Why I Love Azuki
Azuki Banner (www.azuki.com)
Disclaimer: This is my personal viewpoint. I'm not on the Azuki team. Please keep in mind that I am merely a fan, community member, and holder. Please do your own research and pardon my grammar. Thanks!
Azuki has changed my view of NFTs.
When I first entered the NFT world, I had no idea what to expect. I liked the idea. So I invested in some projects, fought for whitelists, and discovered some cool NFTs projects (shout-out to CATC). I lost more money than I earned at one point, but I hadn't invested excessively (only put in what you can afford to lose). Despite my losses, I kept looking. I almost waited for the “ah-ha” moment. A NFT project that changed my perspective on NFTs. What makes an NFT project more than a work of art?
Answer: Azuki.
The Art
The Azuki art drew me in as an anime fan. It looked like something out of an anime, and I'd never seen it before in NFT.
The project was still new. The first two animated teasers were released with little fanfare, but I was impressed with their quality. You can find them on Instagram or in their earlier Tweets.
The teasers hinted that this project could be big and that the team could deliver. It was amazing to see Shao cut the Azuki posters with her katana. Especially at the end when she sheaths her sword and the music cues. Then the live action video of the young boy arranging the Azuki posters seemed movie-like. I felt like I was entering the Azuki story, brand, and dope theme.
The team did not disappoint with the Azuki NFTs. The level of detail in the art is stunning. There were Azukis of all genders, skin and hair types, and more. These 10,000 Azukis have so much representation that almost anyone can find something that resonates. Rather than me rambling on, I suggest you visit the Azuki gallery
The Team
If the art is meant to draw you in and be the project's face, the team makes it more. The NFT would be a JPEG without a good team leader. Not that community isn't important, but no community would rally around a bad team.
Because I've been rugged before, I'm very focused on the team when considering a project. While many project teams are anonymous, I try to find ones that are doxxed (public) or at least appear to be established. Unlike Azuki, where most of the Azuki team is anonymous, Steamboy is public. He is (or was) Overwatch's character art director and co-creator of Azuki. I felt reassured and could trust the project after seeing someone from a major game series on the team.
Then I tried to learn as much as I could about the team. Following everyone on Twitter, reading their tweets, and listening to recorded AMAs. I was impressed by the team's professionalism and dedication to their vision for Azuki, led by ZZZAGABOND.
I believe the phrase “actions speak louder than words” applies to Azuki. I can think of a few examples of what the Azuki team has done, but my favorite is ERC721A.
With ERC721A, Azuki has created a new algorithm that allows minting multiple NFTs for essentially the same cost as minting one NFT.
I was ecstatic when the dev team announced it. This fascinates me as a self-taught developer. Azuki released a product that saves people money, improves the NFT space, and is open source. It showed their love for Azuki and the NFT community.
The Community
Community, community, community. It's almost a chant in the NFT space now. A community, like a team, can make or break a project. We are the project's consumers, shareholders, core, and lifeblood. The team builds the house, and we fill it. We stay for the community.
When I first entered the Azuki Discord, I was surprised by the calm atmosphere. There was no news about the project. No release date, no whitelisting requirements. No grinding or spamming either. People just wanted to hangout, get to know each other, and talk. It was nice. So the team could pick genuine people for their mintlist (aka whitelist).
But nothing fundamental has changed since the release. It has remained an authentic, fun, and helpful community. I'm constantly logging into Discord to chat with others or follow conversations. I see the community's openness to newcomers. Everyone respects each other (barring a few bad apples) and the variety of people passing through is fascinating. This human connection and interaction is what I enjoy about this place. Being a part of a group that supports a cause.
Finally, I want to thank the amazing Azuki mod team and the kissaten channel for their contributions.
The Brand
So, what sets Azuki apart from other projects? They are shaping a brand or identity. The Azuki website, I believe, best captures their vision. (This is me gushing over the site.)
If you go to the website, turn on the dope playlist in the bottom left. The playlist features a mix of Asian and non-Asian hip-hop and rap artists, with some lo-fi thrown in. The songs on the playlist change, but I think you get the vibe Azuki embodies just by turning on the music.
The Garden is our next stop where we are introduced to Azuki.
A brand.
We're creating a new brand together.
