More on NFTs & Art
Stephen Moore
3 years ago
Trading Volume on OpenSea Drops by 99% as the NFT Boom Comes to an End
Wasn't that a get-rich-quick scheme?
OpenSea processed $2.7 billion in NFT transactions in May 2021.
Fueled by a crypto bull run, rumors of unfathomable riches, and FOMO, Bored Apes, Crypto Punks, and other JPEG-format trash projects flew off the virtual shelves, snatched up by retail investors and celebrities alike.
Over a year later, those shelves are overflowing and warehouses are backlogged. Since March, I've been writing less. In May and June, the bubble was close to bursting.
Apparently, the boom has finally peaked.
This bubble has punctured, and deflation has begun. On Aug. 28, OpenSea processed $9.34 million.
From that euphoric high of $2.7 billion, $9.34 million represents a spectacular decline of 99%.
OpenSea contradicts the data. A trading platform spokeswoman stated the comparison is unfair because it compares the site's highest and lowest trading days. They're the perfect two data points to assess the drop. OpenSea chooses to use ETH volume measures, which ignore crypto's shifting price. Since January 2022, monthly ETH volume has dropped 140%, according to Dune.
Unconvincing counterargument.
Further OpenSea indicators point to declining NFT demand:
Since January 2022, daily user visits have decreased by 50%.
Daily transactions have decreased by 50% since the beginning of the year in the same manner.
Off-platform, the floor price of Bored Apes has dropped from 145 ETH to 77 ETH. (At $4,800, a reduction from $700,000 to $370,000). Google search data shows waning popular interest.
It is a trend that will soon vanish, just like laser eyes.
NFTs haven't moved since the new year. Eminem and Snoop Dogg can utilize their apes in music videos or as 3D visuals to perform at the VMAs, but the reality is that NFTs have lost their public appeal and the market is trying to regain its footing.
They've lost popularity because?
Breaking records. The technology still lacks genuine use cases a year and a half after being popular.
They're pricey prestige symbols that have made a few people rich through cunning timing or less-than-savory scams or rug pulling. Over $10.5 billion has been taken through frauds, most of which are NFT enterprises promising to be the next Bored Apes, according to Web3 is going wonderfully. As the market falls, many ordinary investors realize they purchased into a self-fulfilling ecosystem that's halted. Many NFTs are sold between owner-held accounts to boost their price, data suggests. Most projects rely on social media excitement to debut with a high price before the first owners sell and chuckle to the bank. When they don't, the initiative fails, leaving investors high and dry.
NFTs are fading like laser eyes. Most people pushing the technology don't believe in it or the future it may bring. No, they just need a Kool-Aid-drunk buyer.
Everybody wins. When your JPEGs are worth 99% less than when you bought them, you've lost.
When demand reaches zero, many will lose.
1eth1da
3 years ago
6 Rules to build a successful NFT Community in 2022
Too much NFT, Discord, and shitposting.
How do you choose?
How do you recruit more members to join your NFT project?
In 2021, a successful NFT project required:
Monkey/ape artwork
Twitter and Discord bot-filled
Roadmap overpromise
Goal was quick cash.
2022 and the years after will change that.
These are 6 Rules for a Strong NFT Community in 2022:
THINK LONG TERM
This relates to roadmap planning. Hype and dumb luck may drive NFT projects (ahem, goblins) but rarely will your project soar.
Instead, consider sustainability.
Plan your roadmap based on your team's abilities.
Do what you're already doing, but with NFTs, make it bigger and better.
You shouldn't copy a project's roadmap just because it was profitable.
This will lead to over-promising, team burnout, and an RUG NFT project.
OFFER VALUE
Building a great community starts with giving.
Why are musicians popular?
Because they offer entertainment for everyone, a random person becomes a fan, and more fans become a cult.
That's how you should approach your community.
TEAM UP
A great team helps.
An NFT project could have 3 or 2 people.
Credibility trumps team size.
Make sure your team can answer community questions, resolve issues, and constantly attend to them.
Don't overwork and burn out.
Your community will be able to recognize that you are trying too hard and give up on the project.
BUILD A GREAT PRODUCT
Bored Ape Yacht Club altered the NFT space.
Cryptopunks transformed NFTs.
Many others did, including Okay Bears.
What made them that way?
