More on Personal Growth

Jari Roomer
3 years ago
Successful people have this one skill.
Without self-control, you'll waste time chasing dopamine fixes.
I found a powerful quote in Tony Robbins' Awaken The Giant Within:
“Most of the challenges that we have in our personal lives come from a short-term focus” — Tony Robbins
Most people are short-term oriented, but highly successful people are long-term oriented.
Successful people act in line with their long-term goals and values, while the rest are distracted by short-term pleasures and dopamine fixes.
Instant gratification wrecks lives
Instant pleasure is fleeting. Quickly fading effects leave you craving more stimulation.
Before you know it, you're in a cycle of quick fixes. This explains binging on food, social media, and Netflix.
These things cause a dopamine spike, which is entertaining. This dopamine spike crashes quickly, leaving you craving more stimulation.
It's fine to watch TV or play video games occasionally. Problems arise when brain impulses aren't controlled. You waste hours chasing dopamine fixes.
Instant gratification becomes problematic when it interferes with long-term goals, happiness, and life fulfillment.
Most rewarding things require delay
Life's greatest rewards require patience and delayed gratification. They must be earned through patience, consistency, and effort.
Ex:
A fit, healthy body
A deep connection with your spouse
A thriving career/business
A healthy financial situation
These are some of life's most rewarding things, but they take work and patience. They all require the ability to delay gratification.
To have a healthy bank account, you must save (and invest) a large portion of your monthly income. This means no new tech or clothes.
If you want a fit, healthy body, you must eat better and exercise three times a week. So no fast food and Netflix.
It's a battle between what you want now and what you want most.
Successful people choose what they want most over what they want now. It's a major difference.
Instant vs. delayed gratification
Most people subconsciously prefer instant rewards over future rewards, even if the future rewards are more significant.
We humans aren't logical. Emotions and instincts drive us. So we act against our goals and values.
Fortunately, instant gratification bias can be overridden. This is a modern superpower. Effective methods include:
#1: Train your brain to handle overstimulation
Training your brain to function without constant stimulation is a powerful change. Boredom can lead to long-term rewards.
Unlike impulsive shopping, saving money is boring. Having lots of cash is amazing.
Compared to video games, deep work is boring. A successful online business is rewarding.
Reading books is boring compared to scrolling through funny videos on social media. Knowledge is invaluable.
You can't do these things if your brain is overstimulated. Your impulses will control you. To reduce overstimulation addiction, try:
Daily meditation (10 minutes is enough)
Daily study/work for 90 minutes (no distractions allowed)
First hour of the day without phone, social media, and Netflix
Nature walks, journaling, reading, sports, etc.
#2: Make Important Activities Less Intimidating
Instant gratification helps us cope with stress. Starting a book or business can be intimidating. Video games and social media offer a quick escape in such situations.
Make intimidating tasks less so. Break them down into small tasks. Start a new business/side-hustle by:
Get domain name
Design website
Write out a business plan
Research competition/peers
Approach first potential client
Instead of one big mountain, divide it into smaller sub-tasks. This makes a task easier and less intimidating.
#3: Plan ahead for important activities
Distractions will invade unplanned time. Your time is dictated by your impulses, which are usually Netflix, social media, fast food, and video games. It wants quick rewards and dopamine fixes.
Plan your days and be proactive with your time. Studies show that scheduling activities makes you 3x more likely to do them.
To achieve big goals, you must plan. Don't gamble.
Want to get fit? Schedule next week's workouts. Want a side-job? Schedule your work time.

Tim Denning
2 years ago
Read These Books on Personal Finance to Boost Your Net Worth
And retire sooner.
Books can make you filthy rich.
If you apply what you learn. In 2011, I was broke and had broken dreams.
Someone suggested I read finance books. One Up On Wall Street was his first recommendation.
Finance books were my crack.
I've read every money book since then. Some are good, but most stink.
These books will make you rich.
The Almanack of Naval Ravikant by Eric Jorgenson
This isn't a cliche book.
This book was inspired by a How to Get Rich tweet thread.
It’s one of the best tweets I’ve ever read.
Naval thinks differently. He nukes ordinary ideas. I've never heard better money advice.
Eric Jorgenson wrote a book about this tweet thread with Navals permission. A must-read, easy-to-digest book.
Best quote
Seek wealth, not money or status. Wealth is having assets that earn while you sleep. Money is how we transfer time and wealth. Status is your place in the social hierarchy — Naval
Morgan Housel's The Psychology of Money
Many finance books advise investing like a dunce.
They almost all peddle the buy an index fund BS. Different book.
It's about money-making psychology. Because any fool can get rich and drunk on their ego. Few can consistently make money.
Each chapter is short. A single-page chapter breaks all book publishing rules.
Best quote
Spending money to show people how much money you have is the fastest way to have less money — Morgan Housel
J.L. Collins' The Simple Path to Wealth
Most of the best money books were written by bloggers.
JL Collins blogs. This easy-to-read book was written for his daughter.