A metaverse brand. By the people.
A collection of 10,000 avatars that grant Garden membership. It starts with exclusive streetwear collabs, NFT drops, live events, and more. Azuki allows for a new media genre that the world has yet to discover. Let's build together an Azuki, your metaverse identity.
The Garden is a magical internet corner where art, community, and culture collide. The boundaries between the physical and digital worlds are blurring.
Try a Red Bean.
The text begins with Azuki's intention in the space. It's a community-made metaverse brand. Then it goes into more detail about Azuki's plans. Initiation of a story or journey. "Would you like to take the red bean and jump down the rabbit hole with us?" I love the Matrix red pill or blue pill play they used. (Azuki in Japanese means red bean.)
Morpheus, the rebel leader, offers Neo the choice of a red or blue pill in The Matrix. “You take the blue pill... After the story, you go back to bed and believe whatever you want. Your red pill... Let me show you how deep the rabbit hole goes.” Aware that the red pill will free him from the enslaving control of the machine-generated dream world and allow him to escape into the real world, he takes it. However, living the “truth of reality” is harsher and more difficult.
It's intriguing and draws you in. Taking the red bean causes what? Where am I going? I think they did well in piqueing a newcomer's interest.
Not convinced by the Garden? Read the Manifesto. It reinforces Azuki's role.
Here comes a new wave…
And surfing here is different.
Breaking down barriers.
Building open communities.
Creating magic internet money with our friends.
To those who don’t get it, we tell them: gm.
They’ll come around eventually.
Here’s to the ones with the courage to jump down a peculiar rabbit hole.
One that pulls you away from a world that’s created by many and owned by few…
To a world that’s created by more and owned by all.
From The Garden come the human beans that sprout into your family.
We rise together.
We build together.
We grow together.
Ready to take the red bean?
Not to mention the Mindmap, it sets Azuki apart from other projects and overused Roadmaps. I like how the team recognizes that the NFT space is not linear. So many of us are still trying to figure it out. It is Azuki's vision to adapt to changing environments while maintaining their values. I admire their commitment to long-term growth.
Conclusion
To be honest, I have no idea what the future holds. Azuki is still new and could fail. But I'm a long-term Azuki fan. I don't care about quick gains. The future looks bright for Azuki. I believe in the team's output. I love being an Azuki.
Thank you! IKUZO!
Full post here
Sam Hickmann
3 years ago
+1 💪
More on NFTs & Art
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
Jayden Levitt
3 years ago
How to Explain NFTs to Your Grandmother, in Simple Terms
In simple terms, you probably don’t.
But try. Grandma didn't grow up with Facebook, but she eventually joined.
Perhaps the fear of being isolated outweighed the discomfort of learning the technology.
Grandmas are Facebook likers, sharers, and commenters.
There’s no stopping her.
Not even NFTs. Web3 is currently very complex.
It's difficult to explain what NFTs are, how they work, and why we might use them.
Three explanations.
1. Everything will be ours to own, both physically and digitally.
Why own something you can't touch? What's the point?
Blockchain technology proves digital ownership.
Untouchables need ownership proof. What?
Digital assets reduce friction, save time, and are better for the environment than physical goods.
Many valuable things are intangible. Feeling like your favorite brands. You'll pay obscene prices for clothing that costs pennies.
Secondly, NFTs Are Contracts. Agreements Have Value.
Blockchain technology will replace all contracts and intermediaries.
Every insurance contract, deed, marriage certificate, work contract, plane ticket, concert ticket, or sports event is likely an NFT.
We all have public wallets, like Grandma's Facebook page.
3. Your NFT Purchases Will Be Visible To Everyone.
Everyone can see your public wallet. What you buy says more about you than what you post online.
NFTs issued double as marketing collateral when seen on social media.
While I doubt Grandma knows who Snoop Dog is, imagine him or another famous person holding your NFT in his public wallet and the attention that could bring to you, your company, or brand.
This Technical Section Is For You
The NFT is a contract; its founders can add value through access, events, tuition, and possibly royalties.
Imagine Elon Musk releasing an NFT to his network. Or yearly business consultations for three years.
Christ-alive.
It's worth millions.
These determine their value.
No unsuspecting schmuck willing to buy your hot potato at zero. That's the trend, though.
