My feed

One of the most inspiring moments in microcontroller development is their first installation and launch within a local network. Yet, this very moment can turn into a living hell when the procedure has to be repeated dozens or hundreds of times. Deploying dozens of identical controllers simultaneously demands hours of monotonous configuration—time that any engineer would rather spend on more creative and useful tasks. To solve this problem, a lightweight open-source service codenamed "Esp monitor" was developed.

The Configuration Problem and Protocol Choice 

One of the most popular (and importantly, cheap—costing around $2) microcontrollers is the Wemos D1 Mini based on the ESP8266 chip. It is fast, reasonably reliable, and boasts a vast ecosystem of add-on modules. These are the exact controllers widely used in household appliances and DIY projects due to their massive potential for integration into sensors and home automation systems.

However, they are also among the most inconvenient to configure: by default, the only wireless interface "onboard" is Wi-Fi. This means connecting to a new wireless access point turns into another "dance with a tambourine".

It might seem that this task could be solved by classic port forwarding out of the local Wi-Fi network, but in most scenarios, this is a dead end: 

Imagine your heaviest SQL queries running in milliseconds. It sounds like science fiction, but with the pgpro_result_cache extension, it’s very real. In this article, we’ll look at how multi-second queries can be turned into lightning-fast cache hits.

On July 6, 2026, researchers at Anthropic published the results of a new study claiming to have discovered an analogue of the "global workspace" in Claude, dubbed J-space.

The research is highly fascinating and, I believe, reveals the future of neural networks much more deeply than it appears at first glance.

In this article, I will explore why the Global Workspace Theory (GWT) accurately describes the structure of this finding, yet remains silent on its main oddity: the fact that this workspace consists of "words" (or, more precisely, discrete signs). And I will explain why Lev Vygotsky answered this exact question a century ago.

Regular expressions have the ability to track the path and some reflection. We'll try to use these features to capture and colorize text parts and output them to the console using AutoHotkey.

Совершать невозможное и раздавать пинки здравому смыслу — в этом и состоит жизнь членов Гуррен-Дана! (C) Камина

This article enters into a technical debate with a 2015 article by Atakua, whose approaches I am attacking. Atakua explores 7 types of bytecode interpreters, but does so disrespectfully - the fastest turns out to be binary translation, which is essentially no longer a bytecode interpreter, but a form of Ahead-Of-Time compiler. This binary translation translates bytecode into machine code, which is a chain of calls to compiled service routines. The very same ones that are responsible for executing each opcode in a bytecode interpreter.

But Atakua didn't squeeze all the possible speed out of bytecode interpreters. So this article is a tutorial: how to write a bytecode interpreter that can outperform JIT/AOT compilation in speed. Interested? Read on!

A benchmark is included. There will be a bit of hardcore and not a single AI-generated image!

Hello, Habr!

Let me say right away - I'm not a network engineer or an IT professional in the classic sense. My knowledge of networking is limited to a CompTIA Network+ certification and curiosity. So if network specialists see that something could have been done better, I'd be happy to hear constructive comments.

Now for the story.

A couple of weeks ago, I moved into a new apartment. The first thing I did was set up the internet - I called the guys from the provider to install the equipment, and I went to check the small cabinet in the wall where all the wires come in. Inside, I found a bunch of stuff: telephone wires, something unclear, and several coaxial cables. One came from the hallway, the second was labeled "living room," the third "office," and the fourth was unlabeled.

Neural Networks for the Little Ones

Every time you say “Thank you” to a neural network, you launch a pipeline that multiplies hundreds of matrices with billions of elements, and burn as much electricity as an LED lamp in a few seconds.

This is the first article in a short series dedicated to networks for AI/ML clusters and HPC.

In this series, we’ll touch on the principles of model operation and training, parallelization, DMA and RDMA technologies, network topologies, InfiniBand and RoCE, and we’ll also philosophize on the topic of general and specialized solutions.

In this particular article, we’ll figure out what a neural network is, how it works, how it’s trained, and most importantly, why it needs hundreds of expensive GPU cards and some kind of special network.

The refrain of today’s story: there’s no magic in neural networks—it’s just a multitude of simple operations on numbers, performed on computers with special chips. There’s no magic in how they work, nor in the infrastructure they run on.

Have you ever hidden something inside a PNG? A basic way to securely hide something inside an image. And all in your favorite JavaScript!

Today I would like to share some information with you about a special, somewhat unique edition that exists in Windows 10 and Windows 11, released by Microsoft for the Chinese government sector. What is Windows Enterprise G, also known as Windows Enterprise Government China, how does it differ from other editions, and most importantly, how (and why) you can get it.

We're building a portable 12V 110 Ah LiFePo4 battery for camping and household needs, and also making 12V USB charger modules deliver their full power.

This Powerbank will be useful at home, in the car, in a tent, outdoors, on a boat, at the beach, and where roads and power lines don't reach.

I have been into car tourism for a long time. These are trips by car, with overnight stays and day stops far from civilization. The duration of such trips can be up to two weeks, during which we set up camp in the most beautiful and hard-to-reach places.

While the car is running, it naturally takes care of all electricity needs. Everything that needs to work and charge does. But when it's turned off, the power consumption required by the camp will drain the under-hood battery quite quickly...

A mind-blowing mix of 64/32-bit assembly and good old C++ awaits us. We will create our own implementation of... Fibers (fibers) without calling the Win API or dialing 911.

Wearable devices present a paradox: the band measures your heart rate, sleep, and activity, but the manufacturer doesn't provide a ready-made open API to integrate this data into third-party systems (like a home monitoring setup or a local database). The official Xiaomi Mi Fitness app shows beautiful graphs, but the data remains 'locked' within the mobile ecosystem.

