vinyl record and record player should fit within your $200 budget for an Eagles fan.
19. Explaining complex concepts
I entered: Explain quantum physics to me as if I were 10 years old.
Quantum physics is a branch of science that studies how tiny particles, like atoms and subatomic particles, behave. These particles are so small that they don’t always follow the same rules as the things we can see and touch every day.
For example, sometimes they can be in two places at the same time, or they can be friends with each other even if they are far apart. This might sound strange, but it’s what scientists have learned from studying these tiny particles. Quantum physics helps us understand how the world works at a very small scale, and it can also help us make new technologies, like computers that are much faster than the ones we have today.
20. AP-style editing
Blogs, journals, and books follow AP Style. I asked ChatGPT to "edit using AP Style" and it did a great job.
And then... "Write a catchy headline for a blog post about 16 ChatGPT uses"
Here are some possible blog post titles for 20 creative ChatGPT uses:
“20 Fun and Creative Ways to Use ChatGPT: From Games to Quizzes and More”
“The Ultimate Guide to Using ChatGPT for Entertainment and Creativity”
“20 Reasons to Use ChatGPT: How it Can Enhance Your Gaming, Storytelling, and More”
20 Entertaining Uses for ChatGPT You Never Knew Were Possible”
“Unleash Your Imagination with ChatGPT: 16 Creative and Fun Ways to Use it”
In a previous post, I said ChatGPT will change marketing careers forever. I have never made a statement like that in my life. Even in the early days of the internet, people were cautious.
This technology was just released two weeks ago, and over a million people are already using it. This is the fastest technology adoption in history.
Today's post offers inventive and entertaining ideas, but it's just the beginning. ChatGPT writes code, music, and papers.

Jake Prins
3 years ago
What are NFTs 2.0 and what issues are they meant to address?
New standards help NFTs reach their full potential.
NFTs lack interoperability and functionality. They have great potential but are mostly speculative. To maximize NFTs, we need flexible smart contracts.
Current requirements are too restrictive.
Most NFTs are based on ERC-721, which makes exchanging them easy. CryptoKitties, a popular online game, used the 2017 standard to demonstrate NFTs' potential.
This simple standard includes a base URI and incremental IDs for tokens. Add the tokenID to the base URI to get the token's metadata.
This let creators collect NFTs. Many NFT projects store metadata on IPFS, a distributed storage network, but others use Google Drive. NFT buyers often don't realize that if the creators delete or move the files, their NFT is just a pointer.
This isn't the standard's biggest issue. There's no way to validate NFT projects.
Creators are one of the most important aspects of art, but nothing is stored on-chain.
ERC-721 contracts only have a name and symbol.
Most of the data on OpenSea's collection pages isn't from the NFT's smart contract. It was added through a platform input field, so it's in the marketplace's database. Other websites may have different NFT information.
In five years, your NFT will be just a name, symbol, and ID.
Your NFT doesn't mention its creators. Although the smart contract has a public key, it doesn't reveal who created it.
The NFT's creators and their reputation are crucial to its value. Think digital fashion and big brands working with well-known designers when more professionals use NFTs. Don't you want them in your NFT?
Would paintings be as valuable if their artists were unknown? Would you believe it's real?
Buying directly from an on-chain artist would reduce scams. Current standards don't allow this data.
Most creator profiles live on centralized marketplaces and could disappear. Current platforms have outpaced underlying standards. The industry's standards are lagging.
For NFTs to grow beyond pointers to a monkey picture file, we may need to use new Web3-based standards.
Introducing NFTs 2.0
Fabian Vogelsteller, creator of ERC-20, developed new web3 standards. He proposed LSP7 Digital Asset and LSP8 Identifiable Digital Asset, also called NFT 2.0.
NFT and token metadata inputs are extendable. Changes to on-chain metadata inputs allow NFTs to evolve. Instead of public keys, the contract can have Universal Profile addresses attached. These profiles show creators' faces and reputations. NFTs can notify asset receivers, automating smart contracts.
LSP7 and LSP8 use ERC725Y. Using a generic data key-value store gives contracts much-needed features:
The asset can be customized and made to stand out more by allowing for unlimited data attachment.
Recognizing changes to the metadata
using a hash reference for metadata rather than a URL reference
This base will allow more metadata customization and upgradeability. These guidelines are:
Genuine and Verifiable Now, the creation of an NFT by a specific Universal Profile can be confirmed by smart contracts.
Dynamic NFTs can update Flexible & Updatable Metadata, allowing certain things to evolve over time.
