More on Personal Growth
Darius Foroux
2 years ago
My financial life was changed by a single, straightforward mental model.
Prioritize big-ticket purchases
I've made several spending blunders. I get sick thinking about how much money I spent.
My financial mental model was poor back then.
Stoicism and mindfulness keep me from attaching to those feelings. It still hurts.
Until four or five years ago, I bought a new winter jacket every year.
Ten years ago, I spent twice as much. Now that I have a fantastic, warm winter parka, I don't even consider acquiring another one. No more spending. I'm not looking for jackets either.
Saving time and money by spending well is my thinking paradigm.
The philosophy is expressed in most languages. Cheap is expensive in the Netherlands. This applies beyond shopping.
In this essay, I will offer three examples of how this mental paradigm transformed my financial life.
Publishing books
In 2015, I presented and positioned my first book poorly.
I called the book Huge Life Success and made a funny Canva cover in 30 minutes. This:
That looks nothing like my present books. No logo or style. The book felt amateurish.
The book started bothering me a few weeks after publication. The advice was good, but it didn't appear professional. I studied the book business extensively.
I created a style for all my designs. Branding. Win Your Inner Wars was reissued a year later.
Title, cover, and description changed. Rearranging the chapters improved readability.
Seven years later, the book sells hundreds of copies a month. That taught me a lot.
Rushing to finish a project is enticing. Send it and move forward.
Avoid rushing everything. Relax. Develop your projects. Perform well. Perform the job well.
My first novel was underfunded and underworked. A bad book arrived. I then invested time and money in writing the greatest book I could.
That book still sells.
Traveling
I hate travel. Airports, flights, trains, and lines irritate me.
But, I enjoy traveling to beautiful areas.
I do it strangely. I make up travel rules. I never go to airports in summer. I hate being near airports on holidays. Unworthy.
No vacation packages for me. Those airline packages with a flight, shuttle, and hotel. I've had enough.
I try to avoid crowds and popular spots. July Paris? Nuts and bolts, please. Christmas in NYC? No, please keep me sane.
I fly business class behind. I accept upgrades upon check-in. I prefer driving. I drove from the Netherlands to southern Spain.
Thankfully, no lines. What if travel costs more? Thus? I enjoy it from the start. I start traveling then.
I rarely travel since I'm so difficult. One great excursion beats several average ones.
Personal effectiveness
New apps, tools, and strategies intrigue most productivity professionals.
No.
I researched years ago. I spent years investigating productivity in university.
I bought books, courses, applications, and tools. It was expensive and time-consuming.
Im finished. Productivity no longer costs me time or money. OK. I worked on it once and now follow my strategy.
I avoid new programs and systems. My stuff works. Why change winners?
Spending wisely saves time and money.
Spending wisely means spending once. Many people ignore productivity. It's understudied. No classes.
Some assume reading a few articles or a book is enough. Productivity is personal. You need a personal system.
Time invested is one-time. You can trust your system for life once you find it.
Concentrate on the expensive choices.
Life's short. Saving money quickly is enticing.
Spend less on groceries today. True. That won't fix your finances.
Adopt a lifestyle that makes you affluent over time. Consider major choices.
Are they causing long-term poverty? Are you richer?
Leasing cars comes to mind. The automobile costs a fortune today. The premium could accomplish a million nice things.
Focusing on important decisions makes life easier. Consider your future. You want to improve next year.
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.
James White
3 years ago
Ray Dalio suggests reading these three books in 2022.
An inspiring reading list
I'm no billionaire or hedge-fund manager. My bank account doesn't have millions. Ray Dalio's love of reading motivates me to think differently.
Here are some books recommended by Ray Dalio. Each influenced me. Hope they'll help you.
Sapiens by Yuval Noah Harari
Page Count: 512
Rating on Goodreads: 4.39
My favorite nonfiction book.
Sapiens explores human evolution. It explains how Homo Sapiens developed from hunter-gatherers to a dominant species. Amazing!
Sapiens will teach you about human history. Yuval Noah Harari has a follow-up book on human evolution.
My favorite book quotes are:
The tendency for luxuries to turn into necessities and give rise to new obligations is one of history's few unbreakable laws.
Happiness is not dependent on material wealth, physical health, or even community. Instead, it depends on how closely subjective expectations and objective circumstances align.
The romantic comparison between today's industry, which obliterates the environment, and our forefathers, who coexisted well with nature, is unfounded. Homo sapiens held the record among all organisms for eradicating the most plant and animal species even before the Industrial Revolution. The unfortunate distinction of being the most lethal species in the history of life belongs to us.
