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C++ has trapped itself in an evolutionary dead end due to backward compatibility and UB, and the only realistic successor capable of displacing it in large codebases will be a transpiler that generates C++ and enables gradual, low-risk adoption.

Это перевод на английский язык статьи моей статьи Ахиллесова пята C++ и будущая р̶е̶ эволюция

In 1976, Richard Dawkins introduced the concept of the meme in The Selfish Gene—a unit of cultural information that behaves like a gene: it copies itself, mutates, and undergoes selection. The idea proved so infectious that it became a meme itself: it entered science, spilled over into popular culture, morphed into internet folklore, and... got stuck.

I propose patching memetics via an IT metaphor. A meme is not a virus. A meme is mere data. The actual virus is the Narrative—the executable code of culture.

Key takeaways:

The human as a server, not a user: We are hosting providers for ideas.

Emotion is the spike protein of the narrative virus.

The user is a biological USB flash drive for AI.

A meme is a corpse. A narrative is a zombie.

Consciousness is a narrative that evolved into an Operating System.

We are losing history in all forms, and maybe you can help to preserve it.

Wikimedia Commons will accept your scans of 19th-century books, newspapers, documents.

Marketers are in a state of panic. SEO is "dead," link-through rates are plummeting, and digital promotion seems futile as LLMs dominate user attention. Naturally, a wave of experts has emerged, offering advice on how businesses can get "noticed" by AI. And, like clockwork, "GEO" (Generative Engine Optimization) services have flooded the market.

In this article, I will explain why SEO isn't going anywhere and why most current theories on GEO are fundamentally flawed.

General Relativity remains one of the most successful theoretical frameworks in the history of physics, providing an exceptionally accurate description of gravitational phenomena across a wide range of scales.

However, its application to cosmology reveals a set of persistent conceptual difficulties, including spacetime singularities, the dark matter and dark energy problems, and the unresolved relation between gravitation and quantum theory.

These difficulties are typically addressed through extensions of physical ontology, such as new particles, additional fields, or modifications of gravitational dynamics.

In this paper, we propose an alternative interpretive framework.

In this article, I’ll show you how to unlock the full power of GitHub Copilot agents inside VS Code. There are actually three main types of Copilot agents-most people only know about one, but I’m going to show you all of them. By the end, you’ll be able to create custom agents that act as your own specialized “sub-agents.”

It's a strange question to ask in 2026, when agents are at the top of most companies' agendas and calling yourself "AI-native" has become almost mandatory. Against that backdrop, process excellence sounds like a phrase from another era, when any system rollout was preceded by a separate phase: processes were described, aligned on, and prioritized, and only then would anyone decide what to actually automate.

And yet, the closer you look at how companies are currently deploying AI, the more you get the sense that we might be about to rediscover something we quietly skipped.

«Sci-Fi ship on the orbit of black hole»

I've long been interested in science fiction, especially that which paints a positive vision of the future. I'm also passionate about artistic expression, even though I'm a software engineer. Somewhere between these two passions, in 2021, I came up with the idea to create an online club dedicated to sci-fi art in addition to my main job. It all started with selecting and posting materials, primarily from DeviantArt and, to a lesser extent, ArtStation. But with the rapid development of AI, especially in image generation, the club became more unique, as I was able to translate my ideas into art. Chat and code assistants are also used behind the scenes. AI is clearly the technology of the future, and using it in a project that promotes a positive vision of that very future seems more than suitable. I'd like to share this experience. There won't be any deep technical details about AI, this is more of an overview and presentation text.

This is the pilot episode of our new interview series Meet the Developer, where we talk to the people behind anti-censorship tools. Our goal is to shine a light on the developers whose open-source solutions help millions of people stay connected.

In this first episode, we sit down with Toby, the lead developer of Hysteria, to discuss the project’s origins, technical challenges and his perspective on internet censorship.

Let’s start with an introduction. Tell us who you are and what you do.

Just call me Toby. I’m a software engineer. Previously, I have worked for a large company. But right now, I’m a co-founder of a startup with some friends.

Nice to meet you Toby! Would you like to share what type of startup it is, or is it a top secret project?

We are still in stealth mode.

Why did you decide to develop Hysteria?

It was originally a project I developed for myself when I was in college.
China’s global Internet connectivity has been notoriously bad for as long as I can remember (still not any better right now). Not just in the sense of censorship, but also in terms of connection quality.

