More on NFTs & Art

Yogita Khatri
3 years ago
Moonbirds NFT sells for $1 million in first week
On Saturday, Moonbird #2642, one of the collection's rarest NFTs, sold for a record 350 ETH (over $1 million) on OpenSea.
The Sandbox, a blockchain-based gaming company based in Hong Kong, bought the piece. The seller, "oscuranft" on OpenSea, made around $600,000 after buying the NFT for 100 ETH a week ago.
Owl avatars
Moonbirds is a 10,000 owl NFT collection. It is one of the quickest collections to achieve bluechip status. Proof, a media startup founded by renowned VC Kevin Rose, launched Moonbirds on April 16.
Rose is currently a partner at True Ventures, a technology-focused VC firm. He was a Google Ventures general partner and has 1.5 million Twitter followers.
Rose has an NFT podcast on Proof. It follows Proof Collective, a group of 1,000 NFT collectors and artists, including Beeple, who hold a Proof Collective NFT and receive special benefits.
These include early access to the Proof podcast and in-person events.
According to the Moonbirds website, they are "the official Proof PFP" (picture for proof).
Moonbirds NFTs sold nearly $360 million in just over a week, according to The Block Research and Dune Analytics. Its top ten sales range from $397,000 to $1 million.
In the current market, Moonbirds are worth 33.3 ETH. Each NFT is 2.5 ETH. Holders have gained over 12 times in just over a week.
Why was it so popular?
The Block Research's NFT analyst, Thomas Bialek, attributes Moonbirds' rapid rise to Rose's backing, the success of his previous Proof Collective project, and collectors' preference for proven NFT projects.
Proof Collective NFT holders have made huge gains. These NFTs were sold in a Dutch auction last December for 5 ETH each. According to OpenSea, the current floor price is 109 ETH.
According to The Block Research, citing Dune Analytics, Proof Collective NFTs have sold over $39 million to date.
Rose has bigger plans for Moonbirds. Moonbirds is introducing "nesting," a non-custodial way for holders to stake NFTs and earn rewards.
Holders of NFTs can earn different levels of status based on how long they keep their NFTs locked up.
"As you achieve different nest status levels, we can offer you different benefits," he said. "We'll have in-person meetups and events, as well as some crazy airdrops planned."
Rose went on to say that Proof is just the start of "a multi-decade journey to build a new media company."
Matt Nutsch
3 years ago
Most people are unaware of how artificial intelligence (A.I.) is changing the world.
Recently, I saw an interesting social media post. In an entrepreneurship forum. A blogger asked for help because he/she couldn't find customers. I now suspect that the writer’s occupation is being disrupted by A.I.
Introduction
Artificial Intelligence (A.I.) has been a hot topic since the 1950s. With recent advances in machine learning, A.I. will touch almost every aspect of our lives. This article will discuss A.I. technology and its social and economic implications.
What's AI?
A computer program or machine with A.I. can think and learn. In general, it's a way to make a computer smart. Able to understand and execute complex tasks. Machine learning, NLP, and robotics are common types of A.I.
AI's global impact
AI will change the world, but probably faster than you think. A.I. already affects our daily lives. It improves our decision-making, efficiency, and productivity.
A.I. is transforming our lives and the global economy. It will create new business and job opportunities but eliminate others. Affected workers may face financial hardship.
AI examples:
OpenAI's GPT-3 text-generation
Developers can train, deploy, and manage models on GPT-3. It handles data preparation, model training, deployment, and inference for machine learning workloads. GPT-3 is easy to use for both experienced and new data scientists.
My team conducted an experiment. We needed to generate some blog posts for a website. We hired a blogger on Upwork. OpenAI created a blog post. The A.I.-generated blog post was of higher quality and lower cost.
MidjourneyAI's Art Contests
AI already affects artists. Artists use A.I. to create realistic 3D images and videos for digital art. A.I. is also used to generate new art ideas and methods.
MidjourneyAI and GigapixelAI won a contest last month. It's AI. created a beautiful piece of art that captured the contest's spirit. AI triumphs. It could open future doors.
