Hustle Hub #31

New to Hustle Hub? Make sure to subscribe for more!

Hey friends,

Recently I’ve been reading a newsletter written by Cornellius Yudha Wijay to learn various tips for data career advice, machine learning, and cool tricks to use Python. His sharing has always been very crisp, straight-to-the-point, and packed with insights (especially from the data career’s standpoint).

Highly recommended if you’re keen to take your data career to the next level. Check it out below 👇🏻

In today's issue, I’d like to share with you how to solve problems using First Principles thinking, how I got scammed 😂, a book on system design, and the launch of the ChatGPT iOS app.

Let’s get to it! 🚀 

🛖 What's in the hub today?

• Tip: How to solve problems using First Principles thinking

• Mistake: I got scammed

• Learning: Never do things out of desperation

• Book: System Design Interview

• Tool: ChatGPT (iOS app)

⭐️ 1 Tip

How to Solve Problems Using First Principles Thinking

First Principles thinking was first popularised by Elon Musk when he shared the Physics framework that he has been using for problem-solving, which had led to all the innovative companies (SpaceX, Tesla, Neuralink etc.) that he built to solve critical problems.

Here’s how he described First Principles thinking:

While most people tend to follow what other people are doing, First Principles thinking is basically the practice of actively questioning every assumption you think you know about a given problem or scenario, and then creating new knowledge and solutions from scratch.

This is not easy, but it’d often help you solve problems with innovative solutions instead of just following what has been done before without questioning the norm.

🧠 Here are 3 steps to practise First Principles Thinking

1️⃣ Step 1: Identify and define your assumptions

• When faced with a problem, simply write down your assumptions about the problem and double-check if they are true.

• Example (How Elon Musk built Tesla)

  • Before Tesla, most people assumed that making car battery packs was really expensive and that's just the way they will always be.

  • Historically, it has cost $600 per kilowatt hour. It's not going to be much better than that in the future.

2️⃣ Step 2: Break down the problem into its fundamental principles

• Understand the basic truths of anything and challenge socially accepted beliefs.

• Ask powerful questions (5 Whys) to uncover these truths:

  • Why do I think this way?

  • Is my assumption/thinking really true?

  • What am I sure is really true?

  • What if I’m wrong?

• Example (How Elon Musk built Tesla)

  • While most people assumed that making car battery packs was expensive, Elon challenged the assumptions by asking these questions instead:

    • What are the material constituents of the batteries?

    • What is the stock-market value of the material constituents?

    • Is it really that expensive?

3️⃣ Step 3: Create innovative solutions from scratch

• Once you've identified and broken down your problems or assumptions into their most basic truths, you can begin to create new insightful solutions from scratch.

• Example (How Elon Musk built Tesla)

  • After asking the questions above, Elon realised that the basic materials got cobalt, nickel, aluminium, carbon, some polymers for separation, and a seal can.

  • He broke that down on a material basis and ask, "If we bought that on the London Metal Exchange, what would each of those things cost?"It's like $80 per kilowatt hour (NOT $600 per kilowatt hour).

  • So clearly you just need to think of clever ways to take those materials and combine them into the shape of a battery cell and you can have batteries that are much, much cheaper than anyone realizes.

  • And that’s how Tesla was born 🏎️

🤝🏻Over to you:

• When faced with problems next time, you can try these 3 steps to challenge the assumptions and come up with more innovative solutions.

• Very often, you’d be surprised that sometimes the solution is much simpler than we are originally using. It’s just that we over-complicated the problems.

⚠️ 1 Mistake

Okay… It’s a bit embarrassing to say this, but I got scammed back in 2019. 🤦🏻‍♂️

Here’s the short story of what happened:

• I was approached by a conference organiser to speak at a conference in Hong Kong.

• I was sceptical at first, thinking that it was too good to be true. Weirdly speaking, I also got to pay $200 to speak at the conference.

• Because I was so desperate to gain exposure and improve my public speaking skills as a fresh graduate, I decided to “trust” the person, hoping that it was real.

• So I made the payment, booked a flight ticket with accommodation, and BOOM! The person ghosted me and I never heard back from him anymore. 🤯

My suspicion was valid. But I succumbed to my desperation. 🫠

🧠 1 Learning

You might be wondering if I still went to Hong Kong since I already booked the flight tickets. The answer is — YES!

I decided to switch my perspective from wallowing in my self-pity to taking this as an opportunity to travel to Hong Kong (my first time). 🇭🇰

Suddenly, I had an “accidental” solo trip. 😂

🧠 Here’s what I’ve learned:

• Never do things out of desperation because it’s just pure stupidity (just like me).

• When things look too good to be true, chances are you’re right. Trust your guts.

• When shit happens, instead of complaining, switch your perspective and make the best out of the situation.

• Most importantly, learn from your mistakes.

📚️ 1 Book

System Design Interview – An insider's guide

I never understood the importance of system design, until I started building Staq from scratch from tech architecture, data pipeline, API security and scalability, to how backend could talk to frontend seamlessly with low latency.