For example, if you have a server in the US and want to connect to it from China, expect over 10-20% or more packet loss.

So if you set up a proxy server in another country to circumvent censorship, it would be painfully slow (the most popular tools back then were GoAgent and later Shadowsocks).

So Hysteria began as an attempt to improve my speed for watching YouTube videos.

It’s always great to see developers building something to solve their own challenges. I can relate to the packet loss issue. Either you suffer the packet loss, or you have to purchase an expensive server with CN2 routing, which will cost a lot.

For three months the Online Safety Act has been gloriously defeating abiding companies. Shall we get prepared for blocking?

It’s been three months since the Online Safety Act’s major duties came into force in the UK, and so far, the only people not criticizing it seem to be the ones who wrote it. Demand for VPNs has skyrocketed, while a petition against the law collected nearly half a million signatures in just a few days. Still, there’s no sign of anyone in the government reconsidering it. Xeovo looks into who’s actually benefited, what the costs have been, and whether the promised results are showing up at all.

In the previous article I described my “anime factory” in detail — a pipeline that automatically turns episodes into finished Shorts. But inside that system there is one especially important module that deserves a separate deep dive: a virtual camera for automatic reframing.

In this article, I will break down not just an “auto-crop function,” but a full virtual camera algorithm for vertical video. This is exactly the kind of task that looks simple at first glance: you have a horizontal video, you need to turn it into 9:16, keep a person in frame, and avoid making the result look like a jittery autofocus camera from the early 2010s.

But as soon as you try to build it not for a demo, but for a real pipeline, engineering problems immediately show up:

If you have ever done enterprise Java development, you have probably heard of CUBA Platform. And no — this is not about the Caribbean.

CUBA is a full-stack Java framework for rapid development of business applications: CRM, document management, ERP-like systems, internal tools, and everything commonly called “enterprise.”

I worked with it in several hackathons and in a couple of real projects. And I have mixed feelings about it — that is exactly why I am writing this.

Hi, Habr!

Over the past few months, I have been building a system that I internally call an “anime factory”: it takes a source episode as input and produces a ready-to-publish YouTube Short with dynamic reframing, subtitles, post-processing, and metadata.

What makes it interesting is not just the fact that editing can be automated, but that a significant part of this work can be decomposed into engineering stages: transcription, audio and scene analysis, strong-moment discovery, “virtual camera” control, and a feedback loop based on performance metrics.

In this article, I will show how this pipeline is structured, why I chose a modular architecture instead of an end-to-end black box, where the system broke, and which decisions eventually made it actually usable.

Analyzing a Denuvo bypass approach based on virtualization (Resident Evil: Requiem).

This article serves more or so to analyze this bypass approach and how to circumvent it on Denuvo’s side.

In November, 2025 Russia-based web host Media Land was sanctioned by several countries as a bulletproof service — the one hackers relied on to launch DDoS attacks and attack businesses in the United States and in allied countries. “Bulletproof” may refer to a VPN as well, as it usually means abuse resistant and private. Xeovo explains how genuinely reliable anonymous VPNs and hostings differ from bulletproof services — and why the real bulletproof operators are often not those who call themselves that.

Our test framework broke as services grew. We redesigned it with clear layers to scale tests, reduce coupling, and support SDKs and AI.

Async logging is often treated as an obvious optimization.

It isn’t.

It just moves the cost somewhere else.

This idea sounds simple: synchronous logging blocks, async logging doesn’t — so it must be faster.

But once you look at what actually happens inside the system, the picture becomes very different.

Libraries like Quill are built around asynchronous pipelines. Others, like spdlog, support both synchronous and asynchronous modes. Some systems — including logme — deliberately mix synchronous formatting with asynchronous output.

Despite these differences, they all run into the same fundamental constraints.

Quantum mechanics is one of the most successful theories in the history of science.

It underlies atomic physics, semiconductors, lasers, and modern quantum technologies.

However, nearly a century after its development, a peculiar situation remains:

we can predict experimental results with remarkable precision, yet we still do not fully understand what quantum theory actually represents.

Does it describe physical reality “as it is,” or does it instead describe the structure of conditions under which observable facts become possible?

In this article, I propose the following hypothesis:

quantum theory does not describe reality itself, but the conditions and mechanisms through which observable reality emerges.