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Advice to Young People, The Lies I Tell Myself

I'm really not qualified to give advice. But enough people DM'd me on Twitter, so here it is. I don't have to answer the same question over and over again. After some more editing I realised that I am actually writing this for my younger sister Katherine.

If you want to know who I am, check out blog/whoami or my Twitter.

Don't read this if you're seeking a nuanced perspective

These are simply the lies I tell myself to keep on living my life in good faith. I'm not saying this is the right way to do things. I'm just saying this is how I did things. I will do my best to color my advice with my own experiences, but I'm not going to pretend that the suffering and the privilege I've experienced is universal.

A feat of strength MVP for AI Apps

A minimum viable product (MVP) is a version of a product with just enough features to be usable by early customers, who can then provide feedback for future product development.

Today I want to focus on what that looks like for shipping AI applications. To do that, we only need to understand 4 things.

  1. What does 80% actually mean?

  2. What segments can we serve well?

  3. Can we double down?

  4. Can we educate the user about the segments we don’t serve well?

The Pareto principle, also known as the 80/20 rule, still applies but in a different way than you might think.

How to ask for Referrals (Among other things)

How can I help? Do you know anyone that could use my help? Do you know anyone that could use my services?

These are all examples of exceptionally low agency questions. Not only is it difficult to answer the question, you subject your victim to a lot of additional work and thinking in their busy day.

It's like seeing your mom sweating away busy cooking, chopping vegetables and asking "How can I help?" It's a lot of work to manage you, and it's a lot of work to think about what you can do. Now she has to consider what's in your ability, what the unfinished work is, and prioritize that versus the other.

This post is my simple framework on how I ask.

My year at 1100ng/dL

I'm not a doctor, but I did manage to double my testosterone levels in a year. I'm going to talk about what I did, what I learned, and what I think about it:

  1. It's just a fact that male testosterone levels have been dropping for the past couple of years.
  2. I felt like I was in a rut and I wanted to feel better, and I did.
  3. I was such a psycho about it that I decided to go off the protocol.
  4. Despite that, I still think every man should get their levels tested and see if they can improve them. And just understand how they feel.

What I Learned from Indie Consulting

Fragments

If you think this writing style is strange, this is because much of this writing is actually a collected batch of voice memos transcribed into an essay using betterdictation.com's distilled whisper model. There will likely contain errors, as there are pieces and fragments of some of the thoughts I have on the topic. I welcome all most all edits and comments.

I specify indie consulting as something that is completely and wholly separate from the big-time consulting we hear about from those ridiculous institutions. Check out this video roasting McKinsey From John Oliver to understand how I feel about many of these folks. Theres another great video that I saw on tiktok.

If you want to learn about my consulting practice check out my services page.

A Critique on Couches

Here are some fragmented reasons as to why I don't like having a couch.

The couch, often positioned facing a television, symbolizes the societal imposition of a predetermined essence onto our living spaces. This arrangement, reminiscent of Sartre's concept of bad faith, dictates the room's function and restricts its potential. It mirrors the limitations we place upon ourselves when we conform to societal expectations, disregarding our authentic selves.

For real.

Tips for probabilistic software

This writing stems from my experience advising a few startups, particularly smaller ones with plenty of junior software engineers trying to transition into machine learning and related fields. From this work, I've noticed three topics that I want to address. My aim is that, by the end of this article, these younger developers will be equipped with key questions they can ask themselves to improve their ability to make decisions under uncertainty.

  1. Could an experiment just answer my questions?
  2. What specific improvements am I measuring?
  3. How will the result help me make a decision?
  4. Under what conditions will I reevaluate if results are not positive?
  5. Can I use the results to update my mental model and plan future work?

I used to hate rich people.

This entire piece of writing is dedicated to a recent response on Hacker News. I hope you can see, as a member of reality, that I write this sincerely.

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Preamble

Also, I wrote this as a speech-to-text conversion. As I mentioned in my advice post about writing more, my measure for writing more is simply putting more words on a page. If you're wondering how I can be so vulnerable, it's the same as what I mentioned about confidence. If you think this comment hurt me remember that you're just a mirror.

I've also learned that writing is a exorcism of your own thoughts. The more I write, the less these thoughts stick around in my head.

Learning to Learn

After writing my post advice for young people, a couple of people asked about my learning process. I could discuss overcoming plateaus or developing mastery, learning for the joy of learning. I could also talk about how to avoid feeling overwhelmed by new topics and break them down into smaller pieces. However, I think that has been done before.

Instead, I'm going to explore a new style. I'm just going to go through a chronological telling of my life and what I learned from just trying new things. I'm going to talk about the tactics and strategies and see how this pans out.

Who am I?

In the next year, this blog will be painted with a mix of technical machine learning content and personal notes. I've spent more of my 20s thinking about my life than machine learning. I'm not good at either, but I enjoy both.

Life story

I was born in a village in China. My parents were the children of rural farmers who grew up during the Cultural Revolution. They were the first generation of their family to read and write, and also the first generation to leave the village.