Because they answered a key question.
What is my NFT supposed to be?
Before planning art, this question must be answered.
NFTs can't be just jpegs.
What does it represent?
Is it a Metaverse-ready project?
What blockchain are you going to be using and why?
Set some ground rules for yourself. This helps your project's direction.
These questions will help you and your team set a direction for blockchain, NFT, and Web3 technology.
EDUCATE ON WEB3
The more the team learns about Web3 technology, the more they can offer their community.
Think tokens, metaverse, cross-chain interoperability and more.
BUILD A GREAT COMMUNITY
Several projects mistreat their communities.
They treat their community like "customers" and try to sell them NFT.
Providing Whitelists and giveaways aren't your only community-building options.
Think bigger.
Consider them family and friends, not wallets.
Consider them fans.
These are some tips to start your NFT project.
Jim Clyde Monge
3 years ago
Can You Sell Images Created by AI?
Some AI-generated artworks sell for enormous sums of money.
But can you sell AI-Generated Artwork?
Simple answer: yes.
However, not all AI services enable allow usage and redistribution of images.
Let's check some of my favorite AI text-to-image generators:
Dall-E2 by OpenAI
The AI art generator Dall-E2 is powerful. Since it’s still in beta, you can join the waitlist here.
OpenAI DOES NOT allow the use and redistribution of any image for commercial purposes.
Here's the policy as of April 6, 2022.
Here are some images from Dall-E2’s webpage to show its art quality.
Several Reddit users reported receiving pricing surveys from OpenAI.
This suggests the company may bring out a subscription-based tier and a commercial license to sell images soon.
MidJourney
I like Midjourney's art generator. It makes great AI images. Here are some samples:
Standard Licenses are available for $10 per month.
Standard License allows you to use, copy, modify, merge, publish, distribute, and/or sell copies of the images, except for blockchain technologies.
If you utilize or distribute the Assets using blockchain technology, you must pay MidJourney 20% of revenue above $20,000 a month or engage in an alternative agreement.
Here's their copyright and trademark page.
Dream by Wombo
Dream is one of the first public AI art generators.
This AI program is free, easy to use, and Wombo gives a royalty-free license to copy or share artworks.
Users own all artworks generated by the tool. Including all related copyrights or intellectual property rights.
Here’s Wombos' intellectual property policy.
Final Reflections
AI is creating a new sort of art that's selling well. It’s becoming popular and valued, despite some skepticism.
Now that you know MidJourney and Wombo let you sell AI-generated art, you need to locate buyers. There are several ways to achieve this, but that’s for another story.
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Sam Hickmann
3 years ago
Improving collaboration with the Six Thinking Hats
Six Thinking Hats was written by Dr. Edward de Bono. "Six Thinking Hats" and parallel thinking allow groups to plan thinking processes in a detailed and cohesive way, improving collaboration.
Fundamental ideas
In order to develop strategies for thinking about specific issues, the method assumes that the human brain thinks in a variety of ways that can be intentionally challenged. De Bono identifies six brain-challenging directions. In each direction, the brain brings certain issues into conscious thought (e.g. gut instinct, pessimistic judgement, neutral facts). Some may find wearing hats unnatural, uncomfortable, or counterproductive.
The example of "mismatch" sensitivity is compelling. In the natural world, something out of the ordinary may be dangerous. This mode causes negative judgment and critical thinking.
Colored hats represent each direction. Putting on a colored hat symbolizes changing direction, either literally or metaphorically. De Bono first used this metaphor in his 1971 book "Lateral Thinking for Management" to describe a brainstorming framework. These metaphors allow more complete and elaborate thought separation. Six thinking hats indicate ideas' problems and solutions.
Similarly, his CoRT Thinking Programme introduced "The Five Stages of Thinking" method in 1973.
| HAT | OVERVIEW | TECHNIQUE |
|---|---|---|
| BLUE | "The Big Picture" & Managing | CAF (Consider All Factors); FIP (First Important Priorities) |
| WHITE | "Facts & Information" | Information |
| RED | "Feelings & Emotions" | Emotions and Ego |
| BLACK | "Negative" | PMI (Plus, Minus, Interesting); Evaluation |
| YELLOW | "Positive" | PMI |
| GREEN | "New Ideas" | Concept Challenge; Yes, No, Po |
Strategies and programs
After identifying the six thinking modes, programs can be created. These are groups of hats that encompass and structure the thinking process. Several of these are included in the materials for franchised six hats training, but they must often be adapted. Programs are often "emergent," meaning the group plans the first few hats and the facilitator decides what to do next.
