You've made it.
Hi! I'm Sam Ritchie.
I'm currently working as a senior staff research engineer at the MIT Probabilistic Computing Project, exploring and building out tools in support of a system of intelligent, networked books; more on this coming soon.
Previously I've spent time as a staff research engineer at Google X, working in the field of AI and deep reinforcement learning. I've spent most of my career working on large-scale streaming systems for companies like Twitter and Stripe. I'm quite interested in the problem of how to present research results in interactive ways that make results intuitive and visual; the relevant phrase is, "Kill the PDF".
I'm most well known in the software world as the author of the Emmy computer algebra system, Summingbird, and Algebird, and as the maintainer of Cascalog. I have a secret identity as a mountain athlete, and write race reports from time to time.
Here are a few sequences of posts that you might find interesting. If you do find anything valuable, please consider supporting my work via GitHub Sponsors.
Race Reports (index)
- Leadville Trail 100 2013
- Leadville Trail 100 2014
- Wasatch Front 100 2014
- Miwok 100k 2015
- IMTUF 100 2016
- Vapor Trail 125 Mountain Bike Race 2017
- Niwot's Challenge 2018
- Rainier Infinity Loop 2018
- Tahoe 200 2018 (and part 2!)
- Niwot's Challenge 2019
- Texas Water Safari 2019
Book Reviews (index)
I'm working on a number of book reviews; I'll post them here as I start to produce them. In the meantime you might be interested in my bookshelf.
I post books I'm reading, or have read, on my Goodreads account here.
Here are the reviews:
- 5 Books for Endurance Addicts
- The Measure of a Mountain, by Bruce Barcott
- The Second Kind of Impossible, by Paul Steinhardt
- On Having No Head, by Douglas Harding
- The Second Mountain, by David Brooks
These are forthcoming. I'm working on a number of teaching tracks on various subjects in math, programming and overall learning. Check back in for in-depth series on:
- Reinforcement Learning (An original course on Functional RL)
- Quantum Mechanics: The Theoretical Minimum
- Functional Numerical Methods
- Machine Learning Model Explanations
- Naive Set Theory
- Deep Neural Networks
- How to Read a Book
- Concepts of Modern Mathematics
- The Art and Science of Doing Engineering
- Approximate Data Structures (Exact Counts are Bullshit!)
- Entropy - Permutations and Combinations
- Taylor Series and Imaginary Numbers
- Power Series, Power Serious
Tidbits, insights into my odd mind.
- The Dreadful Secret of Platypus Boarding School (my 7th grade masterpiece.)