That’s when I realised it’s very important to have a good knowledge of system design as a data scientist to have a big picture of how data flows from point A to point B, potential limitations, and how we can overcome it.

That’s why I started reading this book (System Design Interview) written by Alex Xu. Although this book is for system design interview, the best practices and real-world examples shared by Alex are mostly applicable to many applications that you may be building.

📚️ Here are my takeaways from the book:

• How to build scalable applications with low latency

• How to design a web crawler

• Best practices and recommended approaches to connect different systems together to build a data pipeline.

Have you read this book? What's your thought on it?

🧰 1 Tool

The wait is over 🔥

OpenAI has finally made its ChatGPT app available to iOS users in India and over 30 other countries, just a week after its launch in the U.S.

The app has already garnered over 500k downloads in just 6 days, outperforming other AI and chatbot apps as well as Microsoft Edge and Bing apps.

The ChatGPT app allows users to interact with a generative AI-based chatbot, supports voice input, and offers advanced features through a subscription service called ChatGPT Plus.

If you’re an Android user like me, fret not. OpenAI plans to release an Android version of the app in the future. So stay tuned!

How I wish I’m using an iPhone now…📱

🔥 Hustler Spotlight 🔥

👋🏻 How would you introduce yourself?

‍I am a developer turn data guy. I have been in the data industry for 24 years. I was the Microsoft Excel World Champion, and also the founder of the world’s first Covid-19 database, CoronaTracker.

👀 What’s your day to day like in your current role as a CEO at LEAD?

My main job is to go to different channels and listen to what are the problems our students are facing. Then we try to look for qualified instructors to prepare the programs that help to solve their problems.

And I also go around and give talks at universities and conferences, to spread the awareness of data science and artificial intelligence. I want to close the gap between the industry and academia.

⭐️ What has been the biggest highlight of your career so far?

‍I have been fortunate to have several highlights throughout my career. But I would say the most notable one was when I built coronatracker. During the worst time of Covid19, we had 20 million unique users on our site, and cumulative 100 million visits. It has been a great honor to have been able to contribute to the fight against the pandemic by providing accurate and up-to-date information to millions of people worldwide.

🚀 What's a data or AI trend you're watching this year?

‍My background has always been in machine learning and NLP. There are 1,000 new AI applications released every month. It is exciting to see the space grow. There isn’t an industry I am watching in particular, but I expect to see more and more use cases for AI in industries such as customer service, healthcare, and education.

I want to see how far we can push the limit of text-based A.I., and what’s beyond that.

💼 What advice would you give someone starting out in Data Science?

• Learn data storytelling: Learn how to use data to uncover insights and patterns, and weave those insights into a larger part of a narrative that helps people to understand data and motivates them to take action.

• Build a personal brand: Having a strong personal brand, with a portfolio that shows your track record can help you stand out from the competition. It will also open up opportunities that you can’t expect.

• Be good at more than one thing: Be really good at one or two high-demand skills, and learn how to combine those skills. Be someone that can complement other people’s weaknesses and amplify their strengths. Data science is a team game.

🤯 What’s the most important career lesson you wish you’d learned earlier?

Quantitative change leads to qualitative change. I trust my instinct when it comes to choosing projects, even though I am a scientist and I should evaluate things quantitatively.

Later in my career then only I realize, my instinct was built because I have worked on so many different projects from sensors, mobile apps, healthcare, to even healthcare.

🧠 How would you learn Data Science if you had to start over?

Probably not much different from how I started. Start with a simple database tool with GUI (e.g. MS Access) and pick up a simple programming language (Python).

🔥 Where can we find your amazing work?

I publish most of my work in my newsletter https://drlau.beehiiv.com/.

📚 What's your favorite book?

“Sun Tzu: The Art of War”.

This book introduces many ideas that are counterintuitive and challenge our usual ways of thinking. One of the most important ideas in the book is “winning the war without actually fighting”. This idea is like “selling without selling” or “convincing people without being pushy”, which has helped me a lot in my career.

These ideas are also relevant to data science, which emphasizes strategic thinking and planning. Being able to adjust tactics based on situations is essential in data science, and the book's concepts can help prevent mistakes in the journey of aspiring data scientists.

🚀 Whenever you’re ready, there are 4 ways I can help you:

1. Book a coaching call with me if you need help in the following:

2. Promote your brand to 1,000+ subscribers in the data/tech space by sponsoring this newsletter.

3. Watch my YouTube videos where I talk about data science tips, programming, and my tech life (P.S. Don’t forget to like and subscribe 💜).

4. Follow me on LinkedIn and Twitter for more data science career insights, my mistakes and lessons learned from building a startup.

That's all for today

Thanks for reading. I hope you enjoyed today's issue. More than that, I hope it has helped you in some ways and brought you some peace of mind.

You can always write to me by simply replying to this newsletter and we can chat.

See you again next week.

- Admond