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
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.

Franz Schrepf
3 years ago
What I Wish I'd Known About Web3 Before Building
Cryptoland rollercoaster
I've lost money in crypto.
Unimportant.
The real issue: I didn’t understand how.
I'm surrounded with winners. To learn more, I created my own NFTs, currency, and DAO.
Web3 is a hilltop castle. Everything is valuable, decentralized, and on-chain.
The castle is Disneyland: beautiful in images, but chaotic with lengthy lines and kids spending too much money on dressed-up animals.
When the throng and businesses are gone, Disneyland still has enchantment.
The Real Story of Web3
NFTs
Scarcity. Scarce NFTs. That's their worth.
Skull. Rare-looking!
Nonsense.
Bored Ape Yacht Club vs. my NFTs?
Marketing.
BAYC is amazing, but not for the reasons people believe. Apecoin and Otherside's art, celebrity following, and innovation? Stunning.
No other endeavor captured the zeitgeist better. Yet how long did you think it took to actually mint the NFTs?
1 hour? Maybe a week for the website?
Minting NFTs is incredibly easy. Kid-friendly. Developers are rare. Think about that next time somebody posts “DevS dO SMt!?”
NFTs will remain popular. These projects are like our Van Goghs and Monets. Still, be wary. It still uses exclusivity and wash selling like the OG art market.
Not all NFTs are art-related.
Soulbound and anonymous NFTs could offer up new use cases. Property rights, privacy-focused ID, open-source project verification. Everything.
NFTs build online trust through ownership.
We just need to evolve from the apes first.
NFTs' superpower is marketing until then.
Crypto currency
What the hell is a token?
99% of people are clueless.
So I invested in both coins and tokens. Same same. Only that they are not.
Coins have their own blockchain and developer/validator community. It's hard.
Creating a token on top of a blockchain? Five minutes.
Most consumers don’t understand the difference, creating an arbitrage opportunity: pretend you’re a serious project without having developers on your payroll.
Few market sites help. Take a look. See any tokens?
There's a hint one click deeper.
Some tokens are legitimate. Some coins are bad investments.
Tokens are utilized for DAO governance and DApp payments. Still, know who's behind a token. They might be 12 years old.
Coins take time and money. The recent LUNA meltdown indicates that currency investing requires research.
DAOs
Decentralized Autonomous Organizations (DAOs) don't work as you assume.
Yes, members can vote.
A productive organization requires more.
I've observed two types of DAOs.
Total decentralization total dysfunction
Centralized just partially. Community-driven.
A core team executes the DAO's strategy and roadmap in successful DAOs. The community owns part of the organization, votes on decisions, and holds the team accountable.
DAOs are public companies.
Amazing.
A shareholder meeting's logistics are staggering. DAOs may hold anonymous, secure voting quickly. No need for intermediaries like banks to chase up every shareholder.
Successful DAOs aren't totally decentralized. Large-scale voting and collaboration have never been easier.
And that’s all that matters.
Scale, speed.
My Web3 learnings
Disneyland is enchanting. Web3 too.
In a few cycles, NFTs may be used to build trust, not clout. Not speculating with coins. DAOs run organizations, not themselves.
Finally, some final thoughts:
NFTs will be a very helpful tool for building trust online. NFTs are successful now because of excellent marketing.
Tokens are not the same as coins. Look into any project before making a purchase. Make sure it isn't run by three 9-year-olds piled on top of one another in a trench coat, at the very least.
Not entirely decentralized, DAOs. We shall see a future where community ownership becomes the rule rather than the exception once we acknowledge this fact.
Crypto Disneyland is a rollercoaster with loops that make you sick.
Always buckle up.
Have fun!

Elnaz Sarraf
3 years ago
Why Bitcoin's Crash Could Be Good for Investors

The crypto market crashed in June 2022. Bitcoin and other cryptocurrencies hit their lowest prices in over a year, causing market panic. Some believe this crash will benefit future investors.
Before I discuss how this crash might help investors, let's examine why it happened. Inflation in the U.S. reached a 30-year high in 2022 after Russia invaded Ukraine. In response, the U.S. Federal Reserve raised interest rates by 0.5%, the most in almost 20 years. This hurts cryptocurrencies like Bitcoin. Higher interest rates make people less likely to invest in volatile assets like crypto, so many investors sold quickly.

The crypto market collapsed. Bitcoin, Ethereum, and Binance dropped 40%. Other cryptos crashed so hard they were delisted from almost every exchange. Bitcoin peaked in April 2022 at $41,000, but after the May interest rate hike, it crashed to $28,000. Bitcoin investors were worried. Even in bad times, this crash is unprecedented.
Bitcoin wasn't "doomed." Before the crash, LUNA was one of the top 5 cryptos by market cap. LUNA was trading around $80 at the start of May 2022, but after the rate hike?
Less than 1 cent. LUNA lost 99.99% of its value in days and was removed from every crypto exchange. Bitcoin's "crash" isn't as devastating when compared to LUNA.
Many people said Bitcoin is "due" for a LUNA-like crash and that the only reason it hasn't crashed is because it's bigger. Still false. If so, Bitcoin should be worth zero by now. We didn't. Instead, Bitcoin reached 28,000, then 29k, 30k, and 31k before falling to 18k. That's not the world's greatest recovery, but it shows Bitcoin's safety.
Bitcoin isn't falling constantly. It fell because of the initial shock of interest rates, but not further. Now, Bitcoin's value is more likely to rise than fall. Bitcoin's low price also attracts investors. They know what prices Bitcoin can reach with enough hype, and they want to capitalize on low prices before it's too late.

Bitcoin's crash was bad, but in a way it wasn't. To understand, consider 2021. In March 2021, Bitcoin surpassed $60k for the first time. Elon Musk's announcement in May that he would no longer support Bitcoin caused a massive crash in the crypto market. In May 2017, Bitcoin's price hit $29,000. Elon Musk's statement isn't worth more than the Fed raising rates. Many expected this big announcement to kill Bitcoin.

