The author describes their rather interesting struggle with learning to read as a child: certain letters would all look the same, and their brain would attempt to rotate them as if they were an interactive objects. To cope they developed a ‘skyline approach’: every word forms a unique shape like the skyline of buildings.

Their dyslexia obviously still affects them as an adult, and particularly as a software engineer. For their brain, languages that use s-expressions (Lisps) form a consistent visual shape.

There’s languages that try to compact or compress as much semantic information as possible into tokens and syntax, meanwhile with lisp the semantics are front-loaded with verbose function, macro, and special operator names.

Scheme fascinates me even further. Many of the coding conventions in Scheme encourage people to use full and descriptive function names. I believe this gave my mind a deeper ability to organize the skyline shapes.

A curated collection of resources for learning Mandarin Chinese. Designed to help learners and expats master the language effectively.

This is the third test bookmark for testing updates. It’s public, not marked as to-read, and has multiple diverse tags.

Manage your AI data using Oxen’s state of the art data version control. Blazing fast, and Open source.

Interactive visualizations of TypeScript concepts. Behold pretty colors.

Open source resource for learning algorithms and their implementation in any programming language

flashcards in a private podcast feed. Knowledge in Audio format.

Agent Lightning is the absolute trainer to light up AI agents.

Features - Turn your agent into an optimizable beast with ZERO CODE CHANGE (almost)! 💤 Build with ANY agent framework (LangChain, OpenAI Agent SDK, AutoGen, CrewAI, Microsoft Agent Framework…); or even WITHOUT agent framework (Python OpenAI). You name it! 🤖 Selectively optimize one or more agents in a multi-agent system. 🎯 Embraces Algorithms like Reinforcement Learning, Automatic Prompt Optimization, Supervised Fine-tuning and more. 🤗

Frustrated by elusive names and misplaced phones? The science of memory reveals ways to improve your powers of recall. This Psyche guide provides practical, science-backed memory techniques and tips to help readers improve their ability to recall everyday information like people’s names and shopping lists.

This is a repo with links to everything you’d ever want to learn about data engineering. The Data Engineering Handbook on GitHub is a comprehensive, open-source guide and curriculum intended to help aspiring and current professionals master the skills and tools required to become a Data Engineer.

The fastest way to get better at something is to start slow. This article discusses effective strategies and mental models for improving the process of learning new things, covering topics such as meta-learning, spaced repetition, and active recall.

Create mind maps to learn new things using AI. Contribute to aotakeda/learn-thing development by creating an account on GitHub. The learn-thing GitHub repository is a personal knowledge base and collection where the owner documents and organizes various technical and non-technical topics they have learned, serving as a self-curated reference guide.

This comprehensive article from Farnam Street explains mental models, simplified explanations of how things work, across various disciplines (like physics, mathematics, and human nature) to help readers make better decisions and avoid common pitfalls.