Hi guys, I used Machine Learning to build.... the Booki Monster!

One of the biggest problems I've noticed since entering the "real world", is that it's hard to find time for things. Going on adventures, finding a girlfriend, building new social groups, having interesting hobbies...... and reading books. Or maybe, you're just too hungover....... 

But a book that might take 5-10 hours to read? Well, what if I told you that you could get the key points from the book without actually reading the book? I want to introduce you to the "Booki Monster." A machine-learning powered monster that reads your books and summarizes them for you. 

You can play with the application here. If it's slow, give it a sec. 

My goal here is for a non-technical person to understand technically how I built my project.

1. Who is the Booki Monster?

You see those pile of books on your drawer that you're "too busy" to crack open? Well, that's the Booki Monster's food. Feed the Booki Monster your books and then she'll spit out the golden nuggets in the form of summaries.

2.Feeding the Monster

You know that feeling when you're with your friends, you want to eat out, but can't decide where to eat because there are wayyyy too many options? Feeding the Booki Monster was the same, I had too many options: science fiction, business, self-help, psychology, scientific research etc. 

And for those who understand product marketing, when you're product is for everyone, it's for no one.  I'd prefer to make the Booki Monster generate high-quality summaries for a more niche, targeted set of books, than mediocre summaries for many books. 

So I settled on feeding the Booki Monster only business books for this reason. Plus, Blinkist.com, a company that produces human-written summaries, happily agreed to send over their human-written summaries, so I can measure the Booki Monster summaries quality. 

With this understanding, grab your nearest surgeon, and let's start dissecting the body of the Booki Monster. Mmmmm.... tasty........

3.The Booki Monster's Body (Technical)

Method

When creating the Booki Monster, I had a couple different options:

  1. Sentence Extraction: It's similar to DJ'ing vs. Music Production. Am I using the songs already created? Or am I creating new sounds? Sentence Extraction is like DJ'ing, taking the text already written and using them as the summary.
  2. Abstractive Methods: Abstractive Methods are kinda like creating the sounds yourself. In the context of summarizing, it means that the machine needs to understand the text on a much, much deeper level.
  3. Graph-Based: Graph-Based is more like DJ'ing than Music Production. Imagine all your Facebook friends as a fuzzy ball, where each person may have a relationship with another, with varying degrees of strength. The same model would be used for sentences, each sentence would have a relationship with each other, with varying degrees of strength.

And because I only had two weeks to do it, DJ'ing would probably be more feasible for a one-man team.

Strategy

If you've read the Lean Startup, you'll notice that Eric Ries advocates the "Minimum Viable Product" approach. In this context, my goal was to build a working model as fast as I could and then continuously iterate upon that. So the way I modeled this was:

  1. Model one chapter
  2. Model one book
  3. Model five books
  4. Model 10 books

And on... and on.... you get the idea.

Rapid Automatic What.........?

As I'm typing these words on the keyboard, I'm wondering how I can explain this without boring Machine-Learning enthusiasts while making it understandable for normal people.

Sorry ML people, general audience wins here.

Imagine yourself as a puzzle-maker. You're boss gives you a beautiful sunset photo and wants you to hand-cut the pieces out. Each time you cut out the pieces, you have a little snippet of that photo. In Natural Language Processing, taking a picture and cutting it into pieces is called tokenizing. In order to analyze text, we need to cut it up into different pieces( usually each piece = word) but it depends on the project you're working on.

In the context of this project, I wanted to tokenize on key words. Sometimes, an author might use a phrase like "Moby Dick." "Moby Dick" should be treated as one phrase, not two. This is called Rapid Automatic Keyword Extraction.

After passing my books & summaries through a Rapid Automatic Keyword Extraction, it's time to engineer features:

Feature Engineering

To understand what's going on here, let me introduce you to this scenario:

Let's say, you're waiting for your Uber to come and have a couple minutes of time to kill. So you flip out your phone and open up your Facebook. You start scrolling through your newsfeed and see that Sally posted an article that says "Trump Suggests Bigger Role for U.S. in Syria’s Conflict." You live in San Francisco, so you have a passionate hate for Trump, so you click on the link. The article is kinda long and since you're limited on time, you scan the article, trying to decide if the entire thing is worth reading. You see that the article talks about "North Korea" and start thinking " Ohh.... this is interesting, I'll save this for later." When you saw the title of the news article, what keyword triggered you to click?  Trump. If you're interested in foreign policy, it might've been Syria . It changes for each person, but the idea is that there were specific key words in the text that gave you a good picture of what the article is about. And when you scan the article, you see North Korea, so Trump, Syria, North Korea , already give you an idea that this article is about some problems/tensions. 

This idea of a key word giving you some information about text is called a feature. Features are kinda like hints. It's saying "HEY MODEL! PAY ATTENTION TO THIS A LITTLE BIT MORE!"

In addition to key words, here are all the things I thought the model should notice:

  1. Term-Frequency: If a keyword appeared more often, the better the sentence.

  2. Sentence Location: Sentences in the beginning are likely to be more important, since the author is often introducing the general concept of the entire book. Middle sections are usually diving into details, examples of an idea, which may not be the best sentences for summarizing.

  3. Presence of a Verb: I used a position tagger to score the number of verbs a sentence contained. I guessed that sentences which contained verbs, likely had a subject-object action in the sentence, which usually provided more information and to get rid of flowery, descriptive sentences( which aren't good for summaries).

  4. Sentence Length: I down weighted short sentences, since a short, 4 word sentence, that might contain a key word, isn't that important.

And because I'm DJ'ing(extracting), the goal is for each sentence to get it's own "score." It's like how Steph Curry averages 25.3 points, 6.6 assists, 4.5 rebounds per game. Each one of these stats is a "feature" for Steph. And ESPN uses these numbers(plus many more) to create a PER score, for Steph it's 24.74. I'm trying to create the PER of sentences.

And as you might be able to guess, there are an INFINITE amount of additional things I can track, here are a couple:

Sentence Structure: How many subjects, objects occur in the sentence? What combination of subject-object, verb, adverbs are most conducive to high-quality summary sentences?

Named Entity Tagging: If I'm reading an article about "San Francisco" and I see the word "San Francisco","Oakland","San Jose", should I give more weight to these special "entitites"?

Sentence position within paragraph: Topic sentences should be upweighted while the middle sentences should be down-weighted.

PageRank: Similar to how Google's Search algorithm worked, I could add a PageRank method to additionally weight scores.

Word Length: Do # of characters in a word play a part in high-quality summaries?

Punctuation: How effective are rhetorical questions, questions, normal statements, exclamations in providing high-quality information to summaries?

And if the list keeps going, I'm either boring you, or I'm just trying to show you how smart I am(which if you're an ML engineer, you probably don't even think my modeling was smart. Well you're wrong.).