After the art contest win, I registered to try out these new image generating A.I.s. In the MidjourneyAI chat forum, I noticed an artist's plea. The artist begged others to stop flooding RedBubble with AI-generated art.
Shutterstock and Getty Images have halted user uploads. AI-generated images flooded online marketplaces.
Imagining Videos with Meta
Meta released Make-a-Video this week. It's an A.I. app that creates videos from text. What you type creates a video.
This technology will impact TV, movies, and video games greatly. Imagine a movie or game that's personalized to your tastes. It's closer than you think.
Uses and Abuses of Deepfakes
Deepfake videos are computer-generated images of people. AI creates realistic images and videos of people.
Deepfakes are entertaining but have social implications. Porn introduced deepfakes in 2017. People put famous faces on porn actors and actresses without permission.
Soon, deepfakes were used to show dead actors/actresses or make them look younger. Carrie Fischer was included in films after her death using deepfake technology.
Deepfakes can be used to create fake news or manipulate public opinion, according to an AI.
Voices for Darth Vader and Iceman
James Earl Jones, who voiced Darth Vader, sold his voice rights this week. Aged actor won't be in those movies. Respeecher will use AI to mimic Jones's voice. This technology could change the entertainment industry. One actor can now voice many characters.
AI can generate realistic voice audio from text. Top Gun 2 actor Val Kilmer can't speak for medical reasons. Sonantic created Kilmer's voice from the movie script. This entertaining technology has social implications. It blurs authentic recordings and fake media.
Medical A.I. fights viruses
A team of Chinese scientists used machine learning to predict effective antiviral drugs last year. They started with a large dataset of virus-drug interactions. Researchers combined that with medication and virus information. Finally, they used machine learning to predict effective anti-virus medicines. This technology could solve medical problems.
AI ideas AI-generated Itself
OpenAI's GPT-3 predicted future A.I. uses. Here's what it told me:
AI will affect the economy. Businesses can operate more efficiently and reinvest resources with A.I.-enabled automation. AI can automate customer service tasks, reducing costs and improving satisfaction.
A.I. makes better pricing, inventory, and marketing decisions. AI automates tasks and makes decisions. A.I.-powered robots could help the elderly or disabled. Self-driving cars could reduce accidents.
A.I. predictive analytics can predict stock market or consumer behavior trends and patterns. A.I. also personalizes recommendations. sways. A.I. recommends products and movies. AI can generate new ideas based on data analysis.
Conclusion
A.I. will change business as it becomes more common. It will change how we live and work by creating growth and prosperity.
Exciting times, but also one which should give us all pause. Technology can be good or evil. We must use new technologies ethically, fairly, and honestly.
“The author generated some sentences in this text in part with GPT-3, OpenAI’s large-scale language-generation model. Upon generating draft language, the author reviewed, edited, and revised the language to their own liking and takes ultimate responsibility for the content of this publication. The text of this post was further edited using HemingWayApp. Many of the images used were generated using A.I. as described in the captions.”

middlemarch.eth
3 years ago
ERC721R: A new ERC721 contract for random minting so people don’t snipe all the rares!
That is, how to snipe all the rares without using ERC721R!
Introduction: Blessed and Lucky
Mphers was the first mfers derivative, and as a Phunks derivative, I wanted one.
I wanted an alien. And there are only 8 in the 6,969 collection. I got one!
In case it wasn't clear from the tweet, I meant that I was lucky to have figured out how to 100% guarantee I'd get an alien without any extra luck.
Read on to find out how I did it, how you can too, and how developers can avoid it!
How to make rare NFTs without luck.
# How to mint rare NFTs without needing luck
The key to minting a rare NFT is knowing the token's id ahead of time.
For example, once I knew my alien was #4002, I simply refreshed the mint page until #3992 was minted, and then mint 10 mphers.
How did I know #4002 was extraterrestrial? Let's go back.
First, go to the mpher contract's Etherscan page and look up the tokenURI of a previously issued token, token #1:
As you can see, mphers creates metadata URIs by combining the token id and an IPFS hash.
