More on Personal Growth
Simon Ash
2 years ago
The Three Most Effective Questions for Ongoing Development
The Traffic Light Approach to Reviewing Personal, Team and Project Development
What needs improvement? If you want to improve, you need to practice your sport, musical instrument, habit, or work project. You need to assess your progress.
Continuous improvement is the foundation of focused practice and a growth mentality. Not just individually. High-performing teams pursue improvement. Right? Why is it hard?
As a leadership coach, senior manager, and high-level athlete, I've found three key questions that may unlock high performance in individuals and teams.
Problems with Reviews
Reviewing and improving performance is crucial, however I hate seeing review sessions in my diary. I rarely respond to questionnaire pop-ups or emails. Why?
Time constrains. Requests to fill out questionnaires often state they will take 10–15 minutes, but I can think of a million other things to do with that time. Next, review overload. Businesses can easily request comments online. No matter what you buy, someone will ask for your opinion. This bombardment might make feedback seem bad, which is bad.
The problem is that we might feel that way about important things like personal growth and work performance. Managers and team leaders face a greater challenge.
When to Conduct a Review
We must be wise about reviewing things that matter to us. Timing and duration matter. Reviewing the experience as quickly as possible preserves information and sentiments. Time must be brief. The review's importance and size will determine its length. We might only take a few seconds to review our morning coffee, but we might require more time for that six-month work project.
These post-event reviews should be supplemented by periodic reflection. Journaling can help with daily reflections, but I also like to undertake personal reviews every six months on vacation or at a retreat.
As an employee or line manager, you don't want to wait a year for a performance assessment. Little and frequently is best, with a more formal and in-depth assessment (typically with a written report) in 6 and 12 months.
The Easiest Method to Conduct a Review Session
I follow Einstein's review process:
“Make things as simple as possible but no simpler.”
Thus, it should be brief but deliver the necessary feedback. Quality critique is hard to receive if the process is overly complicated or long.
I have led or participated in many review processes, from strategic overhauls of big organizations to personal goal coaching. Three key questions guide the process at either end:
What ought to stop being done?
What should we do going forward?
What should we do first?
Following the Rule of 3, I compare it to traffic lights. Red, amber, and green lights:
Red What ought should we stop?
Amber What ought to we keep up?
Green Where should we begin?
This approach is easy to understand and self-explanatory, however below are some examples under each area.
Red What ought should we stop?
As a team or individually, we must stop doing things to improve.
Sometimes they're bad. If we want to lose weight, we should avoid sweets. If a team culture is bad, we may need to stop unpleasant behavior like gossiping instead of having difficult conversations.
Not all things we should stop are wrong. Time matters. Since it is finite, we sometimes have to stop nice things to focus on the most important. Good to Great author Jim Collins famously said:
“Don’t let the good be the enemy of the great.”
Prioritizing requires this idea. Thus, decide what to stop to prioritize.
Amber What ought to we keep up?
Should we continue with the amber light? It helps us decide what to keep doing during review. Many items fall into this category, so focus on those that make the most progress.
Which activities have the most impact? Which behaviors create the best culture? Success-building habits?
Use these questions to find positive momentum. These are the fly-wheel motions, according to Jim Collins. The Compound Effect author Darren Hardy says:
“Consistency is the key to achieving and maintaining momentum.”
What can you do consistently to reach your goal?
Green Where should we begin?
Finally, green lights indicate new beginnings. Red/amber difficulties may be involved. Stopping a red issue may give you more time to do something helpful (in the amber).
This green space inspires creativity. Kolbs learning cycle requires active exploration to progress. Thus, it's crucial to think of new approaches, try them out, and fail if required.
This notion underpins lean start-build, up's measure, learn approach and agile's trying, testing, and reviewing. Try new things until you find what works. Thomas Edison, the lighting legend, exclaimed:
“There is a way to do it better — find it!”
Failure is acceptable, but if you want to fail forward, look back on what you've done.
John Maxwell concurred with Edison:
“Fail early, fail often, but always fail forward”
A good review procedure lets us accomplish that. To avoid failure, we must act, experiment, and reflect.
Use the traffic light system to prioritize queries. Ask:
Red What needs to stop?
Amber What should continue to occur?
Green What might be initiated?
Take a moment to reflect on your day. Check your priorities with these three questions. Even if merely to confirm your direction, it's a terrific exercise!
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.
Leah
3 years ago
The Burnout Recovery Secrets Nobody Is Talking About
What works and what’s just more toxic positivity
Just keep at it; you’ll get it.
I closed the Zoom call and immediately dropped my head. Open tabs included material on inspiration, burnout, and recovery.
I searched everywhere for ways to avoid burnout.
