This early April, I once again got the opportunity to head to Palo Alto and spend a week at K-Scale Labs: learning from founders, engineers, and designersβall truly united by the goal of changing the world.
Our mission at K-Scale Labs is to make humanity into a Type 1 Kardashev scale civilization. This means building a civilization that is capable of harnessing all of the energy available on Earth and channeling it toward beneficial outcomes. We are doing this by building general-purpose humanoid robots as vehicles for embodied intelligence.
Here are some insights I gathered throughout my time inside and outside the office:
- Picking your mission
- Find role models: read books and biographies; listen to podcasts and audiobooks
- Try lots of different thingsβevery single thing you can possibly try
- Life is a lot of different games and you can do literally anything. Look at every opportunity as a math function youβre trying to optimize for: social life, career aspirations, or the impact you want to make. Maybe even more specific: a person in your life, a goal you hope to achieve, or a trait you hope to build up.
- While optimizing these functions, you need to ensure youβre finding the global maximumsβnot getting stuck in the relatives. More importantly, be very very careful in choosing the functions you choose to optimize forβbecause you definitely canβt pick all of them
- A useful question to consider prior/during optimization is the Hamming Question: βWhat are the most important problems in your field, and why arenβt you working on them?β
- Eventually, when you know what you want to do, focus on that. This game is your game now. Cut out all the noiseβotherβs expectations of you, distracting goals outside of what you want to focus onβand focus on these games alone.
- When you stop playing other peopleβs games, you start competing WITH everyone else rather than AGAINST everyone else
- Game Theory & Molarity
- In another conversation, I expressed frustration about things in my own lifeβand our conversation turned into how game theory ties into our real life
- The Frustration
- Itβs easy to feel disillusioned when you play fair (working hard, being honest, helping others) while others cut corners, manipulate, or cheat and seem to win. In the short term, dishonesty can look like the smarter strategy.
- The One-Shot Game Trap
- If life were a single round, cheaters would always win. In a one-shot payoff matrix, defection dominates because there are no consequences tomorrow. Thatβs why, in isolated moments, dishonesty looks like it pays.
- Life is a Repeated Game
- But life isnβt one round, itβs an ongoing repeated game. In repeated games, cooperation is the rational equilibrium. Over time, honesty and trust compound into stronger networks, reputations, and opportunities. Exploitative wins are brittle; cooperative wins are durable.
- Variance vs. Value
- Short-term setbacks (like losing to someone who cheats today) are just noise in a long game. They donβt erase the higher long-term expected value of playing honestly. The real challenge is staying committed when the short-term variance stacks against you.
- The Payoff of Integrity
- Seen this way, morality isnβt just about βbeing good.β Itβs also the rational way to maximize cumulative reward over a lifetime. Integrity is a long-term winning strategy, and my all-seeing grandparents have always been right.
- Outside of just finishing the AP Microeconomics Oligopoly unit, this conversation also reminded me of an interesting Veritasium video about game theory which I would definitely recommend watching
- Seek discomfort
- Pull out a sheet of paper and write down the 30 things you fear the most
- Starting from the easiest, go through every single thing on the list and fight it the hardest you can
- When you conquer your fears, youβre quite literally the strongest person you possibly can be
- Book Recommendation: The Courage to Be Disliked
- If you make your own decisions and it doesnβt work out, atleast itβs your own decision you regretβnot someone elseβs
- βPeople out in the world will want to expect and demand your goodness, but know that you donβt owe them itβ
All quotes are paraphrased or recreated to convey my own interpretation