The group agrees on how to think, then thinks, then evaluates the results and decides what to do next. Individuals or groups can use sequences (and indeed hats). Each hat is typically used for 2 minutes at a time, although an extended white hat session is common at the start of a process to get everyone on the same page. The red hat is recommended to be used for a very short period to get a visceral gut reaction – about 30 seconds, and in practice often takes the form of dot-voting.
| ACTIVITY | HAT SEQUENCE |
|---|---|
| Initial Ideas | Blue, White, Green, Blue |
| Choosing between alternatives | Blue, White, (Green), Yellow, Black, Red, Blue |
| Identifying Solutions | Blue, White, Black, Green, Blue |
| Quick Feedback | Blue, Black, Green, Blue |
| Strategic Planning | Blue, Yellow, Black, White, Blue, Green, Blue |
| Process Improvement | Blue, White, White (Other People's Views), Yellow, Black, Green, Red, Blue |
| Solving Problems | Blue, White, Green, Red, Yellow, Black, Green, Blue |
| Performance Review | Blue, Red, White, Yellow, Black, Green, Blue |
Use
Speedo's swimsuit designers reportedly used the six thinking hats. "They used the "Six Thinking Hats" method to brainstorm, with a green hat for creative ideas and a black one for feasibility.
Typically, a project begins with extensive white hat research. Each hat is used for a few minutes at a time, except the red hat, which is limited to 30 seconds to ensure an instinctive gut reaction, not judgement. According to Malcolm Gladwell's "blink" theory, this pace improves thinking.
De Bono believed that the key to a successful Six Thinking Hats session was focusing the discussion on a particular approach. A meeting may be called to review and solve a problem. The Six Thinking Hats method can be used in sequence to explore the problem, develop a set of solutions, and choose a solution through critical examination.
Everyone may don the Blue hat to discuss the meeting's goals and objectives. The discussion may then shift to Red hat thinking to gather opinions and reactions. This phase may also be used to determine who will be affected by the problem and/or solutions. The discussion may then shift to the (Yellow then) Green hat to generate solutions and ideas. The discussion may move from White hat thinking to Black hat thinking to develop solution set criticisms.
Because everyone is focused on one approach at a time, the group is more collaborative than if one person is reacting emotionally (Red hat), another is trying to be objective (White hat), and another is critical of the points which emerge from the discussion (Black hat). The hats help people approach problems from different angles and highlight problem-solving flaws.
Pat Vieljeux
3 years ago
In 5 minutes, you can tell if a startup will succeed.
Or the “lie to me” method.
I can predict a startup's success in minutes.
Just interview its founder.
Ask "why?"
I question "why" till I sense him.
I need to feel the person I have in front of me. I need to know if he or she can deliver. Startups aren't easy. Without abilities, a brilliant idea will fail.
Good entrepreneurs have these qualities: He's a leader, determined, and resilient.
For me, they can be split in two categories.
The first entrepreneur aspires to live meaningfully. The second wants to get rich. The second is communicative. He wants to wow the crowd. He's motivated by the thought of one day sailing a boat past palm trees and sunny beaches.
What drives the first entrepreneur is evident in his speech, face, and voice. He will not speak about his product. He's (nearly) uninterested. He's not selling anything. He's not a salesman. He wants to succeed. The product is his fuel.
He'll explain his decision. He'll share his motivations. His desire. And he'll use meaningful words.
Paul Ekman has shown that face expressions aren't cultural. His study influenced the American TV series "lie to me" about body language and speech.
Passionate entrepreneurs are obvious. It's palpable. Faking passion is tough. Someone who wants your favor and money will expose his actual motives through his expressions and language.
The good liar will be able to fool you for a while, but not for long if you pay attention to his body language and how he expresses himself.
And also, if you look at his business plan.
His business plan reveals his goals. Read between the lines.
Entrepreneur 1 will focus on his "why", whereas Entrepreneur 2 will focus on the "how".
Entrepreneur 1 will develop a vision-driven culture.