Anyways, let's get to the sexy stuff in Data Science. We've got our data, we've got our "features", what do we do next.... drumroll please............

Modeling

You remember you're first few years in college, you're excited to become independent from your parents, so you get to your dorm room, your floormates become your bestest buddies, while you go on to inebriate yourself while riding the wave of independent life? And five years later, the wave crashes and you think back: " Man, I was an idiot. I would've totally made better use of my school resources, spent more time learning skills and put myself out there a bit more."

I actually don't believe in replays because you wouldn't have known to do this, if you hadn't done that, circular logic. And the same goes for modeling book summaries. First time around, I'm super excited to add to the hype fueling the buzzword "Machine Learning." But as a young Data Scientist, I am young Luke Skywalker and have many, many things to learn.

I'm going to show you what I did, and what I would do differently next time.

But to dive in, I used two different models:

  1. Latent Dirichlet Allocation

  2. Doc2Vec

And you'll probably have no idea what those mean. Let's start with what Latent Dirichlect Allocation is and why I used it:

Let's say we took the world's 8 billion people and threw em all in a pot. Mixed them up all together. All the Asians standing next to each other, the Indians mixed with Arabs, English & Americans mixed, confusing as shit right. And let's say you were some almighty god, and Zeus commanded you to re-organize this pot into all their original countries without going one by one. How the eff would you do that?

Well, you would use a Topic Model. If you imagine each word in a text as a person, a word likely corresponds to a specific topic. For example, in an article about food, the words "dumpling","fried rice","herbal tea","small eyes" would fall under one topic and "fat","burgers","french fries","obesity" might fall under another. Can you guess what topics they are? Yes, Chinese and American.

I chose Latent Dirichlet Allocation, because it does this categorizing for me.

And since this was my first Data Science project, I wanted to make sure I had a model up and running first and ran out of time in trying other topic models. Other ones I considered:

  • Non-Negative Matrix Factorization

  • Principal Component Analysis

  • Singular Value Decomposition

And I'm not going to exhaust you by explaining what each of those are. But I chose LDA, because each word isn't bound to a specific topic, but each word gets a distribution over all the topics( Sorry, for the non-tech folks, I don't have a good explanation for that, yet).

This model would give me the best key words I could use for my scoring(explained earlier).

Here's what it looks like visually:

Here's a wordcloud of the chosen topic model for Chaos Monkey by Antonio Garcia Martinez:

 

And a wordcloud of the entire book:

 

And you might be wondering, how the heck does the model know how many categories to give the text? How does it know how many key words it chooses? It doesn't. I have to decide that and this depends on my knowledge of the text I'm modeling. I optimized my model for 10 topics & 50 key words. And I chose the topic based on my knowledge of the book( if I read it) or I chose them at random.

(Eff... getting tired writing..... time for a coffee break!)

The second model I tried is a Doc2Vec, which, yes, don't get too excited, is a "neural network." GASP GASP GASP

I'm being silly. You know, I need to have fun writing this.

Ok. Imagine you're standing on the surface of earth, you've been single for way too long, and want to find your significant other by pulling a Goku and shining a Kame-Kame-Ha lightbeam towards the sky. You'll determine that your new girlfriend/boyfriend will shine their own light to the sky. The one that's most similar to your light, is the winner.

Sorry, that's the best explanation I can do right now and the metaphor does not fully represent Doc2Vec correctly. However, the idea is that every sentence is like a beam of light shining to the sky(vector) and we want to see how similar these vectors are to the vector of the entire book. This gives us the score.

And this is how I modeled. In the future, I would:

  1. Try a basic Logistic Regression: Can I classify a specific sentence as representative of a reference summary sentence?

  2. Try all the topic-modeling models listed: A wider variety of models and give me different insights on the text.

  3. Acquire more data to turn it into a Convolutional Neural Network.

  4. Try a sole PageRank/Graph-Based Model.

  5. Use all the models as weights for a "final score" for each sentence based on different techniques.

Scoring

Who is a better athlete, Kobe Bryant or Tom Brady? Who is the better writer, Tolstoy or Hemmingway? Who is the better visionary, Steve Jobs or Bill Gates? What's better, Apple or Android? Better ad platform, Facebook or Google?

When you ask different people, you get different answers. And summaries are the same way. Is there a quantitatively sound way of saying "Yes. This summary is dope."

No, there isn't. But we can try. After doing some research, I found that researchers use something called ROUGE-N Score to measure quality of summaries.

But what the heck does this score actually measure? It looks at the pairs of words in my booki-monster summary and then checks how many times these words occur in the human-written summary. And then takes a ratio.

Here are the scores:

Doc2Vec Split in 10: 0.241( + 0.126 over random)

LDA Split in 10: 0.176 ( + 0.062 over random)

Random Split in 10: 0.114 (-----------------)

Note: Random means, I built a model that randomly takes sentences from the book and titles it "the summary." Because what the heck is the point, if a monkey can write summaries just as good as the Booki Monster's.... and..... these numbers don't mean anything unless we have a baseline.

As you can see, the Kame-Kame-Ha Method(Doc2Vec) did 12.6% better than random and LDA did 6% better than random.

Conclusions

As a "Scientist", I've gotta extract some insights from all this "stuff." Let's bring the cake out the oven! <----- bad metaphor, but whatever.

  1. Better to be used for previews than summaries: Because I was DJ'ing/extracting, I knew that writing style of an author is going to be different from a summary. Author's tend to write their books, knowing they have many, many pages to articulate an iea. As a result, sentences will contain more detail, and author's are willing to dive into technicalities a bit more because they have enough space to explain a term they can use for the rest of the book. Compared with the human-written summaries, human writers are going to condense the writing into fewer words, while diluting the arguments behind the concepts.

  2. Booki Monster loves long, meaty sentences( I thought about making a sexual joke here, but nah. This is professional): If you look at the average sentence length:

 

In addition, I created a quick regression of word/sentence against ROUGE-N score to look at the relationship.

 

Notice that the average words/sentence for the Doc2Vec summaries are about 20 words/sentence longer than the words/sentence in the reference summaries, which supports my first point as well. This finding leads me to claim, that the model bias' a bit towards longer sentences, which makes sense due to the scoring method. A longer sentence has a higher likelihood of containing pairs of words that match pairs in the reference summaries, which boosts the ROUGE-N score. This method does eliminate low-information short sentences.

In the future, how will I not over-weight long sentences but still keep short sentences?

  1. Human summarizers emphasize different key points: Summaries and most writing, is subjective. A human summarizer already decides upon what key points they think the reader finds interesting. However, every reader is asking different questions when they're reading a book. An older man, may be wondering how he can find peace for the rest of his life, while a teenage girl may be trying to figure out what she should do with her life. Different questions, different answers, different summaries.

