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.

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

Poettering said that he does have a vision for how all of the security-related pieces of systemd are meant to fit together. He wanted to use his talk to explain ""how the individual security-related parts of systemd actually fit together and why they exist in the first place"".

Achieving high-performance asynchronous Rust projects transcends mere usage of the async/await syntax; it fundamentally relies on a deep understanding of the underlying task scheduling, lock optimization, and architecture design principles.

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.

This post can be considered an advanced Zig tutorial. I will be covering some of the more unique
aspects of the language, but won't be explaining the easy part. If you haven't read the Zig
Language Reference, you might start there. Additionally,
we will also learn the foundational trick for implementing relational model.

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!

Macros, iterators, patterns, error handling and match make Rust almost perfect

Commentary on software, robotics, and computer vision.

This guide explains everything you need to know to build stand-alone photovoltaic systems that can power almost anything you want.

The course is a hands-on, research-level introduction to the areas of computer science that have a direct relevance to journalism, and the broader project of producing an informed and engaged public $100 installment loan. We study two big ideas: the application of computation to produce journalism (such as data science for investigative reporting), and journalism about areas that involve computation (such as the analysis of credit scoring algorithms.)

Below is a list of some lessons I’ve learned as a distributed systems engineer that are worth being told to a new engineer. Some are subtle, and some are surprising, but none are controversial. This list is for the new distributed systems engineer to guide their thinking about the field they are taking on. It’s not comprehensive, but it’s a good beginning.

In a previous article, I described how to set use Nix and Niv to configure an Elixir dev environment. This setup can be simplified by using Nix flakes instead of Niv.

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

The underlying problem we are facing here with all these examples is the same: having the same set of bits which can mean two different things and needing some way to distinguish those two meanings. Failure to do so leads to ambiguity at best and serious defects at worst. That's why you see so much emphasis in modern systems on type safety and on strict domain separation between different meanings.

JTAG for Reverse Engineers

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