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We continue our journey through the world of CAPTCHAs (Fantastic CAPTCHAs and Where to Find Them, as well as Methods to Combat Them), and today we encounter yet another “tough nut” in the CAPTCHA universe – FunCaptcha (Arkose Labs).

FunCaptcha is a type of CAPTCHA developed by Arkose Labs that offers users small puzzles instead of the usual tasks like recognizing distorted text or selecting images containing buses. In traditional CAPTCHAs (e.g., reCAPTCHA), verification often relies on recognizing distorted characters or simple images. Arkose Labs took a different route: their “entertaining” CAPTCHAs feature interactive challenges with 3D objects, logic puzzles, and audio questions. This approach is intended to be user-friendly for humans while complicating life for bots.

Typical FunCaptcha challenges include:

This article is based on the experience of developing the memsafe library, which, using the Clang plugin, adds safe memory management and invalidation control of reference data types to C++ during source code compilation.

When creating an app or any other software product for children, one of the hardest parts of the process is conducting user research correctly. Although working with kids might seem fun and entertaining, it takes certain skills to get them engaged in testing your product and voicing their opinion so you could gather all the necessary information. It’s important to understand that mentally kids function differently than adults, so working with a young target audience requires a different approach. Treating children like adults in the UX research process can lead to serious mistakes: they might not get a proper understanding of your product and you might end up getting wrong results, only wasting your time and budget. In order to avoid that, we’ve collected a few tips below that might help you communicate with kids more effectively for a productive and fruitful research session.

Imagine a familiar situation: it’s Monday morning, tasks are piling up, and you need to quickly spin up a new service using Postgres Pro. Or maybe you’ve just upgraded your database server over the weekend — added more CPUs, more RAM.

Here’s how to get your database tuned and ready to make the most of the new hardware and workload, without wasting time.

DBAs often struggle to identify the most resource-hungry processes that degrade system performance. Back in 2017, DBA — and now Postgres Professional engineer — Andrey Zubkov faced the same challenge. This led him to develop pg_profile for PostgreSQL, which has since evolved into pgpro_pwr.

In this article, we’ll dive into strategic database monitoring and show you how to pinpoint bottlenecks in your databases using our tools.

We continue to follow the news about PostgreSQL 18. The January CommitFest brings in some notable improvements to monitoring, as well as other new features.

You can find previous reviews of PostgreSQL 18 CommitFests here: 2024-07, 2024-09, 2024-11.

Hi, my name is Ilia. I founded Perfect Wiki — a SaaS product for creating internal company knowledge bases that works directly within Microsoft Teams. We created a simple and convenient tool for storing, editing, and sharing knowledge within companies. It all started with the idea to resolve one specific pain point: the built-in Wiki in Microsoft Teams offered was inconvenient, and there was no worthy alternatives with full integration to the platform.

In this article, I want to share how the idea came about, the mistakes I made, how I found my first customers, and how I gradually grew to a steady income of $250,000 a year over five years. All of this — without investors, a 20-person team, or a “Series A” round.

We at Verilog Meetup constructed an exam/interview problem that has an interesting property: if a student tries to figure out a solution by thinking by himself, he usually succeeds; however if he dumps the problem on ChatGPT, the solution fails (does not pass the automated test), and the student goes into a death spiral of futility, kicking ChatGPT to get the solution right.

There is nothing weird about the problem, we do this in the industry all the time:

In this tutorial, I’ll explain in simple terms what AI, AI agents, and workflows are, and then I’ll walk you through building your very first AI agent in Python using Google’s Agent Development Kit (ADK). By the end, you’ll understand the differences between these concepts and have a working content-assistant agent you can run from your terminal or a web interface.

It’s Never Too Late: My Start into DevOps

Summary

Learn about the challenges, growth, and lessons gained — from juggling work, studies, and a pet project to achieving a dream.

According to Gartner, natural language queries will replace SQL as early as 2026. 

While Gartner's prediction may be optimistic, the shift toward natural language interfaces for databases is inevitable. The timeline may vary, but the transition itself is a certainty.

For people familiar with the term DPI (Deep Packet Inspection), it often carries an unpleasant association: blocking, regulators, censorship, tightening controls. In reality, DPI is simply the name of a technology whose essence lies in the deep analysis of network traffic. Deep traffic analysis involves identifying protocols, extracting the most significant fields and metadata, classifying internet services, and analyzing the nature of network flows. I will explain how such solutions work in this article.

We all strive to build better software, and to do it faster. I believe Test-driven Development offers us a path towards this goal. Still struggling to efficiently utilize this approach? Then I invite you to discuss my tips and tricks to unlock the benefits of TDD!