A future solution can be a query-based summarization method, where the user inputs a specific question they're asking, and then the model writes the summary based on the question the user asks.

Future

In the future, there are many things I may be able to try:

  1. Learn summarization framework: Similar to the grade-school five paragraph format, I can teach the Booki Monster a summarization-writing framework. This can improve the coherence and flow of ideas within the summary.

  2. Human Feedback: Scoring is hard. Like I said before, summaries are subjective. In the future, having the model create summaries and get user feedback can add a human element to summary creation.

  3. Query-Based Summary: Have users input questions and model creates summary based on those questions.

All in all, I hope you enjoyed reading this as much as I had writing/building this project. My journey into the world of Data Science is only beginning and I'll be creating many more monsters to come!

Example

Collapse by Jared Diamond

As for the complications, of course it’s not true that all societies are doomed to collapse because of environmental damage in the past, some societies did while others didn’t; the real question is why only some societies proved fragile, and what distinguished those that collapsed from those that didn’t. Some societies that I shall discuss, such as the Icelanders and Tikopians, succeeded in solving extremely difficult environmental problems, have thereby been able to persist for a long time, and are still going strong today.

Some of my Montana friends now say in retrospect, when we compare the multi-billion dollar mine cleanup costs borne by us taxpayers with Montana’s own meager past earnings from its mines, most of whose profits went to shareholders in the eastern U.S. or in Europe, we realize that Montana would have been better off in the long run if it had never mined copper at all but had just imported it from Chile, leaving the resulting problems to the Chileans! After living for so many years elsewhere, I found that it took me several visits to Montana to get used to the panorama of the sky above, the mountain ring around, and the valley floor below to appreciate that I really could enjoy that panorama as a daily setting for part of my life and to discover that I could open myself up to it, pull myself away from it, and still know that I could return to it.

One person said that Balaguer might have been influenced by exposure to environmentalists during early years in his life that he spent in Europe; one noted that Balaguer was consistently anti Haitian, and that he may have sought to improve the Dominican Republic’s landscape in order to contrast it with Haiti’s devastation; another thought that he had been influenced by his sisters, to whom he was close, and who were said to have been horrified by the deforestation and river siltation that they saw resulting from the Trujillo years; and still another person commented that Balaguer was already 60 years old when he ascended to the post-Trujillo presidency and 90 years old when he stepped down from it, so that he might have been motivated by the changes that he saw around him in his country during his long life.

Sources

Automatic Extraction Based Summarizer - R.M Aliguliyev

Latent Dirichlet Allocation Based Multi-Document Summarization - Rachit Arora, Balaraman Ravindran

Looking for a Few Good Metrics: ROUGE and its Evaluation - Chin-Yew Lin

Sentence Extraction Based Single Document Summarization - Jagadeesh J, Prasad Pingali, Vasudeva Varma

Distributed Representations of Sentences and Documents - Quoc Le, Tomas Mikolov

Latent Dirichlet Allocation - David Blei, Andrew Ng, Michael Jordan

LDA2Vec - Chris Moody

Jeff Rapping Fast: Busta Rhymes verse in "Look At Me Now"

Haven't gotten a chance to update much for the past few months, as Algorithms, Machine Learning, Data Science has sapped away the energy that I'd usually use to write/update( but expect some future data-related posts coming up :) ). 

Nevertheless, no need to break out the tissues, I'M BACK.....kinda...... well, as a break from all this left brain thinking, it was time to do something music-y so I decided to learn Busta Rhymes' verse in " Look At Me Now by Chris Brown." For those who are unfamiliar with rap, it's one of those rap songs where you're thinking two things:

"How the eff does someone talk so fast??"

"I have no clue what this dude is saying...."

And because I've been humbled by the mental calisthenics required to understand Machine Learning, I think it's time to give me ego a tiny stroke. The rap wasn't perfect, but considering I only practiced it for 30 minutes-ish I thought it was pretty good :)

Note: Yes, I am trying to cover up my imperfections by note-ing the amount of time I spent. Don't lie. You do this too. 

For those who are unfamiliar with the song, here's the original: 

What I Learned Living like a Monk for 10 Days

bull-of-the-woods-wilderness-oregon--big.jpg

You know when you’re sick and you’re thinking “ damnit, I feel like I’m going to DIE. Time to live a healthier when I’m recovered.” But when you recover, you return to your old unhealthy habits? Or when it’s the “end” of something, whether it’s college graduation, the last time you’ll see a friend for awhile, you feel like you need to make the most of the limited time left with that person/place?

For some reason, these moments of clarity decide to sprout up at specific moments and then I start thinking “ why can’t I feel like this ALL the time?” It’s weird, because when the finish line is foggy, I take life for granted. And then, when the end nears, I start to wish that I made the most of that time.

It’s kinda crazy to think about because we all have our finish line: dying. I feel like I understand the concept of dying, but it’s impossible to truly know it if I haven’t experienced it.   

It’s interesting because people that teeter on the brink of death, often gain an enlightened clarity of their life. The most important things in life crystallize. They starting wishing they’d spent more time re-connecting with their friends, worked less, had the courage to live their life aligned with their values.

So I guess the solution should be to just shoot myself in the leg, that way I won’t die. But I’ll get the benefits of almost dying! End of article.

Ow fuck! Wanna touch my blood guts? Wanna see my bones? Mmm, scrumptious.

Sorry, I’m being weird.

Anyways, I guess the real question is: how do I gain that deathbed clarity, before I actually die? How can I see the truth of my life, so I can live the rest of my life as happy and fulfilled as I can be? To quote essayist Michel De Montaigne says:

“ If I were a writer of books, I would compile a register, with a comment, of the various deaths of men: he who should teach men to die would at the same time teach them to live.“

So I decided to venture into the Oregon wilderness, to live like a monk for 10 days. I wanted answers.

10 hours of meditation per day. 100 total hours. All vegetarian food. No dinner. No phone. No reading. No writing. I came in looking for death, but left with more life.

So strap on your seatbelts, grab your popcorn. We’re gonna go on an amazing space adventure through the universe inside your brain.

Planet 1: Consciousness

So for the first stop in our journey, we’re gonna be stopping by planet I call “consciousness.” Planet consciousness is gonna act as a backdrop for everything we’re about to discuss and see.

Planet consciousness is a weird planet. It’s a gas planet that doesn’t have a single, set size. It could be the size of Jupiter or it could be the size of a peanut. It’s size changes depending on the who’s looking at it, like a planet-sized Rorschach test.