Overpriced NFTs for low-effort projects created a bubble that has burst.
During a market bubble, you can make money by buying overvalued assets and selling them later for a profit, according to the Greater Fool Theory.
People are struggling. Some are ruined by collateralized loans and the gold rush.
Finances are ruined.
It's uncomfortable.
The same happened in 2018, during the ICO crash or in 1999/2000 when the dot com bubble burst. But the underlying technology hasn’t gone away.
Alex Carter
3 years ago
Metaverse, Web 3, and NFTs are BS
Most crypto is probably too.
The goals of Web 3 and the metaverse are admirable and attractive. Who doesn't want an internet owned by users? Who wouldn't want a digital realm where anything is possible? A better way to collaborate and visit pals.
Companies pursue profits endlessly. Infinite growth and revenue are expected, and if a corporation needs to sacrifice profits to safeguard users, the CEO, board of directors, and any executives will lose to the system of incentives that (1) retains workers with shares and (2) makes a company answerable to all of its shareholders. Only the government can guarantee user protections, but we know how successful that is. This is nothing new, just a problem with modern capitalism and tech platforms that a user-owned internet might remedy. Moxie, the founder of Signal, has a good articulation of some of these current Web 2 tech platform problems (but I forget the timestamp); thoughts on JRE aside, this episode is worth listening to (it’s about a bunch of other stuff too).
Moxie Marlinspike, founder of Signal, on the Joe Rogan Experience podcast.
Source: https://open.spotify.com/episode/2uVHiMqqJxy8iR2YB63aeP?si=4962b5ecb1854288
Web 3 champions are premature. There was so much spectacular growth during Web 2 that the next wave of founders want to make an even bigger impact, while investors old and new want a chance to get a piece of the moonshot action. Worse, crypto enthusiasts believe — and financially need — the fact of its success to be true, whether or not it is.
I’m doubtful that it will play out like current proponents say. Crypto has been the white-hot focus of SV’s best and brightest for a long time yet still struggles to come up any mainstream use case other than ‘buy, HODL, and believe’: a store of value for your financial goals and wishes. Some kind of the metaverse is likely, but will it be decentralized, mostly in VR, or will Meta (previously FB) play a big role? Unlikely.
METAVERSE
The metaverse exists already. Our digital lives span apps, platforms, and games. I can design a 3D house, invite people, use Discord, and hang around in an artificial environment. Millions of gamers do this in Rust, Minecraft, Valheim, and Animal Crossing, among other games. Discord's voice chat and Slack-like servers/channels are the present social anchor, but the interface, integrations, and data portability will improve. Soon you can stream YouTube videos on digital house walls. You can doodle, create art, play Jackbox, and walk through a door to play Apex Legends, Fortnite, etc. Not just gaming. Digital whiteboards and screen sharing enable real-time collaboration. They’ll review code and operate enterprises. Music is played and made. In digital living rooms, they'll watch movies, sports, comedy, and Twitch. They'll tweet, laugh, learn, and shittalk.
The metaverse is the evolution of our digital life at home, the third place. The closest analog would be Discord and the integration of Facebook, Slack, YouTube, etc. into a single, 3D, customizable hangout space.
I'm not certain this experience can be hugely decentralized and smoothly choreographed, managed, and run, or that VR — a luxury, cumbersome, and questionably relevant technology — must be part of it. Eventually, VR will be pragmatic, achievable, and superior to real life in many ways. A total sensory experience like the Matrix or Sword Art Online, where we're physically hooked into the Internet yet in our imaginations we're jumping, flying, and achieving athletic feats we never could in reality; exploring realms far grander than our own (as grand as it is). That VR is different from today's.
Ben Thompson released an episode of Exponent after Facebook changed its name to Meta. Ben was suspicious about many metaverse champion claims, but he made a good analogy between Oculus and the PC. The PC was initially far too pricey for the ordinary family to afford. It began as a business tool. It got so powerful and pervasive that it affected our personal life. Price continues to plummet and so much consumer software was produced that it's impossible to envision life without a home computer (or in our pockets). If Facebook shows product market fit with VR in business, through use cases like remote work and collaboration, maybe VR will become practical in our personal lives at home.
