More on Entrepreneurship/Creators
Desiree Peralta
3 years ago
Why Now Is Your Chance To Create A Millionaire Career
People don’t believe in influencers anymore; they need people like you.
Social media influencers have dominated for years. We've seen videos, images, and articles of *famous* individuals unwrapping, reviewing, and endorsing things.
This industry generates billions. This year, marketers spent $2.23 billion on Instagram, $1 million on Youtube, and $775 million on Tiktok. This marketing has helped start certain companies.
Influencers are dying, so ordinary people like us may take over this billion-dollar sector. Why?
Why influencers are perishing
Most influencers lie to their fans, especially on Instagram. Influencers' first purpose was to make their lives so flawless that others would want to buy their stuff.
In 2015, an Australian influencer with 600,000 followers went viral for revealing all her photos and everything she did to seem great before deleting her account.
“I dramatically edited the pictures, I manipulated the environements, and made my life look perfect in social media… I remember I obsessively checked the like count for a full week since uploading it, a selfie that now has close to 2,500 likes. It got 5 likes. This was when I was so hungry for social media validation … This was the reason why I quit social media: for me, personally, it consumed me. I wasn’t living in a 3D world.”
Influencers then lost credibility.
Influencers seem to live in a bubble, separate from us. Thanks to self-popularity love's and constant awareness campaigns, people find these people ridiculous.
Influencers are praised more for showing themselves as natural and common than for showing luxuries and lies.
Little by little, they are dying, making room for a new group to take advantage of this multi-million dollar business, which gives us (ordinary people) a big opportunity to grow on any content creation platform we want.
Why this is your chance to develop on any platform for creating content
In 2021, I wrote “Not everyone who talks about money is a Financial Advisor, be careful of who you take advice from,”. In it, I warned that not everyone with a large following is a reputable source of financial advice.
Other writers hated this post and said I was wrong.
People don't want Jeff Bezos or Elon Musk's counsel, they said. They prefer to hear about their neighbor's restroom problems or his closest friend's terrible business.
Real advice from regular folks.
And I found this was true when I returned to my independent YouTube channel and had more than 1000 followers after having abandoned it with fewer than 30 videos in 2021 since there were already many personal finance and travel channels and I thought mine wasn't special.
People appreciated my videos because I was a 20-something girl trying to make money online, and they believed my advice more than that of influencers with thousands of followers.
I think today is the greatest time to grow on any platform as an ordinary person. Normal individuals give honest recommendations about what works for them and look easier to make because they have the same options as us.
Nobody cares how a millionaire acquired a Lamborghini unless it's entertaining. Education works now. Real counsel from average people is replicable.
Many individuals don't appreciate how false influencers seem (unreal bodies and excessive surgery and retouching) since it makes them feel uneasy.
That's why body-positive advertisements have been so effective, but they've lost ground in places like Tiktok, where the audience wants more content from everyday people than influencers living amazing lives. More people will relate to your content if you appear genuine.
Last thoughts
Influencers are dwindling. People want more real people to give real advice and demonstrate an ordinary life.
People will enjoy anything you tell about your daily life as long as you provide value, and you can build a following rapidly if you're honest.
This is a millionaire industry that is getting more expensive and will go with what works, so stand out immediately.
Scrum Ventures
3 years ago
Trends from the Winter 2022 Demo Day at Y Combinators
Y Combinators Winter 2022 Demo Day continues the trend of more startups engaging in accelerator Demo Days. Our team evaluated almost 400 projects in Y Combinator's ninth year.
After Winter 2021 Demo Day, we noticed a hurry pushing shorter rounds, inflated valuations, and larger batches.
Despite the batch size, this event's behavior showed a return to normalcy. Our observations show that investors evaluate and fund businesses more carefully. Unlike previous years, more YC businesses gave investors with data rooms and thorough pitch decks in addition to valuation data before Demo Day.
Demo Day pitches were virtual and fast-paced, limiting unplanned meetings. Investors had more time and information to do their due research before meeting founders. Our staff has more time to study diverse areas and engage with interesting entrepreneurs and founders.
This was one of the most regionally diversified YC cohorts to date. This year's Winter Demo Day startups showed some interesting tendencies.