This method gives you the collection's provenance in every URI, and while that URI can be changed, it affects everyone and is public.
Consider a token URI without a provenance hash, like https://mphers.art/api?tokenId=1.
As a collector, you couldn't be sure the devs weren't changing #1's metadata at will.
The API allows you to specify “if #4002 has not been minted, do not show any information about it”, whereas IPFS does not allow this.
It's possible to look up the metadata of any token, whether or not it's been minted.
Simply replace the trailing “1” with your desired id.
Mpher #4002
These files contain all the information about the mpher with the specified id. For my alien, we simply search all metadata files for the string “alien mpher.”
Take a look at the 6,969 meta-data files I'm using OpenSea's IPFS gateway, but you could use ipfs.io or something else.
Use curl to download ten files at once. Downloading thousands of files quickly can lead to duplicates or errors. But with a little tweaking, you should be able to get everything (and dupes are fine for our purposes).
Now that you have everything in one place, grep for aliens:
The numbers are the file names that contain “alien mpher” and thus the aliens' ids.
The entire process takes under ten minutes. This technique works on many NFTs currently minting.
In practice, manually minting at the right time to get the alien is difficult, especially when tokens mint quickly. Then write a bot to poll totalSupply() every second and submit the mint transaction at the exact right time.
You could even look for the token you need in the mempool before it is minted, and get your mint into the same block!
However, in my experience, the “big” approach wins 95% of the time—but not 100%.
“Am I being set up all along?”
Is a question you might ask yourself if you're new to this.
It's disheartening to think you had no chance of minting anything that someone else wanted.
But, did you have no opportunity? You had an equal chance as everyone else!
Take me, for instance: I figured this out using open-source tools and free public information. Anyone can do this, and not understanding how a contract works before minting will lead to much worse issues.
The mpher mint was fair.
While a fair game, “snipe the alien” may not have been everyone's cup of tea.
People may have had more fun playing the “mint lottery” where tokens were distributed at random and no one could gain an advantage over someone simply clicking the “mint” button.
How might we proceed?
Minting For Fashion Hats Punks, I wanted to create a random minting experience without sacrificing fairness. In my opinion, a predictable mint beats an unfair one. Above all, participants must be equal.
Sadly, the most common method of creating a random experience—the post-mint “reveal”—is deeply unfair. It works as follows:
- During the mint, token metadata is unavailable. Instead, tokenURI() returns a blank JSON file for each id.
- An IPFS hash is updated once all tokens are minted.
- You can't tell how the contract owner chose which token ids got which metadata, so it appears random.
Because they alone decide who gets what, the person setting the metadata clearly has a huge unfair advantage over the people minting. Unlike the mpher mint, you have no chance of winning here.
But what if it's a well-known, trusted, doxxed dev team? Are reveals okay here?
No! No one should be trusted with such power. Even if someone isn't consciously trying to cheat, they have unconscious biases. They might also make a mistake and not realize it until it's too late, for example.
You should also not trust yourself. Imagine doing a reveal, thinking you did it correctly (nothing is 100%! ), and getting the rarest NFT. Isn't that a tad odd Do you think you deserve it? An NFT developer like myself would hate to be in this situation.
Reveals are bad*
UNLESS they are done without trust, meaning everyone can verify their fairness without relying on the developers (which you should never do).
An on-chain reveal powered by randomness that is verifiably outside of anyone's control is the most common way to achieve a trustless reveal (e.g., through Chainlink).
Tubby Cats did an excellent job on this reveal, and I highly recommend their contract and launch reflections. Their reveal was also cool because it was progressive—you didn't have to wait until the end of the mint to find out.
In his post-launch reflections, @DefiLlama stated that he made the contract as trustless as possible, removing as much trust as possible from the team.
In my opinion, everyone should know the rules of the game and trust that they will not be changed mid-stream, while trust minimization is critical because smart contracts were designed to reduce trust (and it makes it impossible to hack even if the team is compromised). This was a huge mistake because it limited our flexibility and our ability to correct mistakes.