Before PCs, we relied on Blockbuster, the Yellow Pages, cabs to get to the airport, handwritten taxes, landline phones to schedule social events, and other archaic methods. It is impossible for me to conceive what VR, in the form of headsets and hand controllers, stands to give both professional and especially personal digital experiences that is an order of magnitude better than what we have today. Is looking around better than using a mouse to examine a 3D landscape? Do the hand controls make x10 or x100 work or gaming more fun or efficient? Will VR replace scalable Web 2 methods and applications like Web 1 and Web 2 did for analog? I don't know.
My guess is that the metaverse will arrive slowly, initially on displays we presently use, with more app interoperability. I doubt that it will be controlled by the people or by Facebook, a corporation that struggles to properly innovate internally, as practically every large digital company does. Large tech organizations are lousy at hiring product-savvy employees, and if they do, they rarely let them explore new things.
These companies act like business schools when they seek founders' results, with bureaucracy and dependency. Which company launched the last popular consumer software product that wasn't a clone or acquisition? Recent examples are scarce.
Web 3
Investors and entrepreneurs of Web 3 firms are declaring victory: 'Web 3 is here!' Web 3 is the future! Many profitable Web 2 enterprises existed when Web 2 was defined. The word was created to explain user behavior shifts, not a personal pipe dream.
Origins of Web 2: http://www.oreilly.com/pub/a/web2/archive/what-is-web-20.html
One of these Web 3 startups may provide the connecting tissue to link all these experiences or become one of the major new digital locations. Even so, successful players will likely use centralized power arrangements, as Web 2 businesses do now. Some Web 2 startups integrated our digital lives. Rockmelt (2010–2013) was a customizable browser with bespoke connectors to every program a user wanted; imagine seeing Facebook, Twitter, Discord, Netflix, YouTube, etc. all in one location. Failure. Who knows what Opera's doing?
Silicon Valley and tech Twitter in general have a history of jumping on dumb bandwagons that go nowhere. Dot-com crash in 2000? The huge deployment of capital into bad ideas and businesses is well-documented. And live video. It was the future until it became a niche sector for gamers. Live audio will play out a similar reality as CEOs with little comprehension of audio and no awareness of lasting new user behavior deceive each other into making more and bigger investments on fool's gold. Twitter trying to buy Clubhouse for $4B, Spotify buying Greenroom, Facebook exploring live audio and 'Tiktok for audio,' and now Amazon developing a live audio platform. This live audio frenzy won't be worth their time or energy. Blind guides blind. Instead of learning from prior failures like Twitter buying Periscope for $100M pre-launch and pre-product market fit, they're betting on unproven and uncompelling experiences.
NFTs
NFTs are also nonsense. Take Loot, a time-limited bag drop of "things" (text on the blockchain) for a game that didn't exist, bought by rich techies too busy to play video games and foolish enough to think they're getting in early on something with a big reward. What gaming studio is incentivized to use these items? Who's encouraged to join? No one cares besides Loot owners who don't have NFTs. Skill, merit, and effort should be rewarded with rare things for gamers. Even if a small minority of gamers can make a living playing, the average game's major appeal has never been to make actual money - that's a profession.
No game stays popular forever, so how is this objective sustainable? Once popularity and usage drop, exclusive crypto or NFTs will fall. And if NFTs are designed to have cross-game appeal, incentives apart, 30 years from now any new game will need millions of pre-existing objects to build around before they start. It doesn’t work.
Many games already feature item economies based on real in-game scarcity, generally for cosmetic things to avoid pay-to-win, which undermines scaled gaming incentives for huge player bases. Counter-Strike, Rust, etc. may be bought and sold on Steam with real money. Since the 1990s, unofficial cross-game marketplaces have sold in-game objects and currencies. NFTs aren't needed. Making a popular, enjoyable, durable game is already difficult.
With NFTs, certain JPEGs on the internet went from useless to selling for $69 million. Why? Crypto, Web 3, early Internet collectibles. NFTs are digital Beanie Babies (unlike NFTs, Beanie Babies were a popular children's toy; their destinies are the same). NFTs are worthless and scarce. They appeal to crypto enthusiasts seeking for a practical use case to support their theory and boost their own fortune. They also attract to SV insiders desperate not to miss the next big thing, not knowing what it will be. NFTs aren't about paying artists and creators who don't get credit for their work.