As I write this post, I’m sitting at a Starbucks. I can see an ant crawling up the leg of my table. I would’ve accidentally killed this ant if I didn’t notice it crawling up towards my hands. This ant, has no clue that I can squash his guts, ending his epic journey to the sugar packet across the table. This ant, could probably find sugar somewhere else, away from this giant human being, but he can’t comprehend that this bigger guy can destroy his guts. If I tried to tell him to run out of danger, my voice would whiz through his head. He just wants sugar.

This ant, would see planet consciousness as a small peanut speck. The idea of a human being is wayyyyy over his head.

But let’s take a trained pet dog. If I told a dog to sit, he’ll sit with the understanding that I might reward him with food. He’s capable of growing some attachments towards me as an owner, so when we get separated, he’ll start crying. If I try to crush him like an ant, he/she will run away. But if I tried to explain chemically, how chocolate can poison him, he’s not gonna have any clue what I’m talking about. For a dog, planet consciousness is a bit bigger. Maybe the size of a car. Much bigger than the ant, but much smaller than a human.   

And now, let’s look at the consciousness of a human being. We’ve got the amazing capability to create a bomb that can destroy earth. We invent devices that allow us to communicate with people on the other side of the world. We can built space satellites that travel to Saturn. Pretty amazing stuff. So let’s say the size of planet consciousness for us, is the size of California. Pretty huge.

As humans, we’ve got a natural tendency to think we know everything. We thought the earth was flat and the universe revolved around earth. In 1900, famous mathematician & physicist, Lord Kelvin stated:

“There is nothing new to be discovered in physics now. All that remains is more and more precise measurement."

He was obviously wrong, as Einstein discovered the Theory of Relativity & Max Planck developing his theory of Quantum Mechanics. There are a ton of other examples of certain ideas proven false. My point is that at every point in history, it’s easy to think we already know everything, when in fact, most of what we know now is probably wrong.

So if humans see planet consciousness as the size of California, what “thing” would see planet consciousness as the size of the earth? I don’t know. We’re like the ant. It’s outside our comprehension.

Keep in mind, the sizes of planet consciousness aren’t 100% proportionally accurate. I just want to show you that there is a large difference amongst different creatures.

To generalize this idea, every creature and thing has some size of planet consciousness. Some less so and some more evolved.

As for humans, we’re all kinda in the same range of consciousness. The stupidest human is probably smarter than the smartest ape. And the smartest ape is probably smarter than the dumbest fruit fly.

As for humans, let’s fly into the human range to get a snapshot. To get a clear picture, let’s go visit the people on the three moons surrounding planet consciousness.

Moon 1: Reactiveness, Fear-Driven, Insecure

Moon 1 is a bit of a wasteland. If you’ve seen Wall-E, it’s kinda like the wasteland earth turns into, except there are human beings living in it. Most people on Moon 1 are trapped in their own little world, not giving much thought to the good of others. Their world is pretty shitty, and they attribute this shitty world to bad luck. They feel like their a victim of their circumstances and hold a lot of anger towards the people of the other moons, because their’s is the shittiest. Most of the people on this planet are reactive to all the unfortunate things happening on their planet: constant space rain thunderstorms, dangerous comets hitting their planet.

Rather than take responsibility for their lives, the people on Moon 1 delegate their responsibility elsewhere. They hold quite a bit of negativity. They constantly gossip and overindulge themselves in sensual pleasures. They only think about their own needs, which can only explain why their world is such a shitshow, since nobody makes an effort to help their civilization.

For those on Moon 1, they see planet consciousness comparatively smaller than those on Moon 2 and Moon 3. Definitely much larger than a dog, but much less than the members on the other moons.

Moon 2

The people on Moon 2, used to actually be Moon 1 people. A group of them, finally realized that the reason why Moon 1was so shitty, was their fault. So in an effort to take responsibility for their own lives, they decided to migrate over to Moon 2, where they could start fresh, develop a new mindset, so they could live happier, peaceful lives. There’s still some Moon 1 behavior ingrained in them, but Moon 2 people are actively looking to make changes to their lives. Moon 2 people are beginning to engage with life much more, meet new people and actively try to break out of their own little bubble. Think of Moon 2 like a modern day NYC or Los Angeles. Still kinda grungy, but constantly looking for ways to improve.

Someone living on Moon 2, is likely living with a “planet consciousness” that’s a much larger than Moon 1.

Moon 3: Love, Compassion

Moon 3 people are the most evolved out of the three moons. Moon 3 people don’t actually put themselves on a pedestal over Moon 1 people. Moon 3 people see Moon 1 people as equals, just with a lot of pain and internal problems they have yet to solve. Moon 3 people build things for the good of all their people. They push the boundaries of what can and cannot be done, constantly push their evolutionary progress. They do things without expecting anything in return. Think of Moon 3 people like the Gandhi’s, Malcolm X’s, MLK’s, Elon Musk’s, but most importantly, these people are happy, living a life according to their own values. Those who go out and do things for the benefit of others, not just themselves.

And the reality is, everybody actually experiences what it’s like to be on Moon 3 when they’re about to die. They see the truth of their lives. And I suspect, that those amazing, high-level thinkers, or people just living a life according to their values, saw the truth of their lives before actually experiencing death. The size of planet consciousness to them is much, much larger than Moon 1 and Moon 2.

Looking at the three moons, it’s not as categorized as I make it sound. We all oscillate between the three moons. For me, spending time with the toxic, negative people, eating junk food, lack of energy brings me down to that irritable, reactive Moon 1 behavior. Sometimes, when I’m in the wilderness and stare up at the stars, meditating on the vast depth of the universe, it brings me up to Moon 3. It’s never constant. We’re always going through the ups and downs of life.

But what gets in the way of operating on Moon 3, the highest version of ourselves? I introduce the evil alien spaceships, space rain and dangerous comets.

Evil Alien Spaceships: Emotional Pains

A lot of what’s causing problems on Moon 1 is the evil alien spaceships. These evil alien spaceships invaded Moon 1 a looonnngggg time ago, like Cortes overpowering the Aztecs, and took control of the people on Moon 1. The problem is that a lot of the people on Moon 1 think they’re acting out of free-will, when it’s actually the evil alien spaceships controlling them.

For example, if 100 years ago, a father started abusing his child. The image of the father beating him gets stored into the child’s brain as “this is how fathers should treat children.” If the child doesn’t do the work to kill this evil alien spaceship, the avoidance of this pain is gonna guide the child’s behavior into adulthood.  

Or it may not be as extreme, maybe a kid was verbally bullied as a child and as a result, entered into adulthood with low self-esteem and confidence.

My point, is not to tell you about yourself. I’m not a psycho-therapist. But my point, is to show you that a lot of what happens to you during childhood has an affect on your behavior when you’re an adult. And for a lot of painful memories, we bury these pains inside of us and we avoid dealing with them through compulsive behavior, like alcohol, drugs, sex, workaholism, excessive shopping etc. All forms of us avoiding confronting the pain in our lives.

