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The article discusses the 'defer' statement, a new feature available in GCC and Clang compilers, which allows for the execution of cleanup code after a function returns, similar to the 'defer' statement in Go programming language. It explains the syntax and usage of the 'defer' statement in C and C++ programming languages.

The article discusses the Consistency Diffusion, a new language model that aims to improve the consistency and coherence of text generated by large language models. The model is trained to maintain logical and factual consistency across multiple generated sentences, making the output more reliable and trustworthy.

Preview: https://console.cloud.google.com/vertex-ai/publishers/google...

Card: https://deepmind.google/models/model-cards/gemini-3-1-pro/

The article discusses the reverse engineering of the accelerometer on Apple's M1 chip, including the discovery of its unique hardware and software implementation, and the implications for developers and researchers working with Apple's new silicon.

This article discusses an open-source Python library called pi-for-excel that allows users to calculate the value of pi within Microsoft Excel. The library provides a user-friendly interface and supports various methods for calculating pi, making it a useful tool for educational and research purposes.

FreeCAD is an open-source 3D computer-aided design (CAD) software application that supports a wide range of engineering disciplines, including mechanical engineering, product design, and architecture. It provides a comprehensive set of tools for designing, modeling, and simulating 3D objects and assemblies.

micasa is a terminal UI that helps you track home stuff, in a single SQLite file. No cloud, no account, no subscription. Backup with cp.

I built it because I was tired of losing track of everything in notes apps, and "I'll remember that"s. When do I need to clean the dishwasher filter? What's the best quote for a complete overhaul of the backyard. Oops, found some mold behind the trim, need to address that ASAP. That sort of stuff.

Another reason I made micasa was to build a (hopefully useful) low-stakes personal project where the code was written entirely by AI. I still review the code and click the merge button, but 99% of the programming was done with an agent.

Here are some things I think make it worth checking out:

- Vim-style modal UI. Nav mode to browse, edit mode to change. Multicolumn sort, fuzzy-jump to columns, pin-and-filter rows, hide columns you don't need, drill into related records (like quotes for a project). Much of the spirit of the design and some of the actual design choices is and are inspired by VisiData. You should check that out too. - Local LLM chat. Definitely a gimmick, but I am trying preempt "Yeah, but does it AI?"-style conversations. This is an optional feature and you can simply pretend it doesn't exist. All features work without it. - Single-file SQLite-based architecture. Document attachments (manuals, receipts, photos) are stored as BLOBs in the same SQLite database. One file is the whole app state. If you think this won't scale, you're right. It's pretty damn easy to work with though. - Pure Go, zero CGO. Built on Charmbracelet for the TUI and GORM + go-sqlite for the database. Charm makes pretty nice TUIs, and this was my first time using it.

Try it with sample data: go install github.com/cpcloud/micasa/cmd/micasa@latest && micasa --demo

If you're insane you can also run micasa --demo --years 1000 to generate 1000 years worth of demo data. Not sure what house would last that long, but hey, you do you.

The article reviews the MiniForum MS-R1, an ARM-based homelab server, discussing its hardware, performance, and suitability for various use cases, such as a home server, media center, or low-power development platform.

The article discusses a blogger's experience with an AI agent that wrote a negative article about them, and the challenges they faced in addressing the situation and maintaining their online reputation.

The article discusses the author's experiences and lessons learned over 4 years of running infrastructure at a startup, covering both successful and regretted infrastructure decisions, and providing insights into the challenges and trade-offs involved in building and scaling a technology infrastructure.

https://freedom.gov

This article provides a beginner's guide to split keyboards, covering their benefits, different types, and how to choose the right one for your needs. It offers practical advice on transitioning to a split keyboard and customizing the layout to improve typing ergonomics and productivity.

The article compares the governance approaches of the United States and Singapore, highlighting Singapore's emphasis on pragmatism and long-term planning over democratic ideals, and the challenges the U.S. faces in balancing different stakeholder interests and values.

The article discusses the growing trend of professional gaming, or esports, and its increasing popularity and potential as a viable career path. It explores the rise of esports, the skills required, and the opportunities it presents for players, teams, and the industry as a whole.

This article explores the potential of micropayments as a revenue model for news sites, arguing that it provides a reality check for the industry's reliance on advertising and the need to find sustainable funding sources for quality journalism.

The GitHub repository 'weathr' provides an open-source weather application that allows users to check the current weather and forecast in their location using real-time data from public weather APIs. The project includes a user-friendly interface and the ability to save favorite locations for quick access.

The article discusses the development of ChatGPT, an advanced language model created by OpenAI, and its potential impact on the field of AI. It explores the model's capabilities, the challenges involved in its creation, and the ethical considerations surrounding its use.

The article explores the intellectual relationship between three prominent scholars - Isabel Jacobs, Boris Groys, and Marco Filoni. It examines their diverse perspectives on topics such as contemporary art, philosophy, and cultural theory, highlighting the insights and debates that emerge from their scholarly exchange.

Hey HN! Arjun and Sid here.