This book popularized the phrase F You Money. With enough money in your bank account and investment portfolio, you can say F You more.
A bad boss is an example. You can leave instead of enduring his wrath.
You can then sit at home and look for another job while financially secure. JL says its mind-freedom is powerful.
Best phrasing
You own the things you own and they in turn own you — J.L. Collins
Tony Robbins' Unshakeable
I like Tony. This book makes me sweaty.
Tony interviews the world's top financiers. He interviews people who rarely do so.
This book taught me all-weather portfolio. It's a way to invest in different asset classes in good, bad, recession, or depression times.
Look at it:
Investing isn’t about buying one big winner — that’s gambling. It’s about investing in a diversified portfolio of assets.
Best phrasing
The best opportunities come in times of maximum pessimism — Tony Robbins
Ben Graham's The Intelligent Investor
This book helped me distinguish between a spectator and an investor.
Spectators are those who shout that crypto, NFTs, or XYZ platform will die.
Tourists. They want attention and to say "I told you so." They make short-term and long-term predictions like fortunetellers. LOL. Idiots.
Benjamin Graham teaches smart investing. You'll buy a long-term asset. To be confident in recessions, use dollar-cost averaging.
Best phrasing
Those who do not remember the past are condemned to repeat it. — Benjamin Graham
The Napoleon Hill book Think and Grow Rich
This classic book introduced positive thinking to modern self-help.
Lazy pessimists can't become rich. No way.
Napoleon said, "Thoughts create reality."
No surprise that he discusses obsession and focus in this book. They are the fastest ways to make more money to invest in time and wealth-protecting assets.
Best phrasing
The starting point of all achievement is DESIRE. Keep this constantly in mind. Weak desire brings weak results, just as a small fire makes a small amount of heat — Napoleon Hill
Ramit Sethi's book I Will Teach You To Be Rich
This book is mostly good. The part about credit cards is trash.
Avoid credit card temptations. I don't care about their airline points.
This book teaches you to master money basics (that many people mess up) then automate it so your monkey brain doesn't ruin your financial future.
The book includes great negotiation tactics to help you make more money in less time.
Best quote
The 85 Percent Solution: Getting started is more important than becoming an expert — Ramit Sethi
David Bach's The Automatic Millionaire
You've probably met a six- or seven-figure earner who's broke. All their money goes to useless things like cars.
Money isn't as essential as what you do with it. David teaches how to automate your earnings for more money.
Compounding works once investing is automated. So you get rich.
His strategy eliminates luck and (almost) guarantees millionaire status.
Best phrasing
Every time you earn one dollar, make sure to pay yourself first — David Bach
Thomas J. Stanley's The Millionaire Next Door
Thomas defies the definition of rich.
He spends much of the book highlighting millionaire traits he's studied.
Rich people are quiet, so you wouldn't know they're wealthy. They don't earn much money or drive a BMW.
Thomas will give you the math to get started.
Best phrasing
I am not impressed with what people own. But I’m impressed with what they achieve. I’m proud to be a physician. Always strive to be the best in your field…. Don’t chase money. If you are the best in your field, money will find you. — Thomas J. Stanley
by Bill Perkins "Die With Zero"
Let’s end with one last book.
Bill's book angered many people. He says we spend too much time saving for retirement and die rich. That bank money is lost time.
Your grandkids could use the money. When children inherit money, they become lazy, entitled a-holes.
Bill wants us to spend our money on life-enhancing experiences. Stop saving money like monopoly monkeys.
Best phrasing
You should be focusing on maximizing your life enjoyment rather than on maximizing your wealth. Those are two very different goals. Money is just a means to an end: Having money helps you to achieve the more important goal of enjoying your life. But trying to maximize money actually gets in the way of achieving the more important goal — Bill Perkins

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.
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Laura Sanders
3 years ago
Xenobots, tiny living machines, can duplicate themselves.
Strange and complex behavior of frog cell blobs
A xenobot “parent,” shaped like a hungry Pac-Man (shown in red false color), created an “offspring” xenobot (green sphere) by gathering loose frog cells in its opening.
Tiny “living machines” made of frog cells can make copies of themselves. This newly discovered renewal mechanism may help create self-renewing biological machines.
According to Kirstin Petersen, an electrical and computer engineer at Cornell University who studies groups of robots, “this is an extremely exciting breakthrough.” She says self-replicating robots are a big step toward human-free systems.
Researchers described the behavior of xenobots earlier this year (SN: 3/31/21). Small clumps of skin stem cells from frog embryos knitted themselves into small spheres and started moving. Cilia, or cellular extensions, powered the xenobots around their lab dishes.
The findings are published in the Proceedings of the National Academy of Sciences on Dec. 7. The xenobots can gather loose frog cells into spheres, which then form xenobots.
The researchers call this type of movement-induced reproduction kinematic self-replication. The study's coauthor, Douglas Blackiston of Tufts University in Medford, Massachusetts, and Harvard University, says this is typical. For example, sexual reproduction requires parental sperm and egg cells. Sometimes cells split or budded off from a parent.