We all think we behave out of our own volition, but in reality, we’re all like machines, inputs go in, specific outputs come out. You’re not exempt. And this emotional pain is what gets in the way of the truth.

To return briefly to my meditation, these emotional painful memories would surface and as I sat there. I’d sit there and start crying. Sometimes, my mind lost the memory, but the pain was still there, so I’d start crying for no reason. But the interesting thing is that once I became aware of the pain, I just let it go. It’s like you’re holding a hot coal in your hand all your life. Once you’re aware that you’re hand is burning, you just drop it. I’d walk out of the meditation hall a bit lighter, staring off into the Oregon wilderness, as if it was the first time I’d ever seen something so beautiful.

Space Rain: The Thinking Mind

Space Rain is like normal rain. Just like how rain is good for watering plants, too much rain will cause floods, disasters and drowning. The thinking mind is the same way. We need to think to solve problems, but 90% of the thinking we do is useless.

Since Moon 1 people are constantly thinking about themselves, there’s always a ton of space rain, flooding their society and making everyone miserable.  They have no idea that their own thinking is causing all this unhappiness, so they just react to the unhappiness around them.

The problem with thinking too much, is that it detaches you from reality, the truth. You start filtering your reality through the concepts in your head, rather than seeing reality as it is. Let’s use an extreme example, let’s say you’re a racist white supremacist. Naturally, you’re going to think that black people are terrible people. One day, you’re walking on the street, and you see a black person hop into a nice, Mercedes-Benz. Since you’re concept of black people is negative, you’ll filter this image through your mind, inferring that the black person probably stole the car, which is likely not the correct assumption.

Notice that the thinking you do always takes place in the past or the future. Notice, that you can’t think about now, because by default, you wouldn’t be thinking. For example, let’s say you wanted to think about a picture of a TV. Well, to create that picture, you’re mind will use your previous memories of a TV to create that picture of a TV. By doing this, you’re thinking from the past to create this image. Or if you have a big presentation at work next week, and you’re mind keeps jumping out to presentation day, you’re thinking about the future.

It’s important to reflect on the past to learn and to set goals, but after a certain point, a thought can become compulsive, where more thinking creates more unhappiness. There are so many times in my life where I messed up on a project, screwed up with a girl, made a mistake, but my mind kept creating this mile-long chains of thoughts, keeping me up all night.

The Green Goo Virus: Cravings & Attachments

One of the things that the aliens brought with them to Moon 1, is the Green Goo virus. The Green Goo virus causes the people of Moon 1 to feel like they never have enough in their lives. They always need more money, more food, more sex etc. They’re overly attached to the emotional high they get from that activity: relationship, money, food, drugs, sex etc. 

But if you notice every “high” you get, there’s always a low that balances it out. The initial passionate, high you get from a relationship can result in you getting emotionally attached to that high. You don’t want to let it go, so your behavior becomes needy, jealous, possessive, which turns off the other person in the relationship(I can say from personal experience) which then leads to unhappiness. Or that emotional high you get from some experience or drug, causes you to get attached to that feeling, only to be sad when you can’t replicate it ever again. Or you can replicate it which starts an addiction.  

And even Moon 3 people can get infected by the Green Goo virus. Say, you wanted to build a business so you can help the world become better public speakers. But after awhile, you lose sight of your mission, and start trying to grow the business as huge as possible, while diluting the quality of your product.

As we travel across this universe, you’re probably wondering, what’s the solution? How does someone on Moon 1 evolve to Moon 3? What should I do? And to be honest, I don’t know, but here’s what I suspect.

The Sun: Awareness

For those who haven’t studied meditation, people think the goal of meditation is to “not think.” But in reality, what meditation really is, is to become aware of your thoughts and not making a “self” out of them.

Throughout your entire life, you build this identity of who you are. You internalize certain likes, dislikes, experiences and it creates this image you have of yourself. Imagine a blank painting palette, and with each life experience, belief, learning, you add a brush stroke to that image of yourself.

For Moon 1 people, they walk through the world seeing reality through the lens of their own painting. If they love a certain EDM song by Porter Robinson, “good music” to them is actually “how much does this song resemble Porter Robinson?” If you ask them if they like Bluegrass music, they probably wouldn’t like it because it’s too different. But if you asked a country boy in the Midwest, he’d probably love Bluegrass. If two different people have two different opinions of the same thing, who’s right?  Nobody. Their preference is just a reflection of themselves.

What’s interesting about meditation, is that when you detach from your thoughts, you no longer operate as the painting, you become a third party watching that painting. Because once you detach from your thoughts, that’s when you loosen up your identity. The thought isn’t reality, it’s merely an image popping up in your head.

To explain this further, let’s do a thought experiment. Imagine every thought as a LEGO piece. As you go through life, you gradually build this LEGO sculpture of yourself. But through life, many of the pieces you add to that sculpture may be toxic, negative thoughts, cravings, addictions, painful experiences etc. The benefit of meditation or any type of awareness training, is that it helps you become aware of what pieces are in that sculpture. And just like the sunlight evaporating water, shining sunlight on those pieces disintegrates those pieces.   

Where this metaphor fails, is that you always want to keep this sculpture flexible and dynamic. When it becomes too rigid, that is, you becoming too attached to your identity, that’s when you resist change. Or if you lose your identity, that’s when you become depressed. It’s like a guy who over-invests his identity into his relationship. He drops his hobbies, spends all his time with his significant other. The problem is, when you over-invest your identity in anything, when you lose it, you’ll feel like you’ve died inside. This can explain why lots of professional athletes fall into depression after they retire, since they’ve invested their entire lives into this one thing.

And I’m not saying you shouldn’t be invested in relationships, your business or anything. You should care. But it should be balanced with perspective and healthy detachment from the outcome. For example, Steph Curry, after blowing a 3-1 lead to the Cavs in the 2016 NBA Finals, had this to say:

"We had a great night as a family, everybody that came to the game with me, we went back to the house. It wasn't as lively as a celebration get-together would have been, but it was still a moment to appreciate all the good things that have happened along the way, on and off the court, and keeping that perspective. This game means a lot to us as players and to the fans and anybody that has a vested interested in the game, but at the end of the day, there's still life and you can still win at life knowing we didn't get a championship this year.

Going back to the sculpture metaphor, how do we identify the toxic pieces?

This is where we see the sun, because the sun is where light reveals the darkness. In the universe of our mind, the hidden, dark corners, end up being the blind spots in our lives. The things we’re most resistant to seeing are the things we need most. The pieces we’re most afraid to let go of are the ones we need to relinquish. Awareness is like the flashlight shining light on the dark corners of your mind.