The initial task was purely practical: to set up automatic collection of health data into a local SQLite database and display reports in a family Telegram bot. Since the band syncs with the app, which in turn syncs with the Xiaomi cloud, the data is guaranteed to be transmitted over the network. I needed to understand the format in which it's transmitted and how to retrieve it.

This article is a technical breakdown of the journey from analyzing network traffic and setting up trust for a custom CA to reverse-engineering Xiaomi's RC4 protocol, decrypting AES/CBC objects from FDS storage, and parsing the proprietary binary sleep format.

How to set up transparent synchronization of Obsidian notes between devices (Desktop, Android, iOS) via GitHub:

1. Without third-party applications (like iCloud, SyncThing, Termux, etc.)
2. For free
3. As a bonus—a backup: of both the notes themselves and their change history.

The result is a full-fledged replacement for Notion: structured notes with automatic synchronization between devices.

Hello, Habr!

In this article, I will share my experience of learning English and the things that worked and didn't work for me. The process of learning a language is very individual, and you can never claim that one method/scheme is the right one (although some articles on Habr directly say: this method is right, and that one is not).

Let's start with the background and reasons.

I am a mechanical engineer (my specialty is mechanical seals for rotating shafts). I started working in my field right after my bachelor's degree, while also finishing my master's. As soon as I started working, I tried to absorb as much theoretical knowledge in my specialty from academic sources as possible. I quickly realized that the last serious book in my specialty in Russian was written in 1978. And after more than 40 years, the technology has changed significantly, but there was no description of it in Russian. However, I found people on Reddit working in the States in my same industry. They recommended a lot of great literature to me. Of course, it was all in English and had no Russian translation.

I started my language learning journey in January 2022 from a near-zero level. In all my schools, English language teaching was not at the highest level, and at university, it was enough to memorize 30 sentences to get a decent grade on the exam.

Of course, before starting, I read many articles on Habr about how people learn languages. Some of them were amazing in their speed of mastering the material (something like from zero to fluent in 4 months). But one thing was constant – everyone had some kind of language learning plan.

Yesterday (November 27), Habr hosted an 'Author's Fireside Chat'.

It was very interesting, and one of the speaker's statements struck me. It was that AI can help write simple pieces of code but doesn't work with complex things. Thus, large language models are likened to a junior programmer.

I decided to write an article about it this morning, drawing on my knowledge and experience in computational mathematics (I used to do modeling in the past, and for the last few years, I've been teaching computational mathematics at MIPT). Let me know what you think.

I think this is the main myth of vibe-coding. It's exactly the opposite — AI is often good at writing quite complex things and retrieving important information that is difficult to find on your own. But it gets confused in the most elementary things. It's a reverse junior.

The problem is that this is a dangerous illusion, and I will now clearly explain why, and how it can be dangerous. Brew some coffee and get ready for a debunking that might save your millions, your career, or even human lives in the future.

The modern world is saturated with all kinds of information, and in our difficult times, it's important to be able to not only find it but also to save it. Many have probably noticed that on YouTube, besides the junk, cats, and other useless things (which we sometimes don't mind watching), there is a lot of useful material on a wide variety of topics. And sometimes it would be nice to save this material for the future, so as not to depend on the changing moods in the world.

In this article, I want to explain how you can download videos, audio (Part 1 of the article), playlists, and entire channels from YouTube (Part 2 of the article) without using a VPN and in pure Python. A quick disclaimer: we won't need a VPN, but we will create our own tool that will solve the "problem with outdated and worn-out equipment Google Global Cache" (you know what I mean). I think this tool will be especially relevant today, when for many Russians, YouTube barely works or doesn't work at all.

Everyone who has taken a linear algebra or physics course at university remembers this strange dualism. We were taught that vectors have TWO types of products. The first, scalar, takes two vectors and outputs a number. Geometrically, it's about projections and angles. The second, vector, also takes two vectors and... suddenly spits out a third vector, perpendicular to the first two. And this trick only works in 3D and 7D.

It always seemed like some kind of mathematical 'crutch'.

Why is it so complicated? Why two different products for different tasks? Why does one depend on the cosine and the other on the sine?

What if I told you that they really are 'crutches'? That there is a single, universal, and elegant geometric product, which includes both of these cases (and much more), and which is based on a single, crystal-clear idea. An idea that changes the way we look at the very essence of mathematics.

This article is an invitation to the world of Geometric Algebra. We are going to reinvent multiplication.

We all know this formula. .

This is perhaps the only piece of knowledge from school geometry that stays with a person for their entire life, even if they work as a barista or a copywriter.

But have you ever asked yourself the question: why squares specifically?
Why not cubes? Why not just the sum of the absolute values ?

If you ask a teacher, they will draw little squares on the sides of the triangle. If you ask a university professor, they will write down the definition of a scalar product.
And both of them, in essence, will deceive you. Or, to put it more mildly, they won't tell you the whole truth.

Today, we will unpack this 'black box' and see that the Pythagorean theorem is not about triangles at all. And it should be proven in a completely different way than we were taught.

The school curriculum doesn't provide an answer. Moreover, the history of teaching the Pythagorean theorem is a story of how living, visual geometry was turned into dry, dead algebra. We were led further and further away from understanding the essence and towards abstraction.

Today, we will analyze this path of degradation and show a proof that will bring you back to reality. Spoiler: the Pythagorean theorem is not about triangles. It's about mirrors.

Get ready to have all your preconceptions shattered!

I'm an engineer who has 'recovered' from a knife sharpening obsession. I'll share the least obvious elements of the theory and the simplest technique for keeping a kitchen knife sharp in just one minute a week.