Programmer Weekly (Issue 234 December 5 2024)

Programmer Weekly - Issue 234

December 05, 2024

Programmer Weekly

Welcome to issue 234 of Programmer Weekly. Let's get straight to the links this week.

Quote of the Week

 

"Inheritance is surely a good answer, but who knows the questions?" - Michel Gauthier

Reading List

Meta built a large-scale system to monitor how cryptography is used across their products (Facebook, WhatsApp, Instagram etc.). This helps them identify weak encryption algorithms and improve overall security, with minimal impact on performance.

How I cut infrastructure costs by 75% and increased compute by 2x.

The article describes a method for breaking 4chan's CAPTCHA system using machine learning techniques. It details the process of collecting CAPTCHA images, preprocessing them, training a neural network model, and ultimately achieving a high success rate in solving the CAPTCHAs automatically.

The article provides a comprehensive guide on running Large Language Models (LLMs) locally using llama.cpp, covering installation, building, and usage across different hardware setups. It explains how to set up the environment, build llama.cpp, and run models on various devices, including CPUs and GPUs, with a focus on making LLMs accessible for personal use.

When do you need a Staff Engineers? What's the accountability model with or without?

The article explains why pipes in Unix-like systems can appear to "get stuck" due to output buffering, which occurs when programs save up data before writing to pipes for performance reasons. It discusses various solutions to this issue, including using specific command flags, alternative commands, or tools like stdbuf and unbuffer, while also exploring the behavior of different programs and programming languages regarding buffering.

Optimization and automation can be useless and reckless, outmatched by systemic pressures and their trade-offs. Localized friction, hidden by optimizations, can hold the key to larger scale impact.

Watch and Listen

The video explores the nature of software complexity, distinguishing it from difficulty, and examines how systems evolve from simplicity to unmanageable complexity due to factors like scale, leaky abstractions, and mismatched models. It also discusses strategies for managing complexity, such as using type systems, aligning models with reality, and designing systems appropriate for their current scale.

The programming landscape has shifted from favoring object-oriented paradigms to embracing procedural and functional styles, with languages like Go and Rust omitting traditional object-oriented features such as classes and inheritance. Procedural programming is resurging due to its simplicity and efficiency, as seen in the popularity of low-level systems languages like Zig, Odin, and Jai, offering an alternative to both object-oriented and functional approaches.

Interesting Projects, Tools and Libraries

Open Source Browser API for AI Agents & Apps. Steel Browser is a batteries-included browser instance that lets you automate the web without worrying about infrastructure. 

Terrateam is an open-source GitOps CI/CD platform for automating infrastructure workflows. It integrates with GitHub to orchestrate Terraform, OpenTofu, CDKTF, and Terragrunt operations via pull requests.

blazing fast `ls` replacement with superpowers. 

Share your screen with one simple room code. No downloads or sign-ups required. 

Self Hosted Alternative To Google Analytics.

A minimalistic text editor for terminal fanatics.

Privastead is a privacy-preserving home security camera solution that uses end-to-end encryption.

Cross-Platform screen sharing made simple.

A fully static distributed library system powered by IPFS, SQLite and GitHub.

A GPU-accelerated 2D graphics environment for Node.js. 

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