The second, on the other hand, will focus on his EBITDA.
Why is the culture so critical? Because it will allow entrepreneur 1 to develop a solid team that can tackle his problems and trials. His team's "why" will keep them together in tough times.
"Give me a terrific start-up team with a mediocre idea over a weak one any day." Because a great team knows when to pivot and trusts each other. Weak teams fail.” — Bernhard Schroeder
Closings thoughts
Every VC must ask Why. Entrepreneur's motivations. This "why" will create the team's culture. This culture will help the team adjust to any setback.
Vitalik
4 years ago
An approximate introduction to how zk-SNARKs are possible (part 1)
You can make a proof for the statement "I know a secret number such that if you take the word ‘cow', add the number to the end, and SHA256 hash it 100 million times, the output starts with 0x57d00485aa". The verifier can verify the proof far more quickly than it would take for them to run 100 million hashes themselves, and the proof would also not reveal what the secret number is.
In the context of blockchains, this has 2 very powerful applications: Perhaps the most powerful cryptographic technology to come out of the last decade is general-purpose succinct zero knowledge proofs, usually called zk-SNARKs ("zero knowledge succinct arguments of knowledge"). A zk-SNARK allows you to generate a proof that some computation has some particular output, in such a way that the proof can be verified extremely quickly even if the underlying computation takes a very long time to run. The "ZK" part adds an additional feature: the proof can keep some of the inputs to the computation hidden.
You can make a proof for the statement "I know a secret number such that if you take the word ‘cow', add the number to the end, and SHA256 hash it 100 million times, the output starts with 0x57d00485aa". The verifier can verify the proof far more quickly than it would take for them to run 100 million hashes themselves, and the proof would also not reveal what the secret number is.
In the context of blockchains, this has two very powerful applications:
- Scalability: if a block takes a long time to verify, one person can verify it and generate a proof, and everyone else can just quickly verify the proof instead
- Privacy: you can prove that you have the right to transfer some asset (you received it, and you didn't already transfer it) without revealing the link to which asset you received. This ensures security without unduly leaking information about who is transacting with whom to the public.
But zk-SNARKs are quite complex; indeed, as recently as in 2014-17 they were still frequently called "moon math". The good news is that since then, the protocols have become simpler and our understanding of them has become much better. This post will try to explain how ZK-SNARKs work, in a way that should be understandable to someone with a medium level of understanding of mathematics.
Why ZK-SNARKs "should" be hard
Let us take the example that we started with: we have a number (we can encode "cow" followed by the secret input as an integer), we take the SHA256 hash of that number, then we do that again another 99,999,999 times, we get the output, and we check what its starting digits are. This is a huge computation.
A "succinct" proof is one where both the size of the proof and the time required to verify it grow much more slowly than the computation to be verified. If we want a "succinct" proof, we cannot require the verifier to do some work per round of hashing (because then the verification time would be proportional to the computation). Instead, the verifier must somehow check the whole computation without peeking into each individual piece of the computation.
One natural technique is random sampling: how about we just have the verifier peek into the computation in 500 different places, check that those parts are correct, and if all 500 checks pass then assume that the rest of the computation must with high probability be fine, too?
Such a procedure could even be turned into a non-interactive proof using the Fiat-Shamir heuristic: the prover computes a Merkle root of the computation, uses the Merkle root to pseudorandomly choose 500 indices, and provides the 500 corresponding Merkle branches of the data. The key idea is that the prover does not know which branches they will need to reveal until they have already "committed to" the data. If a malicious prover tries to fudge the data after learning which indices are going to be checked, that would change the Merkle root, which would result in a new set of random indices, which would require fudging the data again... trapping the malicious prover in an endless cycle.
But unfortunately there is a fatal flaw in naively applying random sampling to spot-check a computation in this way: computation is inherently fragile. If a malicious prover flips one bit somewhere in the middle of a computation, they can make it give a completely different result, and a random sampling verifier would almost never find out.
It only takes one deliberately inserted error, that a random check would almost never catch, to make a computation give a completely incorrect result.
If tasked with the problem of coming up with a zk-SNARK protocol, many people would make their way to this point and then get stuck and give up. How can a verifier possibly check every single piece of the computation, without looking at each piece of the computation individually? There is a clever solution.
see part 2