South Park's Underpants Gnomes
NFTs are a benign, foolish plan to earn money on par with South Park's underpants gnomes. At worst, they're the world of hucksterism and poor performers. Or those with money and enormous followings who, like everyone, don't completely grasp cryptocurrencies but are motivated by greed and status and believe Gary Vee's claim that CryptoPunks are the next Facebook. Gary's watertight logic: if NFT prices dip, they're on the same path as the most successful corporation in human history; buy the dip! NFTs aren't businesses or museum-worthy art. They're bs.
Gary Vee compares NFTs to Amazon.com. vm.tiktok.com/TTPdA9TyH2
We grew up collecting: Magic: The Gathering (MTG) cards printed in the 90s are now worth over $30,000. Imagine buying a digital Magic card with no underlying foundation. No one plays the game because it doesn't exist. An NFT is a contextless image someone conned you into buying a certificate for, but anyone may copy, paste, and use. Replace MTG with Pokemon for younger readers.
When Gary Vee strongarms 30 tech billionaires and YouTube influencers into buying CryptoPunks, they'll talk about it on Twitch, YouTube, podcasts, Twitter, etc. That will convince average folks that the product has value. These guys are smart and/or rich, so I'll get in early like them. Cryptography is similar. No solid, scaled, mainstream use case exists, and no one knows where it's headed, but since the global crypto financial bubble hasn't burst and many people have made insane fortunes, regular people are putting real money into something that is highly speculative and could be nothing because they want a piece of the action. Who doesn’t want free money? Rich techies and influencers won't be affected; normal folks will.
Imagine removing every $1 invested in Bitcoin instantly. What would happen? How far would Bitcoin fall? Over 90%, maybe even 95%, and Bitcoin would be dead. Bitcoin as an investment is the only scalable widespread use case: it's confidence that a better use case will arise and that being early pays handsomely. It's like pouring a trillion dollars into a company with no business strategy or users and a CEO who makes vague future references.
New tech and efforts may provoke a 'get off my lawn' mentality as you approach 40, but I've always prided myself on having a decent bullshit detector, and it's flying off the handle at this foolishness. If we can accomplish a functional, responsible, equitable, and ethical user-owned internet, I'm for it.
Postscript:
I wanted to summarize my opinions because I've been angry about this for a while but just sporadically tweeted about it. A friend handed me a Dan Olson YouTube video just before publication. He's more knowledgeable, articulate, and convincing about crypto. It's worth seeing:
This post is a summary. See the original one here.
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Alex Mathers
24 years ago
400 articles later, nobody bothered to read them.
Writing for readers:
14 years of daily writing.
I post practically everything on social media. I authored hundreds of articles, thousands of tweets, and numerous volumes to almost no one.
Tens of thousands of readers regularly praise me.
I despised writing. I'm stuck now.
I've learned what readers like and what doesn't.
Here are some essential guidelines for writing with impact:
Readers won't understand your work if you can't.
Though obvious, this slipped me up. Share your truths.
Stories engage human brains.
Showing the journey of a person from worm to butterfly inspires the human spirit.
Overthinking hinders powerful writing.
The best ideas come from inner understanding in between thoughts.
Avoid writing to find it. Write.
Writing a masterpiece isn't motivating.
Write for five minutes to simplify. Step-by-step, entertaining, easy steps.
Good writing requires a willingness to make mistakes.
So write loads of garbage that you can edit into a good piece.
Courageous writing.
A courageous story will move readers. Personal experience is best.
Go where few dare.
Templates, outlines, and boundaries help.
Limitations enhance writing.
Excellent writing is straightforward and readable, removing all the unnecessary fat.
Use five words instead of nine.
Use ordinary words instead of uncommon ones.
Readers desire relatability.
Too much perfection will turn it off.
Write to solve an issue if you can't think of anything to write.
Instead, read to inspire. Best authors read.
Every tweet, thread, and novel must have a central idea.
What's its point?
This can make writing confusing.
️ Don't direct your reader.
Readers quit reading. Demonstrate, describe, and relate.
Even if no one responds, have fun. If you hate writing it, the reader will too.
Zuzanna Sieja
3 years ago
In 2022, each data scientist needs to read these 11 books.