Trends and Industries to Watch Before Demo Day
Demo day events at any accelerator show how investment competition is influencing startups. As startups swiftly become scale-ups and big success stories in fintech, e-commerce, healthcare, and other competitive industries, entrepreneurs and early-stage investors feel pressure to scale quickly and turn a notion into actual innovation.
Too much eagerness can lead founders to focus on market growth and team experience instead of solid concepts, technical expertise, and market validation. Last year, YC Winter Demo Day funding cycles ended too quickly and valuations were unrealistically high.
Scrum Ventures observed a longer funding cycle this year compared to last year's Demo Day. While that seems promising, many factors could be contributing to change, including:
Market patterns are changing and the economy is becoming worse.
the industries that investors are thinking about.
Individual differences between each event batch and the particular businesses and entrepreneurs taking part
The Winter 2022 Batch's Trends
Each year, we also wish to examine trends among early-stage firms and YC event participants. More international startups than ever were anticipated to present at Demo Day.
Less than 50% of demo day startups were from the U.S. For the S21 batch, firms from outside the US were most likely in Latin America or Europe, however this year's batch saw a large surge in startups situated in Asia and Africa.
YC Startup Directory
163 out of 399 startups were B2B software and services companies. Financial, healthcare, and consumer startups were common.
Our team doesn't plan to attend every pitch or speak with every startup's founders or team members. Let's look at cleantech, Web3, and health and wellness startup trends.
Our Opinions Following Conversations with 87 Startups at Demo Day
In the lead-up to Demo Day, we spoke with 87 of the 125 startups going. Compared to B2C enterprises, B2B startups had higher average valuations. A few outliers with high valuations pushed B2B and B2C means above the YC-wide mean and median.
Many of these startups develop business and technology solutions we've previously covered. We've seen API, EdTech, creative platforms, and cybersecurity remain strong and increase each year.
While these persistent tendencies influenced the startups Scrum Ventures looked at and the founders we interacted with on Demo Day, new trends required more research and preparation. Let's examine cleantech, Web3, and health and wellness startups.
Hardware and software that is green
Cleantech enterprises demand varying amounts of funding for hardware and software. Although the same overarching trend is fueling the growth of firms in this category, each subgroup has its own strategy and technique for investigation and identifying successful investments.
Many cleantech startups we spoke to during the YC event are focused on helping industrial operations decrease or recycle carbon emissions.
Carbon Crusher: Creating carbon negative roads
Phase Biolabs: Turning carbon emissions into carbon negative products and carbon neutral e-fuels
Seabound: Capturing carbon dioxide emissions from ships
Fleetzero: Creating electric cargo ships
Impossible Mining: Sustainable seabed mining
Beyond Aero: Creating zero-emission private aircraft
Verdn: Helping businesses automatically embed environmental pledges for product and service offerings, boost customer engagement
AeonCharge: Allowing electric vehicle (EV) drivers to more easily locate and pay for EV charging stations
Phoenix Hydrogen: Offering a hydrogen marketplace and a connected hydrogen hub platform to connect supply and demand for hydrogen fuel and simplify hub planning and partner program expansion
Aklimate: Allowing businesses to measure and reduce their supply chain’s environmental impact
Pina Earth: Certifying and tracking the progress of businesses’ forestry projects
AirMyne: Developing machines that can reverse emissions by removing carbon dioxide from the air
Unravel Carbon: Software for enterprises to track and reduce their carbon emissions
Web3: NFTs, the metaverse, and cryptocurrency
Web3 technologies handle a wide range of business issues. This category includes companies employing blockchain technology to disrupt entertainment, finance, cybersecurity, and software development.