As we land back at the space station, the universe didn't give me the answer, it gave me the peak. And the only plausible answer to anything was simple: awareness.  Being aware of your own thoughts, the identity you create for yourself, the world around you, your own body, you’re feelings. It’s about getting out of your head, and actually looking at the world. Not some sort of delusional fantasy you project onto it. To strive to be Moon 3-like, but accepting the fact that sometimes, we may fall to Moon 2. To quiet the space rain thunderstorms. 

Because the truth is actually right in front of us, like a constant humming noise, choked, drowned away in the frenetic pace of our everyday reality. It's just too loud to hear it.  

The 30-Day No Alcohol Challenge

College. The only time when it’s OK to be an alcoholic. Getting fucked up on a Wednesday doesn’t mean you have a problem. It means you’re in a frat. Getting the most inebriated is a badge of honor, while sleeping next to the toilet is the badge of shame. And for most sheltered kids in high school, alcohol and partying shattered the shell of my introversion/shyness.

Throughout those college years, alcohol allowed me to express the part of myself that I couldn’t express sober. Super social, can act cool, amazing beer pong player, flirting with girls( which still needs work), I could say the things that I’d be too scared to say sober. I could be the person I was afraid to be.

And for most people, as you mature, you start to get comfortable in your own skin. You get better at expressing who you are. You start giving less fucks about what people think. You start becoming incapable of dealing with bullshit conversations. Life’s trivialities shrink as life experiences grow.

I’m still pretty young, 24, so I don’t want to sound too jaded. But obviously, my 24 year old self, is much much better at expressing myself than my 16 year old self. And my 30 year old self will be much better than my 24 year old self.

And as I’ve started getting more comfortable in my own skin, I started to question the need for alcohol in my life. Because the reason I started drinking in the first place, was to be the person I couldn’t be sober.

Does alcohol have a place in my life? Rather than flat-out quit, let’s test it out with a 30-day challenge: The 30-day No Alcohol Challenge.

In this post, I’ll talk about why I’m doing this, and alternative approaches I’ll use to drinking.

Why I’m doing this

I want to test out a few hypothesis that I think quitting alcohol will confirm:

1.     Improvement in my social skills: If I was learning how to play the guitar, I wouldn’t take 5 shots before practicing. Similar to guitar, social skills is a skill. How can I get better socially, if I can’t reflect on the previous night, and pin-point weaknesses in my social interactions? How can I get better with girls if I don’t remember how that interaction went, what I said?  

2.     More time to do cool shit: Most college grads working a full-time job realize that we don’t have as much free time as we did in school. For most jobs, we have less control over our time, which means our time is precious. I get annoyed when I spend my entire Saturday binge-watching youtube videos due to my hangover. I love learning new things, writing, going on adventures, and I can’t do that when I’m hungover.

3.     Increased inner-confidence: Learning how to have fun, in any situation, from my internal resources seems like a superpower. No matter where I am, what I do, I can have fun. This one is more about not being dependent on one thing to make me happy. 

How I’m Planning to Do this

Obviously, our moods and states change day-to-day. Some days we feel amazing, super confident, while other days we feel sluggish, anti-social. Usually after a long day’s work, our minds are in that thinking mode, which is good for work, but not very useful for being social. And alcohol often serves as the tool to help us stop thinking and loosen up. But since I’m quitting, I’ll need to figure out other methods of loosening up/turning off my thinking mind:

1.     Improv Comedy Warm-ups: Learning improv was a great way to learn how to loosen up, be silly and in the moment. There was an exercise where the group got into a circle. Each person would jump in the middle and be as silly, crazy as possible. Then the circle would mimic him/her. I would obviously do this solo. (15 minutes)

2.     Rapid-Fire Approaches: Before going to a social event, I’d go and strike up conversations with as many people as I can. That way, I’m forcing myself to be social, before my mind can catch myself. When I go into the social event, I’ll be ‘warmed-up’ socially, and then I can continue talking to people. ( >30 minutes)

3.      Social Challenges: There are a ton of different social challenges, but the key is to do something that isn’t socially normal. Some ideas:

-       Call restaurants/stores and tell them a joke

-       Ask random strangers to give you a compliment

-       Give 15 strangers high-fives

-       Put on your headphones and start dancing in public

-       Lie down in a crowded area

What I’ve learned from doing social challenges, is that they HAVE to be kinda scary and on the edge of my comfort zone. If they’re too easy, it’ll have no effect on me.

4. Self-Amusement: When I was less confident, I often supplicated to others. I’d try to say things to get them to like me. But I’ve realized, that when I say things to entertain myself, it puts me in a good mood. And then that good mood flows out to the people around me. And then people want to be around me. Kinda like when your friend is laughing too hard, and you start laughing, but don’t really know why. This one is less practical, and more about having awareness in a social situation.

Doing many of these will make me look like a crazy person to most people, which is the point. But what I’ve learned from doing weird things in public, is that people are usually too stuck in their heads to pay much attention to what I'm doing. And there are no social repercussions. In fact, the weirder I am, people come to respect me more, since most people would not have the balls to do that.

We’ll see how this goes. I’ll probably write up an update after the 30-days, to see what worked and what didn’t work, and whether I still want to stop drinking.

Using EV(Expected Value) on Life to make better decisions.

For a two month period, poker was my life. I’d spend four hours a day after work devouring every poker book out there, peppering my friend with poker questions, analyzing pot odds & equities, and thinking through hand combinations. I didn’t go out on Friday nights. I spent my Fridays with old NITS( just imagine an uptight, hand-shivering, wrinkle-skinned, 70 year old) and crazy, rich, middle-aged, money-addicted Asian dudes(gambling addicts), flicking chips and folding hands, for hours and hours at Commerce Casino. I’d ride the rollercoaster of emotion, feeling the euphoria of winning $560, while experiencing depressed, blood-drained feeling of losing my entire buy-in($500) within 20 minutes. And although poker can have a reputation as ‘degenerate gambling’, many of the nuances in the game were windows into amazing life lessons.

Poker is a game of decision-making with imperfect information. You can’t see your opponents’ hands. Chess, on the other hand, is a game with perfect information. You can see all the pieces on the board.

Life is a game of decision-making with imperfect information. When you make a major life decision(quitting your job, getting married, moving to a new city), you’re making the decision with a limited amount of information. You might want to move from Los Angeles to New Orleans, but you don’t fully know what type of people live in New Orleans, the culture and job prospects. When you quit your consulting job to look for something better, you might think you landed your dream job at a high-growth startup, but you don’t actually know if you actually like the heavy workload accompanying most startups. You might hate it.