Non-technical talents can benefit data scientists in addition to statistics and programming.
As our article 5 Most In-Demand Skills for Data Scientists shows, being business-minded is useful. How can you get such a diverse skill set? We've compiled a list of helpful resources.
Data science, data analysis, programming, and business are covered. Even a few of these books will make you a better data scientist.
Ready? Let’s dive in.
Best books for data scientists
1. The Black Swan
Author: Nassim Taleb
First, a less obvious title. Nassim Nicholas Taleb's seminal series examines uncertainty, probability, risk, and decision-making.
Three characteristics define a black swan event:
It is erratic.
It has a significant impact.
Many times, people try to come up with an explanation that makes it seem more predictable than it actually was.
People formerly believed all swans were white because they'd never seen otherwise. A black swan in Australia shattered their belief.
Taleb uses this incident to illustrate how human thinking mistakes affect decision-making. The book teaches readers to be aware of unpredictability in the ever-changing IT business.
Try multiple tactics and models because you may find the answer.
2. High Output Management
Author: Andrew Grove
Intel's former chairman and CEO provides his insights on developing a global firm in this business book. We think Grove would choose “management” to describe the talent needed to start and run a business.
That's a skill for CEOs, techies, and data scientists. Grove writes on developing productive teams, motivation, real-life business scenarios, and revolutionizing work.
Five lessons:
Every action is a procedure.
Meetings are a medium of work
Manage short-term goals in accordance with long-term strategies.
Mission-oriented teams accelerate while functional teams increase leverage.
Utilize performance evaluations to enhance output.
So — if the above captures your imagination, it’s well worth getting stuck in.
3. The Hard Thing About Hard Things: Building a Business When There Are No Easy Answers
Author: Ben Horowitz
Few realize how difficult it is to run a business, even though many see it as a tremendous opportunity.
Business schools don't teach managers how to handle the toughest difficulties; they're usually on their own. So Ben Horowitz wrote this book.
It gives tips on creating and maintaining a new firm and analyzes the hurdles CEOs face.
Find suggestions on:
create software
Run a business.
Promote a product
Obtain resources
Smart investment
oversee daily operations
This book will help you cope with tough times.
4. Obviously Awesome: How to Nail Product Positioning
Author: April Dunford
Your job as a data scientist is a product. You should be able to sell what you do to clients. Even if your product is great, you must convince them.
How to? April Dunford's advice: Her book explains how to connect with customers by making your offering seem like a secret sauce.
You'll learn:
Select the ideal market for your products.
Connect an audience to the value of your goods right away.
Take use of three positioning philosophies.
Utilize market trends to aid purchasers
5. The Mom test
Author: Rob Fitzpatrick
The Mom Test improves communication. Client conversations are rarely predictable. The book emphasizes one of the most important communication rules: enquire about specific prior behaviors.
Both ways work. If a client has suggestions or demands, listen carefully and ensure everyone understands. The book is packed with client-speaking tips.
6. Introduction to Machine Learning with Python: A Guide for Data Scientists
Authors: Andreas C. Müller, Sarah Guido
Now, technical documents.
This book is for Python-savvy data scientists who wish to learn machine learning. Authors explain how to use algorithms instead of math theory.
Their technique is ideal for developers who wish to study machine learning basics and use cases. Sci-kit-learn, NumPy, SciPy, pandas, and Jupyter Notebook are covered beyond Python.
If you know machine learning or artificial neural networks, skip this.
7. Python Data Science Handbook: Essential Tools for Working with Data
Author: Jake VanderPlas
Data work isn't easy. Data manipulation, transformation, cleansing, and visualization must be exact.
Python is a popular tool. The Python Data Science Handbook explains everything. The book describes how to utilize Pandas, Numpy, Matplotlib, Scikit-Learn, and Jupyter for beginners.
The only thing missing is a way to apply your learnings.
8. Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
Author: Wes McKinney
The author leads you through manipulating, processing, cleaning, and analyzing Python datasets using NumPy, Pandas, and IPython.
The book's realistic case studies make it a great resource for Python or scientific computing beginners. Once accomplished, you'll uncover online analytics, finance, social science, and economics solutions.