Many of these startups overlap with YC's FinTech trend. Despite this, B2C and B2B enterprises were evenly represented in Web3. We examined:
Stablegains: Offering consistent interest on cash balance from the decentralized finance (DeFi) market
LiquiFi: Simplifying token management with automated vesting contracts, tax reporting, and scheduling. For companies, investors, and finance & accounting
NFTScoring: An NFT trading platform
CypherD Wallet: A multichain wallet for crypto and NFTs with a non-custodial crypto debit card that instantly converts coins to USD
Remi Labs: Allowing businesses to more easily create NFT collections that serve as access to products, memberships, events, and more
Cashmere: A crypto wallet for Web3 startups to collaboratively manage funds
Chaingrep: An API that makes blockchain data human-readable and tokens searchable
Courtyard: A platform for securely storing physical assets and creating 3D representations as NFTs
Arda: “Banking as a Service for DeFi,” an API that FinTech companies can use to embed DeFi products into their platforms
earnJARVIS: A premium cryptocurrency management platform, allowing users to create long-term portfolios
Mysterious: Creating community-specific experiences for Web3 Discords
Winter: An embeddable widget that allows businesses to sell NFTs to users purchasing with a credit card or bank transaction
SimpleHash: An API for NFT data that provides compatibility across blockchains, standardized metadata, accurate transaction info, and simple integration
Lifecast: Tools that address motion sickness issues for 3D VR video
Gym Class: Virtual reality (VR) multiplayer basketball video game
WorldQL: An asset API that allows NFT creators to specify multiple in-game interpretations of their assets, increasing their value
Bonsai Desk: A software development kit (SDK) for 3D analytics
Campfire: Supporting virtual social experiences for remote teams
Unai: A virtual headset and Visual World experience
Vimmerse: Allowing creators to more easily create immersive 3D experiences
Fitness and health
Scrum Ventures encountered fewer health and wellness startup founders than Web3 and Cleantech. The types of challenges these organizations solve are still diverse. Several of these companies are part of a push toward customization in healthcare, an area of biotech set for growth for companies with strong portfolios and experienced leadership.
Here are several startups we considered:
Syrona Health: Personalized healthcare for women in the workplace
Anja Health: Personalized umbilical cord blood banking and stem cell preservation
Alfie: A weight loss program focused on men’s health that coordinates medical care, coaching, and “community-based competition” to help users lose an average of 15% body weight
Ankr Health: An artificial intelligence (AI)-enabled telehealth platform that provides personalized side effect education for cancer patients and data collection for their care teams
Koko — A personalized sleep program to improve at-home sleep analysis and training
Condition-specific telehealth platforms and programs:
Reviving Mind: Chronic care management covered by insurance and supporting holistic, community-oriented health care
Equipt Health: At-home delivery of prescription medical equipment to help manage chronic conditions like obstructive sleep apnea
LunaJoy: Holistic women’s healthcare management for mental health therapy, counseling, and medication
12 Startups from YC's Winter 2022 Demo Day to Watch
Bobidi: 10x faster AI model improvement
Artificial intelligence (AI) models have become a significant tool for firms to improve how well and rapidly they process data. Bobidi helps AI-reliant firms evaluate their models, boosting data insights in less time and reducing data analysis expenditures. The business has created a gamified community that offers a bug bounty for AI, incentivizing community members to test and find weaknesses in clients' AI models.
Magna: DeFi investment management and token vesting
Magna delivers rapid, secure token vesting so consumers may turn DeFi investments into primitives. Carta for Web3 allows enterprises to effortlessly distribute tokens to staff or investors. The Magna team hopes to allow corporations use locked tokens as collateral for loans, facilitate secondary liquidity so investors can sell shares on a public exchange, and power additional DeFi applications.
Perl Street: Funding for infrastructure
This Fintech firm intends to help hardware entrepreneurs get financing by [democratizing] structured finance, unleashing billions for sustainable infrastructure and next-generation hardware solutions. This network has helped hardware entrepreneurs achieve more than $140 million in finance, helping companies working on energy storage devices, EVs, and creating power infrastructure.
CypherD: Multichain cryptocurrency wallet
CypherD seeks to provide a multichain crypto wallet so general customers can explore Web3 products without knowledge hurdles. The startup's beta app lets consumers access crypto from EVM blockchains. The founders have crypto, financial, and startup experience.
Unravel Carbon: Enterprise carbon tracking and offsetting
Unravel Carbon's AI-powered decarbonization technology tracks companies' carbon emissions. Singapore-based startup focuses on Asia. The software can use any company's financial data to trace the supply chain and calculate carbon tracking, which is used to make regulatory disclosures and suggest carbon offsets.
LunaJoy: Precision mental health for women
LunaJoy helped women obtain mental health support throughout life. The platform combines data science to create a tailored experience, allowing women to access psychotherapy, medication management, genetic testing, and health coaching.
Posh: Automated EV battery recycling
Posh attempts to solve one of the EV industry's largest logistical difficulties. Millions of EV batteries will need to be decommissioned in the next decade, and their precious metals and residual capacity will go unused for some time. Posh offers automated, scalable lithium battery disassembly, making EV battery recycling more viable.