In poker, there’s a concept called E(V). If you’ve taken a basic math class, you’ve probably heard of this concept. Here’s the formula:

                                    E(V) = (outcome) x (probability of outcome)

I don’t wanna get too math-y, but the idea here, is that at the poker table, I want to make money. So every decision I make should be aimed at making money. There are times I’ll lose money. But I know, that if I want to make money, I need to make good decisions. I want to make +EV(Expected Value) decisions. Even if I have pocket Aces, three opponents go all-in( which means I stand to win $1,500), AND the math says I’m supposed to win( 80% chance) some guy might get lucky and hit that 20%(yes, I’m salty).

If I extrapolate this concept onto my life, I want to be making life decisions that, in the long run, will provide a +EV return. I can make a good decision that goes sour, but as long as I continue to make good decisions, I’ll benefit in the long run.

To make this model easy to understand, let’s re-write the formula to account for both the risk of a good thing happening vs. the risk of something bad happening:

E(V) = (positive outcome) x (probability of positive outcome) + (negative outcome) x (probability of negative outcome)

So how do we take this concept and apply it to our life? Let’s walk through a few examples.

Let’s use girls first( since that’s what’s usually on my mind lol).

Let’s say I see an attractive girl on the street. She’s totally my type. Hipster-ish looking, kinda innocent, smiling and looks like she’s relishing in the moment.  If we apply this E(V) formula to the situation:

E(V) = (positive outcome = we end up dating/become friends) x (probability of going on date/friends) + (negative outcome = she rejects me) x (probability of getting rejected)

If you look at my situation, intuitively, you’ll see that the E(V) in this situation is SUPER high. Dating someone or making a new friend adds enormous amount of happiness to my life, whereas rejection is the WORST thing that could happen, in that case, I just move on with my life. I would be in the exact same spot, if I didn’t talk to her. There’s only upside in this situation, no real downside. But unfortunately, there are many moments I don’t do it :(

 In another situation, let’s say I’m a parent with two children. I don’t like my job and want to quit to start my own business. However, my business isn’t making enough money to support my family. If I plug into the E(V) formula:

E(V) = (positive outcome = business takes off) x (probability of outcome) + (negative outcome = no job, no money, risk safety of kids) x (probability of outcome)

Looking at this situation, the probability of most entrepreneurs succeeding is <10% while the probability of the negative outcome is pretty high( 90%+). In the long-run, I’m making a negative EV decision here. The smarter decision for me, would be to build the business until it’s earning enough money to support my family, ensuring child safety, before leaving my job.

Another situation, let’s say that I’m 22 years old, I have $10k in my bank account and want to delay working for a year to travel the world:

E(V) = (positive outcome= amazing adventures, friends, life experiences) x (probability of outcome) + (negative outcome= One step behind in career, forego earning a salary for a year) x (probability of outcome)

I actually feel like this situation, depends on my values. If I value adventure/life experiences more, my positive outcome would increase. I would think that starting work at 22 vs. 23, doesn’t make much of a difference in the long-run and the value I’d get from life experiences would outweigh not working, giving me a positive EV. If I valued careers/money, the negative outcome would be higher. I’d see that a year of not deliberately building skills, delays my journey towards mastery/excellence. It’d be $30k not added to my savings, which compounded over 20 years on an 11% return, would be $518,620.48 I’d be foregoing.

And this difference in viewpoint leads to my next point…….

Weaknesses of this model

Judging value and probability is entirely objective. For me, I value learning over security, which means my equation is gonna be drastically different from someone who values a safe, secure life. Because every person has a different set of values, their EV calculation is gonna be different.

As for probability, unlike in poker, blackjack, there’s no formula to calculate an exact number. In life, there are just too many moving parts. The only thing I can do, is make my best guess. And my feeling, is that we all get better at estimating our % with more life experience & more decisions made.

But what about going for my dreams?

There are a lot of professions that may seem to have a – EV, especially artistic professions like writing, painting, dance. I’m not in a position to say whether these careers are positive or negative EV. But my thought, is that people who choose to go into a –EV career, go into that career knowing the odds are stacked against them, but doing it anyways. To quote Elon Musk(again):

“When something is important enough, you do it even if the odds are not in your favor.”

And life isn’t a casino. You have control over your odds :) 

My New Adventure into the World of Data Science

Over the past year and a half, I've learning a variety of skills: freestyle rap, dance, pick-up/social dynamics, copywriting, improv, speed-reading/memory techniques, entrepreneurship, digital marketing, web development and poker. The goal was to "learn how to learn" aka meta-learning. And while learning a ton of random skills is pretty fun and makes me an interesting person, if I'm looking to get enough at something to turn it into a career, I need to focus on getting good at one skill.

And after a year and half of island hopping, I've decided to dive headfirst into a new adventure: data science. And i use the word "adventure" because seeing this as an "adventure" sounds much more appealing than just "pivoting careers."

And from now on, I'm no longer gonna write in the 'you' format. For a couple reasons:

1. I'm not in a position to tell you what to do with your life. I can only speak to my own experiences.

2. Sick of internet writers telling me '10 ways to be more successful' or '5 hacks to be more productive.' --> Charlatans. 

Hence, I write about what I learn in life, through more of an immersive journalism lens. If you can relate or get value from it, even better. 

I'm writing this post for a couple reasons:

1. To share my thought process on how I chose Data Science. My way is definitely not the "right" way. But it's different from the "find your passion" dogma floating around millenials. This works for me, maybe it'll work for you :) 

2. I'm all about clean, fluid thinking. And by getting my thoughts out onto the page, I can dissect my thought process and identify flaws in my thinking. 

Before I dive in, I want to introduce a concept called first principles thinking , which has had an ENORMOUS influence on how I think about thingsAs Elon Musk says:

“I think it is important to reason from first principles rather than by analogy. The normal way we conduct our lives is we reason by analogy. [When reasoning by analogy] we are doing this because it’s like something else that was done or it is like what other people are doing — slight iterations on a theme.

First principles is kind of a physics way of looking at the world. You boil things down to the most fundamental truths and say, “What are we sure is true?” … and then reason up from there.

Somebody could say, “Battery packs are 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.”

With first principles, you say, “What are the material constituents of the batteries? What is the stock market value of the material constituents?”

It’s got cobalt, nickel, aluminum, carbon, some polymers for separation and a seal can. Break that down on a material basis and say, “If we bought that on the London Metal Exchange what would each of those things cost?”

It’s like $80 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.”