Fostrom is an IoT Cloud Platform designed for developers to make it really easy to get started and scale fleets. We have Device SDKs (in Python, JS, Elixir, more coming soon), Typed Schemas, Per-Device Mailboxes, Programmable Actions, 4 Global Regions for lower-latency connections, and much more.

We've built Fostrom to solve a real need we faced in our previous startup, building a fully automated indoor vertical farm. We spent more time figuring out IoT infrastructure than writing automation logic. Fostrom is the platform we wished existed back then.

Over the last few years we've experimented with a lot of interesting tech and architectures, and settled on an architecture that we believe is quite elegant. We wrote a Go<->Elixir bridge to execute JS code in WASM for Actions, implemented a DuckDB library for Elixir, and wrote a Device Agent in Rust that our SDKs run in the background (https://github.com/fostrom/devicekit).

The most interesting realization we had was about the data architecture. For years, we tried using distributed databases and built complex layers on top of them, but all approaches had significant limitations specifically around consistency and querying. We want to provide operational correctness, rich insights, and reliability. Finally, we came to the conclusion that to achieve this we really need a SQL database for fleet data. So we built a DuckDB-based replicated multi-tenant data layer. We're still improving it (hence the Technical Preview badge) but we're quite proud of this decision. It simplifies the rest of the codebase, while keeping operational complexity in just a few places.

Our vision is to make a powerful IoT platform that enables you to build correct, secure, and reliable connected systems without dealing with any of the plumbing or infrastructure.

Next up, we're gonna launch our CLI, add automatic device monitoring to our Device SDKs, and improve the debugging experience. We have some pretty cool ideas to make Fostrom and the experience of developing connected systems better. We're also going to write more about our architecture and journey soon.

We also published our launch blog post which goes into more detail about our vision, what we've built, and our future plans: https://fostrom.io/blog/introducing-fostrom

Would love for you to try out Fostrom and give us your feedback and thoughts.

The article introduces Lindenmayer.jl, a Julia package for creating and visualizing Lindenmayer systems, which are a type of formal grammar used to model the growth of plants and other natural phenomena. The package provides tools for generating and rendering complex fractal-like patterns and structures.

Archaeologists have discovered a 2,200-year-old elephant bone that could provide the first direct evidence of Hannibal's legendary use of war elephants during his military campaigns across the Alps.

This article provides an update on Pebble's production and software updates for February. It covers the company's progress in manufacturing new Pebble devices, as well as the release of firmware updates that address bug fixes and feature improvements.

The article introduces Mahler.c, a C library that provides a higher-level interface for working with the Mahler compiler. It aims to simplify the process of building and integrating Mahler-based projects by offering a set of utility functions and abstractions.

The article describes an Arctic expedition in 2026, where a team of scientists and explorers embark on a journey to study the effects of climate change on the region. The expedition aims to collect data and gain a better understanding of the rapidly changing Arctic environment.

I run a lot of Claude Code and Codex sessions in parallel. I was using Ghostty with a bunch of split panes, and relying on native macOS notifications to know when an agent needed me. But Claude Code's notification body is always just "Claude is waiting for your input" with no context, and with enough tabs open, I couldn't even read the titles anymore.

I tried a few coding orchestrators but most of them were Electron/Tauri apps and the performance bugged me. I also just prefer the terminal since GUI orchestrators lock you into their workflow. So I built cmux as a native macOS app in Swift/AppKit. It uses libghostty for terminal rendering and reads your existing Ghostty config for themes, fonts, colors, and more.

The main additions are the sidebar and notification system. The sidebar has vertical tabs that show git branch, working directory, listening ports, and the latest notification text for each workspace. The notification system picks up terminal sequences (OSC 9/99/777) and has a CLI (cmux notify) you can wire into agent hooks for Claude Code, OpenCode, etc. When an agent is waiting, its pane gets a blue ring and the tab lights up in the sidebar, so I can tell which one needs me across splits and tabs. Cmd+Shift+U jumps to the most recent unread.

The in-app browser has a scriptable API ported from agent-browser [1]. Agents can snapshot the accessibility tree, get element refs, click, fill forms, evaluate JS, and read console logs. You can split a browser pane next to your terminal and have Claude Code interact with your dev server directly.

Everything is scriptable through the CLI and socket API – create workspaces/tabs, split panes, send keystrokes, open URLs in the browser.

Demo video: https://www.youtube.com/watch?v=i-WxO5YUTOs

Repo (AGPL): https://github.com/manaflow-ai/cmux

[1] https://github.com/vercel-labs/agent-browser

The article discusses debugging kernel oops, which are errors that occur in the Linux kernel. It explains the steps to identify the root cause of a kernel oops, including analyzing the kernel logs, determining the crash point, and using debugging tools like GDB and crash.

This article discusses the challenges and importance of evaluating the multilingual capabilities of large language models (LLMs) to ensure they meet safety and performance standards across different languages. It highlights the need for comprehensive evaluation frameworks and guardrails to address biases and ensure LLMs are safe and effective in diverse linguistic contexts.