The Power Of Habit by Charles Duhigg
Page Count: 375
Rating on Goodreads: 4.13
Great book: The Power Of Habit. It illustrates why habits are everything. The book explains how healthier habits can improve your life, career, and society.
The Power of Habit rocks. It's a great book on productivity. Its suggestions helped me build healthier behaviors (and drop bad ones).
Read ASAP!
My favorite book quotes are:
Change may not occur quickly or without difficulty. However, almost any behavior may be changed with enough time and effort.
People who exercise begin to eat better and produce more at work. They are less smokers and are more patient with friends and family. They claim to feel less anxious and use their credit cards less frequently. A fundamental habit that sparks broad change is exercise.
Habits are strong but also delicate. They may develop independently of our awareness or may be purposefully created. They frequently happen without our consent, but they can be altered by changing their constituent pieces. They have a much greater influence on how we live than we realize; in fact, they are so powerful that they cause our brains to adhere to them above all else, including common sense.
Tribe Of Mentors by Tim Ferriss
Page Count: 561
Rating on Goodreads: 4.06
Unusual book structure. It's worth reading if you want to learn from successful people.
The book is Q&A-style. Tim questions everyone. Each chapter features a different person's life-changing advice. In the book, Pressfield, Willink, Grylls, and Ravikant are interviewed.
Amazing!
My favorite book quotes are:
According to one's courage, life can either get smaller or bigger.
Don't engage in actions that you are aware are immoral. The reputation you have with yourself is all that constitutes self-esteem. Always be aware.
People mistakenly believe that focusing means accepting the task at hand. However, that is in no way what it represents. It entails rejecting the numerous other worthwhile suggestions that exist. You must choose wisely. Actually, I'm just as proud of the things we haven't accomplished as I am of what I have. Saying no to 1,000 things is what innovation is.
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Sam Hickmann
3 years ago
The Jordan 6 Rings Reintroduce Classic Bulls
The Jordan 6 Rings return in Bulls colors, a deviation from previous releases. The signature red color is used on the midsole and heel, as well as the chenille patch and pull tab. The rest of the latter fixture is black, matching the outsole and adjacent Jumpman logos. Finally, white completes the look, from the leather mudguard to the lace unit. Here's a closer look at the Jordan 6 Rings. Sizes should be available soon on Nike.com and select retailers. Also, official photos of the Air Jordan 1 Denim have surfaced.
Jordan 6 Rings
Release Date: 2022
Color: N/A
Mens: $130
Style Code: 322992-126
Sneaker News
3 years ago
This Month Will See The Release Of Travis Scott x Nike Footwear
Following the catastrophes at Astroworld, Travis Scott was swiftly vilified by both media outlets and fans alike, and the names who had previously supported him were quickly abandoned. Nike, on the other hand, remained silent, only delaying the release of La Flame's planned collaborations, such as the Air Max 1 and Air Trainer 1, indefinitely. While some may believe it is too soon for the artist to return to the spotlight, the Swoosh has other ideas, as Nice Kicks reveals that these exact sneakers will be released in May.
Both the Travis Scott x Nike Air Max 1 and the Travis Scott x Nike Air Trainer 1 are set to come in two colorways this month. Tinker Hatfield's renowned runner will meet La Flame's "Baroque Brown" and "Saturn Gold" make-ups, which have been altered with backwards Swooshes and outdoors-themed webbing. The high-top trainer is being customized with Hatfield's "Wheat" and "Grey Haze" palettes, both of which include zippers across the heel, co-branded patches, and other details.
See below for a closer look at the four footwear. TravisScott.com is expected to release the shoes on May 20th, according to Nice Kicks. Following that, on May 27th, Nike SNKRS will release the shoe.
Travis Scott x Nike Air Max 1 "Baroque Brown"
Release Date: 2022
Color: Baroque Brown/Lemon Drop/Wheat/Chile Red
Mens: $160
Style Code: DO9392-200
Pre-School: $85
Style Code: DN4169-200
Infant & Toddler: $70
Style Code: DN4170-200
Travis Scott x Nike Air Max 1 "Saturn Gold"
Release Date: 2022
Color: N/A
Mens: $160
Style Code: DO9392-700
Travis Scott x Nike Air Trainer 1 "Wheat"
Restock Date: May 27th, 2022 (Friday)
Original Release Date: May 20th, 2022 (Friday)
Color: N/A
Mens: $140
Style Code: DR7515-200
Travis Scott x Nike Air Trainer 1 "Grey Haze"
Restock Date: May 27th, 2022 (Friday)
Original Release Date: May 20th, 2022 (Friday)
Color: N/A
Mens: $140
Style Code: DR7515-001
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!
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