In order to figure out which direction I wanted to go, I asked myself three, first principles questions:

1. What do I enjoy? When I was a kid, I was obsessed with sports. To this day, I still remember random, arbitrary facts from over a decade ago. I remember that Tom Brady( quarterback of the New England Patriots) went 9-7 in 2002 and missed the playoffs the year after he won his Super Bowl. I remember in 2006, the lone season Randy Moss played a full season on the Raiders, he had exactly 1005 receiving yards(without Googling the numbers). Obviously, those last two sentences won't make sense to those who don't watch football. But the idea is that numbers/stats came pretty easily to me. I don't know if it's my passion, but I enjoyed it, which leads me to the next question......

2. What am I good at? Ever since I've started blogging, a lot of people have told me that I'm pretty good at writing. Obviously, this judgment is relative. I would say I'm OK, relative to my peers. But the odd thing is, when I was a kid, I wasn't a good writer. I got a 520 on the SAT writing section. I've never gotten an A on a paper until I was in college. And I probably read around 1 or 2 books a year when I was a kid. 

But I was killer at math. I got an A in every single math class I've ever taken( except one Calculus class in college). Obviously, as I read and write more, I get better at it. But as Gary Vaynerchuk says:

" Go all-in on your strengths and outsource your weaknesses."

I don't think taking this advice to the extreme is helpful. But I do agree, that focusing on things that come a bit more naturally to me eases my climb towards mastery.  

3. What's going to be important in the future? Money is usually the sign that I'm doing something valuable for the world. There are exceptions, like getting rich off gambling, or daytrading, but I believe that when I add real value to the world, the world will reward me with more than enough $$$.

And if I do want to add value to the world, thinking about what's important in the future, can be the door to figuring out what skills I want to focus on. 

Obviously, when thinking about the future, there are A TON of "important" things. Too many to list in a blog post. Combining future importance with my interests, I wittled my list to these items:

- Virtual Reality

- Artificial Intelligence/Big Data

- Renewable Energy

- 3-D Printing

- Human DNA Sequencing

- Nano-technology

Using my answers from questions 1 and 2, out of all the options, transitioning to AI/Big-Data probably has the least amount of friction considering my current skillset/interests/strengths. 

Conclusion:  Data Science

Obviously, I don't know if this is "what I want to do." But I've come to the conclusion, in every stage of my life, I'll always be figuring out what's next. Like Ralph Waldo Emerson says: 

" The voyage of the best ship is a zigzag line of a hundred tacks. See the line from a sufficient distance, and it straightens itself to the average tendency. Your genuine action will explain itself, and will explain your other genuine actions. Your conformity explains nothing. Act singly, and what you have already done singly will justify you now." 

The journey never ends. There might be a point where I reach the end of my Data Science adventure. What will I do? I'll find a new adventure. 

 

 

 

 

 

Bruce Lee on How to Live

 

" Empty your mind. Be formless. Shapeless. Like water. You put water into a cup it becomes the cup; You put into a bottle it becomes the bottle; You put it in a teapot it becomes the teapot. Now water can flow or it can crash. Be water my friend. " - Bruce Lee  

Note: Excuse my second grade drawings

I always thought of Bruce Lee as some fierce, rock-hard ab, gung-fu artist. When I was obsessed with working out, I'd constantly google 'Bruce Lee' workouts and try to mimic them. However, I had no clue this dude wrote about philosophy, life and self-actualization.

Anyways, I picked up "The Warrior Within" by John Little and I was literally put to tears reading about his philosophy. 

I thought I'd share with you two things I learned from the book:

1. Self-Actualization

Copying Lee's philosophies would go against the very principles Lee stood by. As his son Brandon says:

"When I did The Green Hornet television series back in 1965, I looked around and I saw a lot of human beings. And as I looked at myself, I was the only robot there. I was not being myself. I was trying to accumulate external security, external technique- the way to move my arm and so on--- but 'such a thing had happened to me?' When I look around, I always learn to have faith in yourself. Do not go out and look for a successful personality and duplicate him. That seems to me to be the prevalent thing happening here in Hong Kong. They always copy a person's mannerisms, but they never see beyond that. They never start at the very source, the very root of their own being, and ask the question: 'How can I be me?'"

Lee defined the summit of human achievement, not in success or financial reward, but by the honest expressing of oneself:

"In life, what more can you ask for than to be real? To fulfill one's potential instead of wasting energy on [attempting to] actualize one's dissipating image, which is not real and an expenditure of one's vital energy. We have great work ahead of us, and it needs devotion and much, much energy. To grow, to discover, we need involvement, which is something I experience every day--- sometimes good, sometimes frustrating. No matter what, you must let your inner light guide you out of the darkness." 

Because when I'm not in touch with my honest feelings, how can I expect to truly enjoy the juices of life? How can I truly create something original? There is no such thing as copied originality. Because the next Bruce Lee will not be Bruce Lee. The next Mark Zuckerberg will not be Mark Zuckerberg. The next Steve Jobs will not be Steve Jobs. 

But what does honest self-expression actually mean? I think it means to just know what you want from life, independent from the crowd. And that's really hard, because people, society, constantly hammer their un-grounded beliefs and ideas into your head. And if you're not careful, a nail might get lodged into your brain. 

But does this mean that I should discount advice from "successful" people and solely trust myself? I don't think it's that black and white. Lee outlines a four-step process he teaches in jeet kune do:

" 1) Research your own experience

2) Absorb what is useful

3) Reject what is useless

4) Add what is specifically your own "

Because the only way to develop an intuitive grasp of what works for me and what doesn't, can only come from experience.

2. Relationships

In addition to self-actualization, Lee beautifully articulates his beliefs on love:

" Love is like a friendship caught on fire. In the beginning, a flame, very pretty, often hot and fierce, but still only light and flickering. As love grows older, our hearts mature and our love becomes as coals, deep-burning and unquenchable."

Because long-term romance isn't the exciting, passion-filled romance of young, crazy adventures. It's that mundane, 6000th dinner, after a tired day of work:

"The happiness that is derived from excitement is like a brilliant fire--- soon it will go out. Before we married, we never had the chance to go out to nightclubs. We only spent our nights watching TV and chatting. Many young couples live a very exciting life when they are in love. So, when they marry, and their lives are related to calmness and dullness, they will feel impatient and will drink the bitter cup of a sad marriage" 

But Lee doesn't limit his definition of relationships to romance. The ultimate relationship is the one between life and death:

" Like everyone else, you want to learn the way to win, but never to accept the way to lose. To accept defeat-- to learn to die-- is to be liberated from it. Once you accept, you are free to flow and to harmonize. Fluidity is the way to an empty mind. So when tomorrow comes, you must free your ambitious mind and learn the art of dying." 

We learn to live by learning to die, while many of us are dying to live. We're in this constant searching for money, posessions, a lust, to allow us to start living. In reality, we don't need to ask the world for permission. We have permission. We just need to choose to use it. 

The Warrior Within by John Little is a beautiful book on the philosophies of Bruce Lee. Highly recommended.