9. Data Science from Scratch
Author: Joel Grus
Here's a title for data scientists with Python, stats, maths, and algebra skills (alongside a grasp of algorithms and machine learning). You'll learn data science's essential libraries, frameworks, modules, and toolkits.
The author works through all the key principles, providing you with the practical abilities to develop simple code. The book is appropriate for intermediate programmers interested in data science and machine learning.
Not that prior knowledge is required. The writing style matches all experience levels, but understanding will help you absorb more.
10. Machine Learning Yearning
Author: Andrew Ng
Andrew Ng is a machine learning expert. Co-founded and teaches at Stanford. This free book shows you how to structure an ML project, including recognizing mistakes and building in complex contexts.
The book delivers knowledge and teaches how to apply it, so you'll know how to:
Determine the optimal course of action for your ML project.
Create software that is more effective than people.
Recognize when to use end-to-end, transfer, and multi-task learning, and how to do so.
Identifying machine learning system flaws
Ng writes easy-to-read books. No rigorous math theory; just a terrific approach to understanding how to make technical machine learning decisions.
11. Deep Learning with PyTorch Step-by-Step
Author: Daniel Voigt Godoy
The last title is also the most recent. The book was revised on 23 January 2022 to discuss Deep Learning and PyTorch, a Python coding tool.
It comprises four parts:
Fundamentals (gradient descent, training linear and logistic regressions in PyTorch)
Machine Learning (deeper models and activation functions, convolutions, transfer learning, initialization schemes)
Sequences (RNN, GRU, LSTM, seq2seq models, attention, self-attention, transformers)
Automatic Language Recognition (tokenization, embeddings, contextual word embeddings, ELMo, BERT, GPT-2)
We admire the book's readability. The author avoids difficult mathematical concepts, making the material feel like a conversation.
Is every data scientist a humanist?
Even as a technological professional, you can't escape human interaction, especially with clients.
We hope these books will help you develop interpersonal skills.
Rick Blyth
3 years ago
Looking for a Reliable Micro SaaS Niche
Niches are rich, as the adage goes.
Micro SaaS requires a great micro-niche; otherwise, it's merely plain old SaaS with a large audience.
Instead of targeting broad markets with few identifying qualities, specialise down to a micro-niche. How would you target these users?
Better go tiny. You'll locate and engage new consumers more readily and serve them better with a customized solution.
Imagine you're a real estate lawyer looking for a case management solution. Because it's so specific to you, you'd be lured to this link:
instead of below:
Next, locate mini SaaS niches that could work for you. You're not yet looking at the problems/solutions in these areas, merely shortlisting them.
The market should be growing, not shrinking
We shouldn't design apps for a declining niche. We intend to target stable or growing niches for the next 5 to 10 years.
If it's a developing market, you may be able to claim a stake early. You must balance this strategy with safer, longer-established niches (accountancy, law, health, etc).
First Micro SaaS apps I designed were for Merch By Amazon creators, a burgeoning niche. I found this niche when searching for passive income.
Graphic designers and entrepreneurs post their art to Amazon to sell on clothes. When Amazon sells their design, they get a royalty. Since 2015, this platform and specialty have grown dramatically.
Amazon doesn't publicize the amount of creators on the platform, but it's possible to approximate by looking at Facebook groups, Reddit channels, etc.
I could see the community growing week by week, with new members joining. Merch was an up-and-coming niche, and designers made money when their designs sold. All I had to do was create tools that let designers focus on making bestselling designs.
Look at the Google Trends graph below to see how this niche has evolved and when I released my apps and resigned my job.
Are the users able to afford the tools?
Who's your average user? Consumer or business? Is your solution budgeted?
If they're students, you'll struggle to convince them to subscribe to your study-system app (ahead of video games and beer).
Let's imagine you designed a Shopify plugin that emails customers when a product is restocked. If your plugin just needs 5 product sales a month to justify its cost, everyone wins (just be mindful that one day Shopify could potentially re-create your plugins functionality within its core offering making your app redundant ).
Do specialized users buy tools? If so, that's comforting. If not, you'd better have a compelling value proposition for your end customer if you're the first.
This should include how much time or money your program can save or make the user.
Are you able to understand the Micro SaaS market?
Ideally, you're already familiar about the industry/niche. Maybe you're fixing a challenge from your day job or freelance work.