And @DefiLlama is a superstar developer. Imagine how much stress maximizing trustlessness will cause you!
That leaves me with a bad solution that works in 99 percent of cases and is much easier to implement: random token assignments.
Introducing ERC721R: A fully compliant IERC721 implementation that picks token ids at random.
ERC721R implements the opposite of a reveal: we mint token ids randomly and assign metadata deterministically.
This allows us to reveal all metadata prior to minting while reducing snipe chances.
Then import the contract and use this code:
What is ERC721R and how does it work
First, a disclaimer: ERC721R isn't truly random. In this sense, it creates the same “game” as the mpher situation, where minters compete to exploit the mint. However, ERC721R is a much more difficult game.
To game ERC721R, you need to be able to predict a hash value using these inputs:
This is impossible for a normal person because it requires knowledge of the block timestamp of your mint, which you do not have.
To do this, a miner must set the timestamp to a value in the future, and whatever they do is dependent on the previous block's hash, which expires in about ten seconds when the next block is mined.
This pseudo-randomness is “good enough,” but if big money is involved, it will be gamed. Of course, the system it replaces—predictable minting—can be manipulated.
The token id is chosen in a clever implementation of the Fisher–Yates shuffle algorithm that I copied from CryptoPhunksV2.
Consider first the naive solution: (a 10,000 item collection is assumed):
- Make an array with 0–9999.
- To create a token, pick a random item from the array and use that as the token's id.
- Remove that value from the array and shorten it by one so that every index corresponds to an available token id.
This works, but it uses too much gas because changing an array's length and storing a large array of non-zero values is expensive.
How do we avoid them both? What if we started with a cheap 10,000-zero array? Let's assign an id to each index in that array.
Assume we pick index #6500 at random—#6500 is our token id, and we replace the 0 with a 1.
But what if we chose #6500 again? A 1 would indicate #6500 was taken, but then what? We can't just "roll again" because gas will be unpredictable and high, especially later mints.
This allows us to pick a token id 100% of the time without having to keep a separate list. Here's how it works:
- Make a 10,000 0 array.
- Create a 10,000 uint numAvailableTokens.
- Pick a number between 0 and numAvailableTokens. -1
- Think of #6500—look at index #6500. If it's 0, the next token id is #6500. If not, the value at index #6500 is your next token id (weird!)
- Examine the array's last value, numAvailableTokens — 1. If it's 0, move the value at #6500 to the end of the array (#9999 if it's the first token). If the array's last value is not zero, update index #6500 to store it.
- numAvailableTokens is decreased by 1.
- Repeat 3–6 for the next token id.
So there you go! The array stays the same size, but we can choose an available id reliably. The Solidity code is as follows:
Unfortunately, this algorithm uses more gas than the leading sequential mint solution, ERC721A.
This is most noticeable when minting multiple tokens in one transaction—a 10 token mint on ERC721R costs 5x more than on ERC721A. That said, ERC721A has been optimized much further than ERC721R so there is probably room for improvement.
Conclusion
Listed below are your options:
- ERC721A: Minters pay lower gas but must spend time and energy devising and executing a competitive minting strategy or be comfortable with worse minting results.
- ERC721R: Higher gas, but the easy minting strategy of just clicking the button is optimal in all but the most extreme cases. If miners game ERC721R it’s the worst of both worlds: higher gas and a ton of work to compete.
- ERC721A + standard reveal: Low gas, but not verifiably fair. Please do not do this!
- ERC721A + trustless reveal: The best solution if done correctly, highly-challenging for dev, potential for difficult-to-correct errors.
Did I miss something? Comment or tweet me @dumbnamenumbers.
Check out the code on GitHub to learn more! Pull requests are welcome—I'm sure I've missed many gas-saving opportunities.
Thanks!
Read the original post here
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Jan-Patrick Barnert
3 years ago
Wall Street's Bear Market May Stick Around
If history is any guide, this bear market might be long and severe.