“This is unique,” Blackiston says. These xenobots “find loose parts in the environment and cobble them together.” This second generation of xenobots can move like their parents, Blackiston says.
The researchers discovered that spheroid xenobots could only produce one more generation before dying out. The original xenobots' shape was predicted by an artificial intelligence program, allowing for four generations of replication.
A C shape, like an openmouthed Pac-Man, was predicted to be a more efficient progenitor. When improved xenobots were let loose in a dish, they began scooping up loose cells into their gaping “mouths,” forming more sphere-shaped bots (see image below). As many as 50 cells clumped together in the opening of a parent to form a mobile offspring. A xenobot is made up of 4,000–6,000 frog cells.
Petersen likes the Xenobots' small size. “The fact that they were able to do this at such a small scale just makes it even better,” she says. Miniature xenobots could sculpt tissues for implantation or deliver therapeutics inside the body.
Beyond the xenobots' potential jobs, the research advances an important science, says study coauthor and Tufts developmental biologist Michael Levin. The science of anticipating and controlling the outcomes of complex systems, he says.
“No one could have predicted this,” Levin says. “They regularly surprise us.” Researchers can use xenobots to test the unexpected. “This is about advancing the science of being less surprised,” Levin says.
Sam Hickmann
3 years ago
What is headline inflation?
Headline inflation is the raw Consumer price index (CPI) reported monthly by the Bureau of labour statistics (BLS). CPI measures inflation by calculating the cost of a fixed basket of goods. The CPI uses a base year to index the current year's prices.
Explaining Inflation
As it includes all aspects of an economy that experience inflation, headline inflation is not adjusted to remove volatile figures. Headline inflation is often linked to cost-of-living changes, which is useful for consumers.
The headline figure doesn't account for seasonality or volatile food and energy prices, which are removed from the core CPI. Headline inflation is usually annualized, so a monthly headline figure of 4% inflation would equal 4% inflation for the year if repeated for 12 months. Top-line inflation is compared year-over-year.
Inflation's downsides
Inflation erodes future dollar values, can stifle economic growth, and can raise interest rates. Core inflation is often considered a better metric than headline inflation. Investors and economists use headline and core results to set growth forecasts and monetary policy.
Core Inflation
Core inflation removes volatile CPI components that can distort the headline number. Food and energy costs are commonly removed. Environmental shifts that affect crop growth can affect food prices outside of the economy. Political dissent can affect energy costs, such as oil production.
From 1957 to 2018, the U.S. averaged 3.64 percent core inflation. In June 1980, the rate reached 13.60%. May 1957 had 0% inflation. The Fed's core inflation target for 2022 is 3%.
Central bank:
A central bank has privileged control over a nation's or group's money and credit. Modern central banks are responsible for monetary policy and bank regulation. Central banks are anti-competitive and non-market-based. Many central banks are not government agencies and are therefore considered politically independent. Even if a central bank isn't government-owned, its privileges are protected by law. A central bank's legal monopoly status gives it the right to issue banknotes and cash. Private commercial banks can only issue demand deposits.
What are living costs?
The cost of living is the amount needed to cover housing, food, taxes, and healthcare in a certain place and time. Cost of living is used to compare the cost of living between cities and is tied to wages. If expenses are higher in a city like New York, salaries must be higher so people can live there.
What's U.S. bureau of labor statistics?
BLS collects and distributes economic and labor market data about the U.S. Its reports include the CPI and PPI, both important inflation measures.

Sammy Abdullah
3 years ago
SaaS payback period data
It's ok and even desired to be unprofitable if you're gaining revenue at a reasonable cost and have 100%+ net dollar retention, meaning you never lose customers and expand them. To estimate the acceptable cost of new SaaS revenue, we compare new revenue to operating loss and payback period. If you pay back the customer acquisition cost in 1.5 years and never lose them (100%+ NDR), you're doing well.
To evaluate payback period, we compared new revenue to net operating loss for the last 73 SaaS companies to IPO since October 2017. (55 out of 73). Here's the data. 1/(new revenue/operating loss) equals payback period. New revenue/operating loss equals cost of new revenue.
Payback averages a year. 55 SaaS companies that weren't profitable at IPO got a 1-year payback. Outstanding. If you pay for a customer in a year and never lose them (100%+ NDR), you're establishing a valuable business. The average was 1.3 years, which is within the 1.5-year range.
New revenue costs $0.96 on average. These SaaS companies lost $0.96 every $1 of new revenue last year. Again, impressive. Average new revenue per operating loss was $1.59.
Loss-in-operations definition. Operating loss revenue COGS S&M R&D G&A (technical point: be sure to use the absolute value of operating loss). It's wrong to only consider S&M costs and ignore other business costs. Operating loss and new revenue are measured over one year to eliminate seasonality.
Operating losses are desirable if you never lose a customer and have a quick payback period, especially when SaaS enterprises are valued on ARR. The payback period should be under 1.5 years, the cost of new income < $1, and net dollar retention 100%.