Unai: VR headset with 5x higher resolution
Unai stands apart from metaverse companies. Its VR headgear has five times the resolution of existing options and emphasizes human expression and interaction in a remote world. Maxim Perumal's method of latency reduction powers current VR headsets.
Palitronica: Physical infrastructure cybersecurity
Palitronica blends cutting-edge hardware and software to produce networked electronic systems that support crucial physical and supply chain infrastructure. The startup's objective is to build solutions that defend national security and key infrastructure from cybersecurity threats.
Reality Defender: Deepfake detection
Reality Defender alerts firms to bogus users and changed audio, video, and image files. Reality Deference's API and web app score material in real time to prevent fraud, improve content moderation, and detect deception.
Micro Meat: Infrastructure for the manufacture of cell-cultured meat
MicroMeat promotes sustainable meat production. The company has created technologies to scale up bioreactor-grown meat muscle tissue from animal cells. Their goal is to scale up cultured meat manufacturing so cultivated meat products can be brought to market feasibly and swiftly, boosting worldwide meat consumption.
Fleetzero: Electric cargo ships
This startup's battery technology will make cargo ships more sustainable and profitable. Fleetzero's electric cargo ships have five times larger profit margins than fossil fuel ships. Fleetzeros' founder has marine engineering, ship operations, and enterprise sales and business experience.
MAJESTY AliNICOLE WOW!
3 years ago
YouTube's faceless videos are growing in popularity, but this is nothing new.
I've always bucked social media norms. YouTube doesn't compare. Traditional video made me zig when everyone zagged. Audio, picture personality animation, thought movies, and slide show videos are most popular and profitable.
YouTube's business is shifting. While most video experts swear by the idea that YouTube success is all about making personal and professional Face-Share-Videos, those who use YouTube for business know things are different.
In this article, I will share concepts from my mini master class Figures to Followers: Prioritizing Purposeful Profits Over Popularity on YouTube to Create the Win-Win for You, Your Audience & More and my forthcoming publication The WOWTUBE-PRENEUR FACTOR EVOLUTION: The Basics of Powerfully & Profitably Positioning Yourself as a Video Communications Authority to Broadcast Your WOW Effect as a Video Entrepreneur.
I've researched the psychology, anthropology, and anatomy of significant social media platforms as an entrepreneur and social media marketing expert. While building my YouTube empire, I've paid particular attention to what works for short, mid, and long-term success, whether it's a niche-focused, lifestyle, or multi-interest channel.
Most new, semi-new, and seasoned YouTubers feel vlog-style or live-on-camera videos are popular. Faceless, animated, music-text-based, and slideshow videos do well for businesses.
Buyer-consumer vs. content-consumer thinking is totally different when absorbing content. Profitability and popularity are closely related, however most people become popular with traditional means but not profitable.
In my experience, Faceless videos are more profitable, although it depends on the channel's style. Several professionals are now teaching in their courses that non-traditional films are making the difference in their business success and popularity.
Face-Share-Personal-Touch videos make audiences feel like they know the personality, but they're not profitable.
Most spend hours creating articles, videos, and thumbnails to seem good. That's how most YouTubers gained their success in the past, but not anymore.
Looking the part and performing a typical role in videos doesn't convert well, especially for newbie channels.
Working with video marketers and YouTubers for years, I've noticed that most struggle to be consistent with content publishing since they exclusively use formats that need extensive development. Camera and green screen set ups, shooting/filming, and editing for post productions require their time, making it less appealing to post consistently, especially if they're doing all the work themselves.
Because they won't make simple format videos or audio videos with an overlay image, they overcomplicate the procedure (even with YouTube Shorts), and they leave their channels for weeks or months. Again, they believe YouTube only allows specific types of videos. Even though this procedure isn't working, they plan to keep at it.
A successful YouTube channel needs multiple video formats to suit viewer needs, I teach. Face-Share-Personal Touch and Faceless videos are both useful.
How people engage with YouTube content has changed over the years, and the average customer is no longer interested in an all-video channel.
Face-Share-Personal-Touch videos are great
Google Live
Online training
Giving listeners a different way to access your podcast that is being broadcast on sites like Anchor, BlogTalkRadio, Spreaker, Google, Apple Store, and others Many people enjoy using a video camera to record themselves while performing the internet radio, Facebook, or Instagram Live versions of their podcasts.
