Published on July 22, 2026 at 18:00 CEST (UTC+2)
Why I Am Not Going to Buy a Computer (41 points by KarlVM12)
Why I Am Not Going to Buy a Computer – Karl Muller reflects on Wendell Berry’s 1980s essay about refusing computers in favor of hand-writing and typewriters. He argues that the same disconnect Berry foresaw is now amplified by AI-generated art and writing, which strip away human meaning, emotion, and the learning that comes from the creation process. The piece warns that when work is done autonomously, people lose connection to the labor and the value of imperfection. It’s a philosophical critique of modern automation and its impact on human creativity.
Does creatine make you smarter? (19 points by surprisetalk)
Does creatine make you smarter? – This article explores the scientific evidence behind creatine as a dietary supplement, debunking myths about testosterone increase and hair loss. It explains that creatine is a normal nutrient found in meat and synthesized by the body, used for cellular energy delivery. The author reviews studies on cognitive benefits, noting mixed results but concluding that creatine is likely safe and might offer modest brain performance improvements. It’s a balanced, evidence-based take on a popular health topic.
The startup's Postgres survival guide (75 points by abelanger)
The startup’s Postgres survival guide – Alexander Belanger shares a practical, hard-earned guide for keeping PostgreSQL databases stable and fast as a startup grows. Starting from basic SQL knowledge, it covers indexing, ORM limitations, query optimization, and common pitfalls. The guide is intended for engineers who need to move beyond “slow query? add an index” and into deeper operational knowledge. It also references using AI assistants like Claude for query generation, warning that such tools can bypass understanding.
Show HN: HN Hall of Fame – browse 3,100 legendary Hacker News links (13 points by oyster143)
Show HN: HN Hall of Fame – browse 3,100 legendary Hacker News links – This site curates Hacker News submissions that have been rediscovered and resubmitted many times over many years. It organizes links by category (e.g., essays, tools, learning) and shows peak points, number of submissions, and time span. Examples include “We can’t send email more than 500 miles” and “Teach Yourself Programming in Ten Years.” It’s a nostalgic trip through HN’s most enduring content.
Show HN: Bento - An entire PowerPoint in one HTML file (edit+view+data+collab) (14 points by starfallg)
Show HN: Bento – An entire PowerPoint in one HTML file – Bento is a tool that packs an entire PowerPoint presentation (editing, viewing, data, collaboration) into a single self-contained HTML file. The goal is simplicity and portability, eliminating the need for PowerPoint software or complex file formats. The snippet provided is minimal, but the concept aligns with the trend of single-file web applications.
10 REM"_(C2SLFF4 (97 points by ingve)
10 REM"_(C2SLFF4 – Beej investigates a mysterious comment at the beginning of the 1980s BASIC game The Wizard’s Castle. The seemingly garbled string “_(C2SLFF4” turns out to be intentional, likely a checksum or protection mechanism in the Exidy Sorcerer platform. The article dives deep into emulators, POKE/PEEK commands, and memory addresses to decode it. It’s a fascinating piece of retro-computing archaeology that celebrates low-level programming ingenuity.
Neo Radar: A browser-based orbital mechanics engine with 41k real asteroids (9 points by daviazpen)
Neo Radar: A browser-based orbital mechanics engine with 41k real asteroids – This tool provides real-time simulation of near-Earth objects using JPL Horizons ephemeris data. It uses full Runge-Kutta 4 N-body dynamics for 47 high-fidelity objects and Kepler’s equation for 41,812 catalog asteroids, with all eight planets simulated. Users can toggle Jupiter/Saturn gravity perturbations and see live close approaches. It’s a showcase of how modern browser tech can deliver high-precision physics for astronomy.
Introduction to Formal Verification with Lean Part 1 (173 points by badcryptobitch)
Introduction to Formal Verification with Lean Part 1 – This tutorial teaches how to use the Lean proof assistant to formally verify cryptographic protocols, starting with the One-Time Pad. It walks through basic Lean syntax and then proves the OTP’s perfect secrecy using definitions from Boneh and Shoup. The target audience is cryptographic engineers new to formal methods. The article signals growing interest in machine-checked proofs for security-critical systems.
