A brief homage to two new-ish dev tools. I recently transitioned my Python workflow to uv, and I’ve been using it alongside Ghostty.

Distortions in the uv. All the details of a side quest to get a solid grasp on dependency management with uv!

Step by step build of a minimal neural network. In a separate post, I did a selective pass over the development of artificial neural networks to highlight baked in design choices.

Inspecting a minimalist neural network … is a perfect way to get to know your way around the essential components.

A tiny exploration of plotting math functions in Rust. Interested in learning about the Julia and Mandelbrot sets?

Great craftsmanship - worth the effort and the wait. Quoting Peter Norvig’s Teach Yourself Programming in Ten Years:

The wild beast. Python is the defacto language of machine learning.

Memory management and Rust’s data ownership model. Rust guarantees memory-safety without the overhead of a garbage collector by implementing a unique data ownership model.

🌱 Notes 🌱 … masquerading as a post. Initially intended to gather developers’ ML workflows, dev tools and discourse on AI/AGI got patched in.

Getting ready to Go. I’ve been working in Python and learning Rust, ignoring Go for a few months.

Learning a bit of Rust… is one of my 2024 batch goals at Recurse.

Free range programmers. “The retreat where curious programmers recharge and grow.

Mechanistic interpretability for transformer architectures (and more!). During my second batch at RC, I joined a study group to cover the materials from Callum McDougall’s Alignment Research Engineer Accelerator aka ARENA program which is normally delivered by LISA: the London Initiative for Safe AI.

Welcome! 👋 In the past, I’ve used a few other platforms for (sporadically) posting my writing (see Medium and Substack Posts).

🌱 Notes 🌱 … on learning about machine learning. Where to begin?

Recursive sidequest. During my first Recurse Center retreat in the fall of 2021, I started learning Python in earnest (along with a little React on the side), worked on code craftsmanship, and started to fill in the gaps of my non-CS background on any aspects of computing I happened across during study sessions or while pairing with fellow Recursers.

In addition to research publications, I have a small collection of prior publicly-shared works on Medium and Substack.

This post shares a bit about the translational geroscience portfolio I nurtured into being at the University of Oxford between early 2019 and mid-2021.

Scaling biohacking. Longevity intervention can be a loaded expression, too often carrying the weight of association with quests for immortality.

Notes from James Mickens’ talk at USENIX Security ‘18. If you haven’t seen James’ talk and have an hour to view his actual keynote, please do yourself a favor and just go see his talk.

Humanity in an AI-enabled world. In studying AI, ML, and the general advance of technology — and observing the response to the hype that surrounds all that — I’m compelled to ask whether we’re fully considering our power in determining the nature of the influence of technology.

Caveat emptor! Written in November 2017. Progress in AI is astonishingly rapid: this is inevitably out of date.

Inverse problems. Much of the complexity of the human body is shrouded in mystery.