Video Blog Updates
even more
Faceless videos are popular for business and benefit both entrepreneurs and audiences.
For the business owner/entrepreneur…
Less production time results in time dollar savings.
enables the business owner to demonstrate the diversity of content development
For the Audience…
The channel offers a variety of appealing content options.
The same format is not monotonous or overly repetitive for the viewers.
Below are a couple videos from YouTube guru Make Money Matt's channel, which has over 347K subscribers.
Enjoy
24 Best Niches to Make Money on YouTube Without Showing Your Face
Make Money on YouTube Without Making Videos (Free Course)
In conclusion, you have everything it takes to build your own YouTube brand and empire. Learn the rules, then adapt them to succeed.
Please reread this and the other suggested articles for optimal benefit.
I hope this helped. How has this article helped you? Follow me for more articles like this and more multi-mission expressions.
You might also like
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
Trevor Stark
3 years ago
Peter Thiels's Multi-Billion Dollar Net Worth's Unknown Philosopher
Peter Thiel studied philosophy as an undergraduate.
Peter Thiel has $7.36 billion.
Peter is a world-ranked chess player, has a legal degree, and has written profitable novels.
In 1999, he co-founded PayPal with Max Levchin, which merged with X.com.
Peter Thiel made $55 million after selling the company to eBay for $1.5 billion in 2002.
You may be wondering…
How did Peter turn $55 million into his now multi-billion dollar net worth?
One amazing investment?
Facebook.
Thiel was Facebook's first external investor. He bought 10% of the company for $500,000 in 2004.
This investment returned 159% annually, 200x in 8 years.
By 2012, Thiel sold almost all his Facebook shares, becoming a billionaire.
What was the investment thesis of Peter?
This investment appeared ridiculous. Facebook was an innovative startup.
Thiel's $500,000 contribution transformed Facebook.
Harvard students have access to Facebook's 8 features and 1 photo per profile.
How did Peter determine that this would be a wise investment, then?
Facebook is a mimetic desire machine.
Social media's popularity is odd. Why peek at strangers' images on a computer?
Peter Thiel studied under French thinker Rene Girard at Stanford.
Mimetic Desire explains social media's success.
Mimetic Desire is the idea that humans desire things simply because other people do.
If nobody wanted it, would you?
Would you desire a family, a luxury car, or expensive clothes if no one else did? Girard says no.
People we admire affect our aspirations because we're social animals. Every person has a role model.
Our nonreligious culture implies role models are increasingly other humans, not God.
The idea explains why social media influencers are so powerful.
Why would Andrew Tate or Kim Kardashian matter if people weren't mimetic?
Humanity is fundamentally motivated by social comparison.
Facebook takes advantage of this need for social comparison, and puts it on a global scale.
It aggregates photographs and updates from millions of individuals.
Facebook mobile allows 24/7 social comparison.
Thiel studied mimetic desire with Girard and realized Facebook exploits the urge for social comparison to gain money.
Social media is more significant and influential than ever, despite Facebook's decline.
Thiel and Girard show that applied philosophy (particularly in business) can be immensely profitable.
Ray Dalio
3 years ago
The latest “bubble indicator” readings.
As you know, I like to turn my intuition into decision rules (principles) that can be back-tested and automated to create a portfolio of alpha bets. I use one for bubbles. Having seen many bubbles in my 50+ years of investing, I described what makes a bubble and how to identify them in markets—not just stocks.
A bubble market has a high degree of the following:
- High prices compared to traditional values (e.g., by taking the present value of their cash flows for the duration of the asset and comparing it with their interest rates).
- Conditons incompatible with long-term growth (e.g., extrapolating past revenue and earnings growth rates late in the cycle).
- Many new and inexperienced buyers were drawn in by the perceived hot market.
- Broad bullish sentiment.
- Debt financing a large portion of purchases.
- Lots of forward and speculative purchases to profit from price rises (e.g., inventories that are more than needed, contracted forward purchases, etc.).
I use these criteria to assess all markets for bubbles. I have periodically shown you these for stocks and the stock market.
What Was Shown in January Versus Now
I will first describe the picture in words, then show it in charts, and compare it to the last update in January.
As of January, the bubble indicator showed that a) the US equity market was in a moderate bubble, but not an extreme one (ie., 70 percent of way toward the highest bubble, which occurred in the late 1990s and late 1920s), and b) the emerging tech companies (ie. As well, the unprecedented flood of liquidity post-COVID financed other bubbly behavior (e.g. SPACs, IPO boom, big pickup in options activity), making things bubbly. I showed which stocks were in bubbles and created an index of those stocks, which I call “bubble stocks.”
Those bubble stocks have popped. They fell by a third last year, while the S&P 500 remained flat. In light of these and other market developments, it is not necessarily true that now is a good time to buy emerging tech stocks.
The fact that they aren't at a bubble extreme doesn't mean they are safe or that it's a good time to get long. Our metrics still show that US stocks are overvalued. Once popped, bubbles tend to overcorrect to the downside rather than settle at “normal” prices.
The following charts paint the picture. The first shows the US equity market bubble gauge/indicator going back to 1900, currently at the 40% percentile. The charts also zoom in on the gauge in recent years, as well as the late 1920s and late 1990s bubbles (during both of these cases the gauge reached 100 percent ).
The chart below depicts the average bubble gauge for the most bubbly companies in 2020. Those readings are down significantly.
The charts below compare the performance of a basket of emerging tech bubble stocks to the S&P 500. Prices have fallen noticeably, giving up most of their post-COVID gains.
The following charts show the price action of the bubble slice today and in the 1920s and 1990s. These charts show the same market dynamics and two key indicators. These are just two examples of how a lot of debt financing stock ownership coupled with a tightening typically leads to a bubble popping.
Everything driving the bubbles in this market segment is classic—the same drivers that drove the 1920s bubble and the 1990s bubble. For instance, in the last couple months, it was how tightening can act to prick the bubble. Review this case study of the 1920s stock bubble (starting on page 49) from my book Principles for Navigating Big Debt Crises to grasp these dynamics.
The following charts show the components of the US stock market bubble gauge. Since this is a proprietary indicator, I will only show you some of the sub-aggregate readings and some indicators.
Each of these six influences is measured using a number of stats. This is how I approach the stock market. These gauges are combined into aggregate indices by security and then for the market as a whole. The table below shows the current readings of these US equity market indicators. It compares current conditions for US equities to historical conditions. These readings suggest that we’re out of a bubble.
1. How High Are Prices Relatively?
This price gauge for US equities is currently around the 50th percentile.
2. Is price reduction unsustainable?
This measure calculates the earnings growth rate required to outperform bonds. This is calculated by adding up the readings of individual securities. This indicator is currently near the 60th percentile for the overall market, higher than some of our other readings. Profit growth discounted in stocks remains high.
Even more so in the US software sector. Analysts' earnings growth expectations for this sector have slowed, but remain high historically. P/Es have reversed COVID gains but remain high historical.
3. How many new buyers (i.e., non-existing buyers) entered the market?
Expansion of new entrants is often indicative of a bubble. According to historical accounts, this was true in the 1990s equity bubble and the 1929 bubble (though our data for this and other gauges doesn't go back that far). A flood of new retail investors into popular stocks, which by other measures appeared to be in a bubble, pushed this gauge above the 90% mark in 2020. The pace of retail activity in the markets has recently slowed to pre-COVID levels.
4. How Broadly Bullish Is Sentiment?
The more people who have invested, the less resources they have to keep investing, and the more likely they are to sell. Market sentiment is now significantly negative.
5. Are Purchases Being Financed by High Leverage?
Leveraged purchases weaken the buying foundation and expose it to forced selling in a downturn. The leverage gauge, which considers option positions as a form of leverage, is now around the 50% mark.
6. To What Extent Have Buyers Made Exceptionally Extended Forward Purchases?
Looking at future purchases can help assess whether expectations have become overly optimistic. This indicator is particularly useful in commodity and real estate markets, where forward purchases are most obvious. In the equity markets, I look at indicators like capital expenditure, or how much businesses (and governments) invest in infrastructure, factories, etc. It reflects whether businesses are projecting future demand growth. Like other gauges, this one is at the 40th percentile.
What one does with it is a tactical choice. While the reversal has been significant, future earnings discounting remains high historically. In either case, bubbles tend to overcorrect (sell off more than the fundamentals suggest) rather than simply deflate. But I wanted to share these updated readings with you in light of recent market activity.