It wasn't that I needed to keep going, change my routine, employ 8D audio playlists, or come up with fresh ideas. I had several ideas and a schedule. I knew what to do.
I wasn't interested. I kept reading, changing my self-care and mental health routines, and writing even though it was tiring.
Since burnout became a psychiatric illness in 2019, thousands have shared their experiences. It's spreading rapidly among writers.
What is the actual key to recovering from burnout?
Every A-list burnout story emphasizes prevention. Other lists provide repackaged self-care tips. More discuss mental health.
It's like the mid-2000s, when pink quotes about bubble baths saturated social media.
The self-care mania cost us all. Self-care is crucial, but utilizing it to address everything didn't work then or now.
How can you recover from burnout?
Time
Are extended breaks actually good for you? Most people need a break every 62 days or so to avoid burnout.
Real-life burnout victims all took breaks. Perhaps not a long hiatus, but breaks nonetheless.
Burnout is slow and gradual. It takes little bits of your motivation and passion at a time. Sometimes it’s so slow that you barely notice or blame it on other things like stress and poor sleep.
Burnout doesn't come overnight; neither will recovery.
I don’t care what anyone else says the cure for burnout is. It has to be time because time is what gave us all burnout in the first place.
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Trent Lapinski
3 years ago
What The Hell Is A Crypto Punk?
We are Crypto Punks, and we are changing your world.
A “Crypto Punk” is a new generation of entrepreneurs who value individual liberty and collective value creation and co-creation through decentralization. While many Crypto Punks were born and raised in a digital world, some of the early pioneers in the crypto space are from the Oregon Trail generation. They were born to an analog world, but grew up simultaneously alongside the birth of home computing, the Internet, and mobile computing.
A Crypto Punk’s world view is not the same as previous generations. By the time most Crypto Punks were born everything from fiat currency, the stock market, pharmaceuticals, the Internet, to advanced operating systems and microprocessing were already present or emerging. Crypto Punks were born into pre-existing conditions and systems of control, not governed by logic or reason but by greed, corporatism, subversion, bureaucracy, censorship, and inefficiency.
All Systems Are Human Made
Crypto Punks understand that all systems were created by people and that previous generations did not have access to information technologies that we have today. This is why Crypto Punks have different values than their parents, and value liberty, decentralization, equality, social justice, and freedom over wealth, money, and power. They understand that the only path forward is to work together to build new and better systems that make the old world order obsolete.
Unlike the original cypher punks and cyber punks, Crypto Punks are a new iteration or evolution of these previous cultures influenced by cryptography, blockchain technology, crypto economics, libertarianism, holographics, democratic socialism, and artificial intelligence. They are tasked with not only undoing the mistakes of previous generations, but also innovating and creating new ways of solving complex problems with advanced technology and solutions.
Where Crypto Punks truly differ is in their understanding that computer systems can exist for more than just engagement and entertainment, but actually improve the human condition by automating bureaucracy and inefficiency by creating more efficient economic incentives and systems.
Crypto Punks Value Transparency and Do Not Trust Flawed, Unequal, and Corrupt Systems
Crypto Punks have a strong distrust for inherently flawed and corrupt systems. This why Crypto Punks value transparency, free speech, privacy, and decentralization. As well as arguably computer systems over human powered systems.
Crypto Punks are the children of the Great Recession, and will never forget the economic corruption that still enslaves younger generations.
Crypto Punks were born to think different, and raised by computers to view reality through an LED looking glass. They will not surrender to the flawed systems of economic wage slavery, inequality, censorship, and subjection. They will literally engineer their own unstoppable financial systems and trade in cryptography over fiat currency merely to prove that belief systems are more powerful than corruption.
Crypto Punks are here to help achieve freedom from world governments, corporations and bankers who monetizine our data to control our lives.
Crypto Punks Decentralize
Despite all the evils of the world today, Crypto Punks know they have the power to create change. This is why Crypto Punks are optimistic about the future despite all the indicators that humanity is destined for failure.
Crypto Punks believe in systems that prioritize people and the planet above profit. Even so, Crypto Punks still believe in capitalistic systems, but only capitalistic systems that incentivize good behaviors that do not violate the common good for the sake of profit.
Cyber Punks Are Co-Creators
We are Crypto Punks, and we will build a better world for all of us. For the true price of creation is not in US dollars, but through working together as equals to replace the unequal and corrupt greedy systems of previous generations.
Where they have failed, Crypto Punks will succeed. Not because we want to, but because we have to. The world we were born into is so corrupt and its systems so flawed and unequal we were never given a choice.
We have to be the change we seek.
We are Crypto Punks.
Either help us, or get out of our way.
Are you a Crypto Punk?