If not, evaluate how long it would take to learn the niche's users. Health & Fitness is easier to relate to and understand than hedge fund derivatives trading.
Competing in these complex (and profitable) fields might offer you an edge.
B2C, B2M, or B2B?
Consider your user base's demographics. Will you target businesses, consumers, or both? Let's examine the different consumer types:
B2B refers to business-to-business transactions where customers are other businesses. UpVoty, Plutio, Slingshot, Salesforce, Atlassian, and Hubspot are a few examples of SaaS, ranging from Micro SaaS to SaaS.
Business to Consumer (B2C), in which your clients are people who buy things. For instance, Duolingo, Canva, and Nomad List.
For instance, my tool KDP Wizard has a mixed user base of publishing enterprises and also entrepreneurial consumers selling low-content books on Amazon. This is a case of business to many (B2M), where your users are a mixture of businesses and consumers. There is a large SaaS called Dropbox that offers both personal and business plans.
Targeting a B2B vs. B2C niche is very different. The sales cycle differs.
A B2B sales staff must make cold calls to potential clients' companies. Long sales, legal, and contractual conversations are typically required for each business to get the go-ahead. The cost of obtaining a new customer is substantially more than it is for B2C, despite the fact that the recurring fees are significantly higher.
Since there is typically only one individual making the purchasing decision, B2C signups are virtually always self-service with reduced recurring fees. Since there is typically no outbound sales staff in B2C, acquisition costs are significantly lower than in B2B.
User Characteristics for B2B vs. B2C
Consider where your niche's users congregate if you don't already have a presence there.
B2B users frequent LinkedIn and Twitter. B2C users are on Facebook/Instagram/Reddit/Twitter, etc.
Churn is higher in B2C because consumers haven't gone through all the hoops of a B2B sale. Consumers are more unpredictable than businesses since they let their bank cards exceed limitations or don't update them when they expire.
With a B2B solution, there's a contractual arrangement and the firm will pay the subscription as long as they need it.
Depending on how you feel about the above (sales team vs. income vs. churn vs. targeting), you'll know which niches to pursue.
You ought to respect potential customers.
Would you hang out with customers?
You'll connect with users at conferences (in-person or virtual), webinars, seminars, screenshares, Facebook groups, emails, support calls, support tickets, etc.
If talking to a niche's user base makes you shudder, you're in for a tough road. Whether they're demanding or dull, avoid them if possible.
Merch users are mostly graphic designers, side hustlers, and entrepreneurs. These laid-back users embrace technologies that assist develop their Merch business.
I discovered there was only one annual conference for this specialty, held in Seattle, USA. I decided to organize a conference for UK/European Merch designers, despite never having done so before.
Hosting a conference for over 80 people was stressful, and it turned out to be much bigger than expected, with attendees from the US, Europe, and the UK.
I met many specialized users, built relationships, gained trust, and picked their brains in person. Many of the attendees were already Merch Wizard users, so hearing their feedback and ideas for future features was invaluable.
focused and specific
Instead of building for a generic, hard-to-reach market, target a specific group.
I liken it to fishing in a little, hidden pond. This small pond has only one species of fish, so you learn what bait it likes. Contrast that with trawling for hours to catch as many fish as possible, even if some aren't what you want.
In the case management scenario, it's difficult to target leads because several niches could use the app. Where do your potential customers hang out? Your generic solution: No.
It's easier to join a community of Real Estate Lawyers and see if your software can answer their pain points.
My Success with Micro SaaS
In my case, my Micro SaaS apps have been my chrome extensions. Since I launched them, they've earned me an average $10k MRR, allowing me to quit my lousy full-time job years ago.
I sold my apps after scaling them for a life-changing lump amount. Since then, I've helped unfulfilled software developers escape the 9-5 through Micro SaaS.
Whether it's a profitable side hustle or a liferaft to quit their job and become their own Micro SaaS boss.
Having built my apps to the point where I could quit my job, then scaled and sold them, I feel I can share my skills with software developers worldwide.
Read my free guide on self-funded SaaS to discover more about Micro SaaS, or download your own copy. 12 chapters cover everything from Idea to Exit.
Watch my YouTube video to learn how to construct a Micro SaaS app in 10 steps.