Protected metadata Now, secure metadata that is readable by smart contracts can be added indefinitely.
Better NFTS prevent the locking of NFTs by only being sent to Universal Profiles or a smart contract that can interact with them.
Summary
NFTS standards lack standardization and powering features, limiting the industry.
ERC-721 is the most popular NFT standard, but it only represents incremental tokenIDs without metadata or asset representation. No standard sender-receiver interaction or security measures ensure safe asset transfers.
NFT 2.0 refers to the new LSP7-DigitalAsset and LSP8-IdentifiableDigitalAsset standards.
They have new standards for flexible metadata, secure transfers, asset representation, and interactive transfer.
With NFTs 2.0 and Universal Profiles, creators could build on-chain reputations.
NFTs 2.0 could bring the industry's needed innovation if it wants to move beyond trading profile pictures for speculation.

Will Lockett
2 years ago
There Is A New EV King in Town
McMurtry Spéirling outperforms Tesla in speed and efficiency.
EVs were ridiculously slow for decades. However, the 2008 Tesla Roadster revealed that EVs might go extraordinarily fast. The Tesla Model S Plaid and Rimac Nevera are the fastest-accelerating road vehicles, despite combustion-engined road cars dominating the course. A little-known firm beat Tesla and Rimac in the 0-60 race, beat F1 vehicles on a circuit, and boasts a 350-mile driving range. The McMurtry Spéirling is completely insane.
Mat Watson of CarWow, a YouTube megastar, was recently handed a Spéirling and access to Silverstone Circuit (view video above). Mat ran a quarter-mile on Silverstone straight with former F1 driver Max Chilton. The little pocket-rocket automobile touched 100 mph in 2.7 seconds, completed the quarter mile in 7.97 seconds, and hit 0-60 in 1.4 seconds. When looking at autos quickly, 0-60 times can seem near. The Tesla Model S Plaid does 0-60 in 1.99 seconds, which is comparable to the Spéirling. Despite the meager statistics, the Spéirling is nearly 30% faster than Plaid!
My vintage VW Golf 1.4s has an 8.8-second 0-60 time, whereas a BMW Z4 3.0i is 30% faster (with a 0-60 time of 6 seconds). I tried to beat a Z4 off the lights in my Golf, but the Beamer flew away. If they challenge the Spéirling in a Model S Plaid, they'll feel as I did. Fast!
Insane quarter-mile drag time. Its road car record is 7.97 seconds. A Dodge Demon, meant to run extremely fast quarter miles, finishes so in 9.65 seconds, approximately 20% slower. The Rimac Nevera's 8.582-second quarter-mile record was miles behind drag racing. This run hampered the Spéirling. Because it was employing gearing that limited its top speed to 150 mph, it reached there in a little over 5 seconds without accelerating for most of the quarter mile! McMurtry can easily change the gearing, making the Spéirling run quicker.
McMurtry did this how? First, the Spéirling is a tiny single-seater EV with a 60 kWh battery pack, making it one of the lightest EVs ever. The 1,000-hp Spéirling has more than one horsepower per kg. The Nevera has 0.84 horsepower per kg and the Plaid 0.44.
However, you cannot simply construct a car light and power it. Instead of accelerating, it would spin. This makes the Spéirling a fan car. Its huge fans create massive downforce. These fans provide the Spéirling 2 tonnes of downforce while stationary, so you could park it on the ceiling. Its fast 0-60 time comes from its downforce, which lets it deliver all that power without wheel spin.
It also possesses complete downforce at all speeds, allowing it to tackle turns faster than even race vehicles. Spéirlings overcame VW IDRs and F1 cars to set the Goodwood Hill Climb record (read more here). The Spéirling is a dragstrip winner and track dominator, unlike the Plaid and Nevera.
The Spéirling is astonishing for a single-seater. Fan-generated downforce is more efficient than wings and splitters. It also means the vehicle has very minimal drag without the fan. The Spéirling can go 350 miles per charge (WLTP) or 20-30 minutes at full speed on a track despite its 60 kWh battery pack. The G-forces would hurt your neck before the battery died if you drove around a track for longer. The Spéirling can charge at over 200 kW in about 30 minutes. Thus, driving to track days, having fun, and returning is possible. Unlike other high-performance EVs.
Tesla, Rimac, or Lucid will struggle to defeat the Spéirling. They would need to build a fan automobile because adding power to their current vehicle would make it uncontrollable. The EV and automobile industries now have a new, untouchable performance king.
