In 2019, I listened to multiple audio-books, however there were 3 books that I found to be the most valuable. They are: Algorithms to Live By: The Computer Science of Human Decisions by Brian Christian and Tom Griffiths, Sapiens: A Brief History of Humankind by Yuval Noah Harari, and Thinking, Fast and Slow by Daniel Kahneman. In this blog post, I will talk about each of these books and what I learned from them.
While listening to Algorithms to Live By, I was reminded of my software and probability classes that I had to take during college. This book covered all kinds of algorithms and how certain algorithms provided the most efficient results for different problems. Here are the different topics covered in the book:
- The secretary problem and the explore exploit issue. This algorithm could you used to mathematically find the ideal spouse for you.
- Slot machine problem – win-stay, lose-shift algorithm.
- Gittin’s approach to multi-arm bandit problem – discounting to present value. Example of doctors assigning clinical trial for better future, or prescribing existing drug. According to Gittin’s index, always play the arm with the highest index. In other words, it is better to explore since it creates novel outcomes.
- Upper confidence bound algorithm – inject dose of exploration.
- A/B testing – example of Obama campaign using different websites and collecting varying amounts of campaign funds.
- When faced with 2 airlines – one is new and the other one is established airline, only fly the new airline, until proven otherwise.
- Real life application of big O notation, bubble sort, insertion sort, merge sort (example: pizza party, each person sorts book, then combines books with other person), bucket sort, comparison counting sort, etc.
- Cache memory – frequently accessed things; FIFO (First In First Out); LRU (Least Recently Used); examples are Amazon with its shipping and Netflix (geography). LRU is better than FIFO; exploit geography; filing and piling (most recent files accessed are put on the left side in the box); Noguchi filing system (pile of unorganized mess is actually more efficient that sorting everything); brain (mind and memory) with more information takes longer to process, so as you age and your memory grows, you have more to process and your output slows. In other words, simply knowing more makes things harder – we aren’t forgetting, we are becoming archives.
- Moore’s algorithm – How to manage a fridge with different food items about to go bad? Throw away largest food item. Sum of completion time – shortest processing time; prioritizing tasks, priority inversion; presidents constraints – scheduling problem – intractable; Optimal solution – earliest due date and shortest processing time.
- Context switching when overloaded, and saying no to more work; staying on single task as long as possible without decreasing responsiveness to minimum acceptable limit – decide how responsive you need to be and be no more responsive than that; interrupt coalescing – checking email at set time once, pay every bill only once at set time – check things at a set time rather than context switching.
- Applications of Bayes rule; Laplace; Copernican principle; priors; power law distribution.
- Marshmallow test with children; need to protect your prior for accurate results; over-fitting (causes noise) 2 factor and 9 factor models; avoid over-fitting as it makes things complicated/complex.
- If you have high uncertainty and limited data, then stop early. Don’t make things complicated; the more uncertain you are, the early you should stop; think with broad strokes.
- Lagrangian relaxation… do it or else what?; constraint relaxation and continuous relaxation.
- Randomness; Monte Carlo; find and check primes – Miller redeem test; bloom filter, and networking.
- Application of recursion in poker; game theory; prisoners dilemma; vickrey auction.
As you can see the book covers a wide range of problems and algorithms. The book draws parallel with how you can use computer algorithms to bring efficiency in your life. This book had lots of examples, and it kept me engaged till the end. I would recommend this book to anyone interested in computer science, and anyone who wants to know how to use algorithms to efficiently address everyday life problems.
If you are a history buff, you are going to love this book. Harari takes you on a journey from the beginning of times all the way to robotics and artificial intelligence. The book talks about how human beings and their cultures evolved over the years, and how different inventions and breakthroughs pushed the sapiens to the top of the ladder. Here are some of the many topics discussed in the book:
- 3 different revolutions at different times in history: Cognitive Revolution, Agricultural Revolution, and Scientific Revolution.
- How and where different species of humans migrated and survived. Why certain species survived and some died off?