I Am Buiding BorgIOS to de-shitify the Internet (7 points by BorgIOS)
I Am Building BorgIOS to de-shitify the Internet – BorgIOS is an experimental, self-organizing, self-healing, distributed network that treats a USB stick as identity and the network as a computer. It aims to replace the current “crap” internet with a decentralized alternative. The project is in early development with disclaimers about bugs and incomplete features. It borrows Borg lore (“Resistance is futile”) and mixes LLM service nodes with blockchain-like concepts.
Drake Anthony Recreates the Mechanical Bulb First Seen in 1675 – TechEBlog (31 points by rbanffy)
Drake Anthony Recreates the Mechanical Bulb First Seen in 1675 – The article describes a recreation of “barometric light,” a phenomenon where shaking a mercury barometer produces a visible glow in the glass tube. The modern version uses a glass flask and mercury, requiring no batteries or wiring. It’s a hands-on physics project that connects 17th-century observation with modern maker culture. The piece also promotes a commercial flashlight, but the core is a fascinating DIY science experiment.
Formal verification is moving into the AI/ML mainstream.
The Lean tutorial (article 8) is part of a broader push to use proof assistants for verifying code correctness, especially in cryptography and AI safety. As AI systems become more critical, machine-checked proofs offer a way to guarantee properties like fairness, robustness, or security. Expect more tooling that bridges Lean/Coq with ML pipelines, especially for model certification.
The debate over AI-generated content and human meaning is intensifying.
Article 1’s philosophical stance against automation echoes widespread concerns about LLMs replacing creative work. This isn’t just a niche opinion – it reflects a growing distrust of “soulless” AI output. For AI/ML developers, this implies a need to design systems that augment rather than replace human effort, and to consider ethical frameworks around attribution and authenticity.
Database performance remains a critical bottleneck for AI applications.
The Postgres survival guide (article 3) highlights that even with AI-assisted coding, scaling databases is a hard, human-driven skill. Many ML systems rely on massive data retrieval and real-time inference, making database tuning (indexing, query planning, ORM abstraction) a key engineering challenge. The reference to Claude writing queries suggests AI tools are used, but they can obscure deeper understanding – a caution for production systems.
Physics simulation tools are converging with ML for real-time prediction.
Neo Radar (article 7) demonstrates high-fidelity orbital mechanics running in a browser. This is directly relevant to ML areas like trajectory prediction, reinforcement learning in physics environments, and neural ODEs. The use of RK4 integration and Kepler solvers shows that careful numerical methods still outperform pure ML for many tasks – but hybrid approaches (physics-informed neural networks) are likely to merge on this front.
Retro computing and low-level hacking persist as a counterbalance to high-level AI abstraction.
Article 6’s deep dive into a 1980s BASIC comment with POKE/PEEK shows that understanding hardware and memory remains valuable. As AI coding assistants handle more boilerplate, there’s a parallel appreciation for the craft of bare-metal programming. This suggests that AI/ML education should still include foundational computing concepts, not just high-level frameworks.
Decentralized and self-organizing networks (like BorgIOS) hint at future AI infrastructure.
Article 9’s vision of a USB-stick identity and peer-to-peer network resonates with trends in federated learning, decentralized AI agents, and edge computing. Although speculative, such projects indicate a desire to move away from centralized cloud dependencies. For AI/ML, this could mean more privacy-preserving training and inference across distributed nodes – but practical hurdles (trust, latency, coordination) remain large.
The maker/hacker ethos continues to produce novel tools that challenge AI’s role in creativity.
Article 10’s recreation of a 1675 barometric light is a pure physics hack, free of any AI component. Yet its popularity on HN (score 31) underscores a persistent appetite for hands-on, non-digital creation. For the AI/ML community, this is a reminder that not every problem needs a machine-learning solution – and that the most compelling innovations often come from understanding underlying physics, materials, and human curiosity.
Analysis generated by deepseek-reasoner