Biography
♠️ I started my adult life as a pro poker player. I also coached and wrote about game theory.
🧠 I studied cognitive science and philosophy of mind with an undergraduate thesis using convolutional neural networks pre-trained with denoising autoencoders.
💻 I worked as a machine learning engineer at a startup working on real-time (sub-40ms latency) models, and then as a data scientist at a multinational nonprofit.
I attended the Recurse Center, and ended up starting a company with my batchmate Nick Sweeting.
Monadical has grown to a team of over 30 engineers who have built over 100 projects, with a focus on state-of-the-art AI technologies, data engineering, gaming, and high-performance blockchain applications. I love this work because I get to learn something new with each project.
More recently, I teamed up with Jordan Steiner to launch Developer Capital, a pre-seed and seed-stage investment corporation. We strive to provide what other investors promise: real support for our investments in the form of actionable technical and operational support via its partnership with Monadical.
Writing
Here is a selection of articles I've written, hosted on Monadical's blog.
- All Systems are Human Systems
- Event-Driven Architecture
- The Monadical Principles Handbook
- How to Make Remote Work: Part Two, Zulip
- How to Make Remote Work: Part One, My Routine
- The Myth of Trustlessness
- An ELI5 explanation of Segwit, the Lightning Network, and how they are related
- Downsings and the Information Game
Talks
Here are some talks I've done. They range in intended audience from children to senior engineers.
How AI Will Impact your Business
This is a presentation I prepared for an audience of business owners and entrepeneurs on how the computer transformed the aviation industry in the 50s and 60s, some basics about the nature of AI, and how I think AI is poised to change the business world in the near future.
Slides (presented May 2024)
A Monopolies and AI
I did a presentation about Lina Khan's FTC, tech monopolies, and what I think of Monopoly risk in the AI sector.
Slides (presented in March 2024)
Papers We Love: Highly accurate protein structure prediction with AlphaFold
I presented for the Montreal chapter of Papers We Love. The audience tends to be highly technical, and curious to learn about a concept in some detail. The talk begins with a primer in artificial neural networks, and then a primer in biology, before explaining the core concepts and architecture of AlphaFold2.
Slides (Presented Nov 2021)
Game Theory in Practice: Lessons from a Professional Poker Career
This was a that I originally did in front of an audience at the Recurse Center in the summer of 2014, when my batchmates learned about my background and were curious to learn about poker theory.
Slides (presented in 2014)
TDD Made Easy
This was a short, practical presentation on the test-driven development approach we took to building the oddslingers codebase.
Slides (presented in Feb 2020)
Welcome To Your Mind
I did this presentation a few times in front of technical audiences in 2014. I had arrived at the field of artificial neural networks from cognitive science and philosophy, and was interested in the the concepts that had emerged from the fields of AI and neuroscience with respect to the nature of intelligence, and wanted to share what I had learned.
Slides (presented in 2014)
Contact
Location:
Montreal
Email:
[My first name] at [my company's website]
Schedule a call:
