Start here if you're new to ML. In nineteen problems we'll get from dot products to a working training loop, all in NumPy. Implement the building blocks (sigmoid, softmax, cross-entropy, attention masks), then build a linear layer and work through the backwards passes that make training work.

There are thousands of options in NixOS, but as users, we usually only interact with a select few of them. Despite that, a huge amount of those options does influence the final result in some way. Have you ever wondered which of them were actually relevant for your specific system?

Some reflections on trusting trust, and how deep the rabbit hole goes.

Last year, I came agross a Linux kernel feature called TCG_TPM2_HMAC. It claims to detect or prevent active and passive interposer attackers.
It all sounds really great. We should care about interposer adversaries. It’s great to use the TPM features that were invented to help us with these problems.

Pipes are ubiquitous in Unix --- but how fast can they go on Linux? In this post we'll iteratively improve a simple pipe-writing benchmark from 3.5GiB/s to 65GiB/s, guided by Linux perf.

This is a tutorial on how to build a digital implementation of a 2nd-order, continuously-variable filter (i.e. one where you can change the parameters runtime) that has dynamic behaviour that mimics an analogue filter.

In this deep dive post, I’ll explain how I used the interning design pattern in Rust to compress this data set by a factor of two thousand! We’ll investigate how to best structure the interner itself, how to tune our data schema to work well with it, and likewise how serialization can best leverage interning.

In a previous post, I’ve shown how to use the rayon framework in Rust to automatically parallelize a loop computation across multiple CPU cores.
In this post, I’ll first explain which profiling tools I used to chase optimizations, before diving into how I built a faster replacement of Rayon for my use case. In the next post, I’ll describe the other optimizations that made my code much faster. Spoiler alert: copying some data sped up my code!

This blogpost describes our investigation and proof of concept to enhance the security of Signal Messenger key management on desktop.

I want to try to catalog the bits that I wish someone had just told me before working with a Postgres database. Hopefully, this makes things easier for the next person going on a journey similar to mine.

Commentary on software, robotics, and computer vision.

Web browsers are ubiquitous, but how do they work? This book explains, building a basic but complete web browser, from networking to JavaScript, in a couple thousand lines of Python.

Explore the In Our Time archive.

In this article we build off what we’ve already learned about io_uring and extend that to build an async echo server.

TL;DR: A world first reverse engineering analysis of AWS Session Tokens. Prior to our research these tokens were a complete black box…

We're Sequin, an open source message stream built on Postgres. We think Sequin's cool, but you don't need to adopt the project to get started with streaming in Postgres. In fact, you can turn Postgres into a basic queue/stream pretty easily. Below, we share what we've learned so you

We examine the recent CrowdStrike outage and provide a technical overview of the root cause.

Talk from POSETTE conference