One could write, “Experienced developers working on parsing and automation often face the need to bypass modern CAPTCHAs.” But that’s too boring… I’d rather start like this—continuing to explore the amusing world of CAPTCHAs, I finally stumbled upon the Chinese variant of protection: the GeeTest CAPTCHA. Let’s break down what this beast is, where it dwells, and why you should (or shouldn’t) fear it… You’ll understand as we go!

GeeTest is one of the advanced anti-bot systems combining user puzzles with behavioral analysis. I decided to take a close look at recognizing the GeeTest CAPTCHA under real-world conditions and figure out how to bypass GeeTest with various methods. But first—a classic introduction (which, by the way, may be more interesting than the practical part of the article, since bypassing the GeeTest CAPTCHA is already a non-trivial task for many readers).

Hi to everyone!

I'm new here. Someone told me that Habr is like russian reddit for developers (and maybe not). And I'm here today to share my story and get opinions from you, part of this community.

In August 2024 I visited Moscow, and got Russian starter pack, even if foregneir :-)
Will be useful later because I'm moving here, Русский язык coming soon, извините!

So let's start with getting a new bank account, make a new mobile number and start to register to some essential service platforms like Metro, Gorod, ВВ, Perekrostak and Yandex for delivery and taxis. And in every service I found something strange. A certain "Ivan" (I've changed the name for privacy) is present in all my accounts where I try to register.
That's it! The phone number that my bank gave me was just.... recyled! So I could start to get personal data through all these existing account on this new phone number of mine but the most shocking thing occured today!

Alarm on 9:00, I woke up and I got a message by Yandex:

The whimsical image of a chess knight in profile among the stars is perhaps the most recognizable among deep space objects. It can be said that the Horsehead Nebula tops the recognition rankings among nebulae and galaxies. Perhaps the Andromeda and Orion Nebulae resonate more with the general public, but only specialists and advanced amateurs know what they look like. Even among them, there are often cases when the famous Andromeda Galaxy is confused with another galaxy, even by experienced popularizers of astronomy. The Orion Nebula, too, can look different in pictures taken with various filters. Yet, the profile of the chess knight allows every inhabitant of Earth to recognize that in front of them is the one-of-a-kind and completely unique Horsehead Nebula.

Let's begin by noting that when we talk about the Horsehead Nebula, we refer to two fundamentally different formations in this region of our Galaxy. Only together do they create this memorable visual image. Moreover, what we see—the glowing diffuse background—is not the Horsehead Nebula. It is a dark silhouette against a light background—a bizarrely shaped dust cloud opaque to the visible radiation of stars and nebulae. If there were no relatively bright emission nebula behind it, we might not even know about any dark gas-dust cosmic horse.

The background for the recognizable horse profile is created by the hydrogen nebula IC 434, discovered by William Herschel in the late 18th century. However, Herschel did not notice any amusing details in the outline of this nebula, although he was an excellent observer—much more keen-sighted and attentive than most of his followers. There are also objective reasons for this—telescopes in Herschel's era were imperfect, and their dark metal mirrors lost from 50% to 80% of the light that entered them.

The large but sparsely populated constellation Monoceros, barely visible to the naked eye, can take pride in hosting an extraordinary treasure: the Rosette Nebula. Monoceros is a relatively recent addition to the star map. Lacking bright stars, astronomers of the pre-telescope era deemed this region unworthy of a constellation. After all, how could a constellation exist without luminous stars? A few 4th-magnitude stars hardly suffice to form a recognizable figure. Consequently, old star maps depicted nothing within the Winter Triangle — formed by Betelgeuse, Sirius, and Procyon (between the constellations Orion, Canis Major, and Canis Minor. Only with the telescope’s invention did it become clear that this region contained notable objects, necessitating a name. Johannes Hevelius, creator of a stunning star atlas, coined the name in the early 18th century. Thus, astronomers gradually accepted a mythical, horse-like beast with a sharp horn — located where the third eye might be — among the winter constellations.

The term "Carina Nebula" is sometimes translated as "Nebula of Carina," evoking the image of a beautiful female name. However, this is a misinterpretation. "Carina" is Latin for "keel," referring to the keel of a ship—not just any ship, but the Argo, depicted on ancient star maps. Over time, the Argo constellation was divided into several modern constellations: Carina, Puppis, Vela, and Pyxis (Compass). The stars of the Argo are invisible from mid-northern latitudes. Even in the best seasons (winter and spring), Carina, Puppis, and Vela remain below the horizon. They can be observed from the northern tropics and farther south. However, in ancient times, when Greek astronomers imagined the Argo in the sky, the Earth's rotational axis was positioned differently due to precession. This allowed the Argo to be visible from Mediterranean shores. Precession, a gradual shift in the Earth's axis, completes a full cycle every 26,000 years. Over three millennia, the stars of the Argo gradually disappeared from the northern sky.