This is the S&P 500 Index's fourth such incident in 20 years. The last bear market of 2020 was a "shock trade" caused by the Covid-19 pandemic, although earlier ones in 2000 and 2008 took longer to bottom out and recover.
Peter Garnry, head of equities strategy at Saxo Bank A/S, compares the current selloff to the dotcom bust of 2000 and the 1973-1974 bear market marked by soaring oil prices connected to an OPEC oil embargo. He blamed high tech valuations and the commodity crises.
"This drop might stretch over a year and reach 35%," Garnry wrote.
Here are six bear market charts.
Time/depth
The S&P 500 Index plummeted 51% between 2000 and 2002 and 58% during the global financial crisis; it took more than 1,000 trading days to recover. The former took 638 days to reach a bottom, while the latter took 352 days, suggesting the present selloff is young.
Valuations
Before the tech bubble burst in 2000, valuations were high. The S&P 500's forward P/E was 25 times then. Before the market fell this year, ahead values were near 24. Before the global financial crisis, stocks were relatively inexpensive, but valuations dropped more than 40%, compared to less than 30% now.
Earnings
Every stock crash, especially earlier bear markets, returned stocks to fundamentals. The S&P 500 decouples from earnings trends but eventually recouples.
Support
Central banks won't support equity investors just now. The end of massive monetary easing will terminate a two-year bull run that was among the strongest ever, and equities may struggle without cheap money. After years of "don't fight the Fed," investors must embrace a new strategy.
Bear Haunting Bear
If the past is any indication, rising government bond yields are bad news. After the financial crisis, skyrocketing rates and a falling euro pushed European stock markets back into bear territory in 2011.
Inflation/rates
The current monetary policy climate differs from past bear markets. This is the first time in a while that markets face significant inflation and rising rates.
This post is a summary. Read full article here

Enrique Dans
2 years ago
When we want to return anything, why on earth do stores still require a receipt?
A friend told me of an incident she found particularly irritating: a retailer where she is a frequent client, with an account and loyalty card, asked for the item's receipt.
We all know that stores collect every bit of data they can on us, including our socio-demographic profile, address, shopping habits, and everything we've ever bought, so why would they need a fading receipt? Who knows? That their consumers try to pass off other goods? It's easy to verify past transactions to see when the item was purchased.
That's it. Why require receipts? Companies send us incentives, discounts, and other marketing, yet when we need something, we have to prove we're not cheating.
Why require us to preserve data and documents when our governments and governmental institutions already have them? Why do I need to carry documents like my driver's license if the authorities can check if I have one and what state it's in once I prove my identity?
We shouldn't be required to give someone data or documents they already have. The days of waiting up with our paperwork for a stern official to inform us something is missing are over.
How can retailers still ask if you have a receipt if we've made our slow, bureaucratic, and all-powerful government sensible? Then what? The shop may not accept your return (which has a two-year window, longer than most purchase tickets last) or they may just let you replace the item.
Isn't this an anachronism in the age of CRMs, customer files that know what we ate for breakfast, and loyalty programs? If government and bureaucracies have learnt to use its own files and make life easier for the consumer, why do retailers ask for a receipt?
They're adding friction to the system. They know we can obtain a refund, use our warranty, or get our money back. But if I ask for ludicrous criteria, like keeping the purchase receipt in your wallet (wallet? another anachronism, if I leave the house with only my smartphone! ), it will dissuade some individuals and tip the scales in their favor when it comes to limiting returns. Some manager will take credit for lowering returns and collect her annual bonus. Having the wrong metrics is common in management.
To slow things down, asking for a receipt is like asking us to perform a handstand and leap 20 times on one foot. You have my information, use it to send me everything, and know everything I've bought, yet when I need a two-way service, you refuse to utilize it and require that I keep it and prove it.
Refuse as customers. If retailers want our business, they should treat us well, not just when we spend money. If I come to return a product, claim its use or warranty, or be taught how to use it, I am the same person you treated wonderfully when I bought it. Remember that, and act accordingly.
A store should use my information for everything, not just what it wants. Keep my info, but don't sell me anything.

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.