- Gossips and rumors is what bonded human beings. The ability of humans to communicate using descriptive language is what differentiated human beings from the rest of the animal kingdom.
- The “fictive” language allowed human beings to imagine and collectively believe/trust in an idea, which could be religion, legend/myth, currency, corporation, etc. It is this collective belief that citizens of a country, or devotees of a religion, or individuals pursuing a certain goal hold, which bonds them together. This collective belief is the glue that allows thousands and millions of human beings to live peacefully without causing any conflict.
- Did different human species intermix? Is there a superior race – “Aryan” race? Was there a mass genocide?
- How did homo-sapiens emerge as the dominant species? How did human beings eradicate most of the large mammals on the planet?
- Harari claimed that industrial farming is one of the worst crimes in the human history.
- Where is the future of the human beings headed with facebook and google and artificial intelligence in our everyday lives?
Overall, I thought this book was very informative and had some great information. After reading this book, you get a better idea of how we got to where we are today. It took us hundreds and thousands of years to become a dominant species. I would recommend this book to anyone who wants to know how human beings took over the world.
Have you ever said something or took a decision in the heat of the moment and later wondered why you said or did that? Kahneman talks about why this happens, and different biases that influence our decision making processes. I really liked this book because it went over various circumstances that affects our decisions. Here are some of the many topics Kahneman discussed in the book:
- System 1, which is our fast and automatic brain that makes split second decisions. System 2, which is our slow and logical brain that makes rational decisions. System 2 is your “lazy” brain, which is always slow to react. So, for example, if you see a grizzly bear on your hike, your System 1 kicks in and you decide to turn around and run. On the other hand, if you were about to invest $10,000, your System 2 is going to analyze the rational behind picking a specific stock.
- We run into biases and fallacies when we start using System 1 in place of using System 2 for our decision making processes.
- Kahneman talks about how human beings are motivated by fear. He talks about loss aversion, which refers to people’s tendency to prefer avoiding loss than acquiring equivalent gain.
- Kahneman talks about how the human mind can be primed by what he calls “framing”. He gives examples of court cases, medical studies, and lawsuits where framing plays a key role. For example, lawyers using numbers (fractions) instead of percentage to make the case more personal. Similarly, medical studies using percentage instead of numbers (fraction) to talk about probability makes things less personal.
- Anchoring – from shopping for your Banana Republic jeans to buying your house, anchoring plays a key role in your decision making process. If you are shown a extremely high “original price”, and then shown another price that’s lower than that “original price”, your brain has been primed into believing that you are getting a good deal. Similarly, if you are the buying a house or a car and are in the process of negotiating, you can throw in a low anchor price and then gradually move up.
- Sunk cost fallacy – this is the time when you have already invested a lot of money or time behind an investment or project, and its “too late” to back out. So, you decide to ride the sinking ship. Your rational “system 2” would tell you to cut your losses, but your “system 1” can’t stand to see all your time go to waste. For example, when you are researching a stock, you read all the annual reports and proxy statements, and it takes your one week to finish your research just to come to a conclusion that there is nothing great about the company. Now, rather than giving up on the company and moving on, your brain is going to try to convince you that the company is not too bad after all.
- Availability bias – this is when you start giving more weight to the information that is easily available, rather than holistically looking at all the information and then making a decision.
- Kahneman also talks about experienced utility, duration neglect, and memory-experience conflict (cold hand experiment).
Overall, I thought Thinking, Fast and Slow was a detailed, well written book. Although it was a long book, I really enjoyed listening to it. I would recommend this book to anyone who is interested in knowing more about different biases and fallacies that secretly influences one’s decisions.
Hope you learned a little and found this blog post helpful. We talked about Algorithms to Live By: The Computer Science of Human Decisions by Brian Christian and Tom Griffiths, Sapiens: A Brief History of Humankind by Yuval Noah Harari, and Thinking, Fast and Slow by Daniel Kahneman. As always, you can sign up for our free mailing list here. You can sign up for our paid subscription services here. Like us on our Facebook page here. Thank you and Happy New Year!
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