Not so. Bitcoin crashed from $58k to $31k in 2021. Bitcoin fell from $41k to $28k in 2022. This crash is smaller. Bitcoin's price held up despite tensions and stress, proving investors still believe in it. What happened after the initial crash in the past?
Bitcoin fell until mid-July. This is also something we’re not seeing today. After a week, Bitcoin began to improve daily. Bitcoin's price rose after mid-July. Bitcoin's price fluctuated throughout the rest of 2021, but it topped $67k in November. Despite no major changes, the peak occurred after the crash. Elon Musk seemed uninterested in crypto and wasn't likely to change his mind soon. What triggered this peak? Nothing, really. What really happened is that people got over the initial statement. They forgot.
Internet users have goldfish-like attention spans. People quickly forgot the crash's cause and were back investing in crypto months later. Despite the market's setbacks, more crypto investors emerged by the end of 2017. Who gained from these peaks? Bitcoin investors who bought low. Bitcoin not only recovered but also doubled its ROI. It was like a movie, and it shows us what to expect from Bitcoin in the coming months.
The current Bitcoin crash isn't as bad as the last one. LUNA is causing market panic. LUNA and Bitcoin are different cryptocurrencies. LUNA crashed because Terra wasn’t able to keep its peg with the USD. Bitcoin is unanchored. It's one of the most decentralized investments available. LUNA's distrust affected crypto prices, including Bitcoin, but it won't last forever.
This is why Bitcoin will likely rebound in the coming months. In 2022, people will get over the rise in interest rates and the crash of LUNA, just as they did with Elon Musk's crypto stance in 2021. When the world moves on to the next big controversy, Bitcoin's price will soar.
Bitcoin may recover for another reason. Like controversy, interest rates fluctuate. The Russian invasion caused this inflation. World markets will stabilize, prices will fall, and interest rates will drop.
Next, lower interest rates could boost Bitcoin's price. Eventually, it will happen. The U.S. economy can't sustain such high interest rates. Investors will put every last dollar into Bitcoin if interest rates fall again.
Bitcoin has proven to be a stable investment. This boosts its investment reputation. Even if Ethereum dethrones Bitcoin as crypto king one day (or any other crypto, for that matter). Bitcoin may stay on top of the crypto ladder for a while. We'll have to wait a few months to see if any of this is true.
This post is a summary. Read the full article here.
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M.G. Siegler
3 years ago
G3nerative
Generative AI hype: some thoughts
The sudden surge in "generative AI" startups and projects feels like the inverse of the recent "web3" boom. Both came from hyped-up pots. But while web3 hyped idealistic tech and an easy way to make money, generative AI hypes unsettling tech and questions whether it can be used to make money.
Web3 is technology looking for problems to solve, while generative AI is technology creating almost too many solutions. Web3 has been evangelists trying to solve old problems with new technology. As Generative AI evolves, users are resolving old problems in stunning new ways.
It's a jab at web3, but it's true. Web3's hype, including crypto, was unhealthy. Always expected a tech crash and shakeout. Tech that won't look like "web3" but will enhance "web2"
But that doesn't mean AI hype is healthy. There'll be plenty of bullshit here, too. As moths to a flame, hype attracts charlatans. Again, the difference is the different starting point. People want to use it. Try it.
With the beta launch of Dall-E 2 earlier this year, a new class of consumer product took off. Midjourney followed suit (despite having to jump through the Discord server hoops). Twelve more generative art projects. Lensa, Prisma Labs' generative AI self-portrait project, may have topped the hype (a startup which has actually been going after this general space for quite a while). This week, ChatGPT went off-topic.
This has a "fake-it-till-you-make-it" vibe. We give these projects too much credit because they create easy illusions. This also unlocks new forms of creativity. And faith in new possibilities.
As a user, it's thrilling. We're just getting started. These projects are not only fun to play with, but each week brings a new breakthrough. As an investor, it's all happening so fast, with so much hype (and ethical and societal questions), that no one knows how it will turn out. Web3's demand won't be the issue. Too much demand may cause servers to melt down, sending costs soaring. Companies will try to mix rapidly evolving tech to meet user demand and create businesses. Frustratingly difficult.
Anyway, I wanted an excuse to post some Lensa selfies.
These are really weird. I recognize them as me or a version of me, but I have no memory of them being taken. It's surreal, out-of-body. Uncanny Valley.

Bloomberg
3 years ago
Expulsion of ten million Ukrainians
According to recent data from two UN agencies, ten million Ukrainians have been displaced.
The International Organization for Migration (IOM) estimates nearly 6.5 million Ukrainians have relocated. Most have fled the war zones around Kyiv and eastern Ukraine, including Dnipro, Zhaporizhzhia, and Kharkiv. Most IDPs have fled to western and central Ukraine.
Since Russia invaded on Feb. 24, 3.6 million people have crossed the border to seek refuge in neighboring countries, according to the latest UN data. While most refugees have fled to Poland and Romania, many have entered Russia.
Internally displaced figures are IOM estimates as of March 19, based on 2,000 telephone interviews with Ukrainians aged 18 and older conducted between March 9-16. The UNHCR compiled the figures for refugees to neighboring countries on March 21 based on official border crossing data and its own estimates. The UNHCR's top-line total is lower than the country totals because Romania and Moldova totals include people crossing between the two countries.
Sources: IOM, UNHCR
According to IOM estimates based on telephone interviews with a representative sample of internally displaced Ukrainians, over 53% of those displaced are women, and over 60% of displaced households have children.