M.G. Siegler
2 years ago
G3nerative
Generative AI hype: some thoughts
The sudden surge in "generative AI" startups and projects feels like the inverse of the recent "web3" boom. Both came from hyped-up pots. But while web3 hyped idealistic tech and an easy way to make money, generative AI hypes unsettling tech and questions whether it can be used to make money.
Web3 is technology looking for problems to solve, while generative AI is technology creating almost too many solutions. Web3 has been evangelists trying to solve old problems with new technology. As Generative AI evolves, users are resolving old problems in stunning new ways.
It's a jab at web3, but it's true. Web3's hype, including crypto, was unhealthy. Always expected a tech crash and shakeout. Tech that won't look like "web3" but will enhance "web2"
But that doesn't mean AI hype is healthy. There'll be plenty of bullshit here, too. As moths to a flame, hype attracts charlatans. Again, the difference is the different starting point. People want to use it. Try it.
With the beta launch of Dall-E 2 earlier this year, a new class of consumer product took off. Midjourney followed suit (despite having to jump through the Discord server hoops). Twelve more generative art projects. Lensa, Prisma Labs' generative AI self-portrait project, may have topped the hype (a startup which has actually been going after this general space for quite a while). This week, ChatGPT went off-topic.
This has a "fake-it-till-you-make-it" vibe. We give these projects too much credit because they create easy illusions. This also unlocks new forms of creativity. And faith in new possibilities.
As a user, it's thrilling. We're just getting started. These projects are not only fun to play with, but each week brings a new breakthrough. As an investor, it's all happening so fast, with so much hype (and ethical and societal questions), that no one knows how it will turn out. Web3's demand won't be the issue. Too much demand may cause servers to melt down, sending costs soaring. Companies will try to mix rapidly evolving tech to meet user demand and create businesses. Frustratingly difficult.
Anyway, I wanted an excuse to post some Lensa selfies.
These are really weird. I recognize them as me or a version of me, but I have no memory of them being taken. It's surreal, out-of-body. Uncanny Valley.
Aniket
3 years ago
Yahoo could have purchased Google for $1 billion
Let's see this once-dominant IT corporation crumble.
What's the capital of Kazakhstan? If you don't know the answer, you can probably find it by Googling. Google Search returned results for Nur-Sultan in 0.66 seconds.
Google is the best search engine I've ever used. Did you know another search engine ruled the Internet? I'm sure you guessed Yahoo!
Google's friendly UI and wide selection of services make it my top choice. Let's explore Yahoo's decline.
Yahoo!
YAHOO stands for Yet Another Hierarchically Organized Oracle. Jerry Yang and David Filo established Yahoo.
Yahoo is primarily a search engine and email provider. It offers News and an advertising platform. It was a popular website in 1995 that let people search the Internet directly. Yahoo began offering free email in 1997 by acquiring RocketMail.
According to a study, Yahoo used Google Search Engine technology until 2000 and then developed its own in 2004.
Yahoo! rejected buying Google for $1 billion
Larry Page and Sergey Brin, Google's founders, approached Yahoo in 1998 to sell Google for $1 billion so they could focus on their studies. Yahoo denied the offer, thinking it was overvalued at the time.
Yahoo realized its error and offered Google $3 billion in 2002, but Google demanded $5 billion since it was more valuable. Yahoo thought $5 billion was overpriced for the existing market.
In 2022, Google is worth $1.56 Trillion.
What happened to Yahoo!
Yahoo refused to buy Google, and Google's valuation rose, making a purchase unfeasible.
Yahoo started losing users when Google launched Gmail. Google's UI was far cleaner than Yahoo's.
Yahoo offered $1 billion to buy Facebook in July 2006, but Zuckerberg and the board sought $1.1 billion. Yahoo rejected, and Facebook's valuation rose, making it difficult to buy.
Yahoo was losing users daily while Google and Facebook gained many. Google and Facebook's popularity soared. Yahoo lost value daily.
Microsoft offered $45 billion to buy Yahoo in February 2008, but Yahoo declined. Microsoft increased its bid to $47 billion after Yahoo said it was too low, but Yahoo rejected it. Then Microsoft rejected Yahoo’s 10% bid increase in May 2008.
In 2015, Verizon bought Yahoo for $4.5 billion, and Apollo Global Management bought 90% of Yahoo's shares for $5 billion in May 2021. Verizon kept 10%.
Yahoo's opportunity to acquire Google and Facebook could have been a turning moment. It declined Microsoft's $45 billion deal in 2008 and was sold to Verizon for $4.5 billion in 2015. Poor decisions and lack of vision caused its downfall. Yahoo's aim wasn't obvious and it didn't stick to a single domain.
Hence, a corporation needs a clear vision and a leader who can see its future.
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