Yucel F. Sahan
3 years ago
How I Created the Day's Top Product on Product Hunt
In this article, I'll describe a weekend project I started to make something. It was Product Hunt's #1 of the Day, #2 Weekly, and #4 Monthly product.
How did I make Landing Page Checklist so simple? Building and launching took 3 weeks. I worked 3 hours a day max. Weekends were busy.
It's sort of a long story, so scroll to the bottom of the page to see what tools I utilized to create Landing Page Checklist :x
As a matter of fact, it all started with the startups-investments blog; Startup Bulletin, that I started writing in 2018. No, don’t worry, I won’t be going that far behind. The twitter account where I shared the blog posts of this newsletter was inactive for a looong time. I was holding this Twitter account since 2009, I couldn’t bear to destroy it. At the same time, I was thinking how to evaluate this account.
So I looked for a weekend assignment.
Weekend undertaking: Generate business names
Barash and I established a weekend effort to stay current. Building things helped us learn faster.
Simple. Startup Name Generator The utility generated random startup names. After market research for SEO purposes, we dubbed it Business Name Generator.
Backend developer Barash dislikes frontend work. He told me to write frontend code. Chakra UI and Tailwind CSS were recommended.
It was the first time I have heard about Tailwind CSS.
Before this project, I made mobile-web app designs in Sketch and shared them via Zeplin. I can read HTML-CSS or React code, but not write it. I didn't believe myself but followed Barash's advice.
My home page wasn't responsive when I started. Here it was:)
And then... Product Hunt had something I needed. Me-only! A website builder that gives you clean Tailwind CSS code and pre-made web components (like Elementor). Incredible.
I bought it right away because it was so easy to use. Best part: It's not just index.html. It includes all needed files. Like
postcss.config.js
README.md
package.json
among other things, tailwind.config.js
This is for non-techies.
Tailwind.build; which is Shuffle now, allows you to create and export projects for free (with limited features). You can try it by visiting their website.
After downloading the project, you can edit the text and graphics in Visual Studio (or another text editor). This HTML file can be hosted whenever.
Github is an easy way to host a landing page.
your project via Shuffle for export
your website's content, edit
Create a Gitlab, Github, or Bitbucket account.
to Github, upload your project folder.
Integrate Vercel with your Github account (or another platform below)
Allow them to guide you in steps.
Finally. If you push your code to Github using Github Desktop, you'll do it quickly and easily.
Speaking of; here are some hosting and serverless backend services for web applications and static websites for you host your landing pages for FREE!
I host landingpage.fyi on Vercel but all is fine. You can choose any platform below with peace in mind.
Vercel
Render
Netlify
After connecting your project/repo to Vercel, you don’t have to do anything on Vercel. Vercel updates your live website when you update Github Desktop. Wow!
Tails came out while I was using tailwind.build. Although it's prettier, tailwind.build is more mobile-friendly. I couldn't resist their lovely parts. Tails :)
Tails have several well-designed parts. Some components looked awful on mobile, but this bug helped me understand Tailwind CSS.
Unlike Shuffle, Tails does not include files when you export such as config.js, main.js, README.md. It just gives you the HTML code. Suffle.dev is a bit ahead in this regard and with mobile-friendly blocks if you ask me. Of course, I took advantage of both.
creativebusinessnames.co is inactive, but I'll leave a deployment link :)
Adam Wathan's YouTube videos and Tailwind's official literature helped me, but I couldn't have done it without Tails and Shuffle. These tools helped me make landing pages. I shouldn't have started over.
So began my Tailwind CSS adventure. I didn't build landingpage. I didn't plan it to be this long; sorry.
I learnt a lot while I was playing around with Shuffle and Tails Builders.
Long story short I built landingpage.fyi with the help of these tools;
Learning, building, and distribution
Shuffle (Started with a Shuffle Template)
Tails (Used components from here)
Sketch (to handle icons, logos, and .svg’s)
metatags.io (Auto Generator Meta Tags)
Vercel (Hosting)
Github Desktop (Pushing code to Github -super easy-)
Visual Studio Code (Edit my code)
Mailerlite (Capture Emails)
Jarvis / Conversion.ai (%90 of the text on website written by AI 😇 )
CookieHub (Consent Management)
That's all. A few things:
The Outcome
.fyi Domain: Why?
I'm often asked this.
I don't know, but I wanted to include the landing page term. Popular TLDs are gone. I saw my alternatives. brief and catchy.
CSS Tailwind Resources
I'll share project resources like Tails and Shuffle.
Beginner Tailwind (I lately enrolled in this course but haven’t completed it yet.)
Thanks for reading my blog's first post. Please share if you like it.
