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Hey everyone! I'm super excited to share something cool I've been playing around with: Google AI Studio. It's like a playground where you can build stuff with Google's AI models. So, if you're curious and want to dip your toes into the world of AI, follow along! I'll show you the basics.

Author: Sergey Lukyanchikov, C-NLTX/Open-Source

Disclaimer: The views expressed in this document reflect the author's subjective perspective on the current and potential capabilities of jBPM.

This text presents jBPM as a platform for orchestrating external AI-centric environments, such as Python, used for designing and running AI solutions. We will provide an overview of jBPM’s most relevant functionalities for AI orchestration and walk you through a practical example that demonstrates its effectiveness as an AI orchestration platform:

How did engineers in the past manage to measure electrical power without modern microchips and DSPs? This article explores the Energomera CE6806P, a device created in 2006 for verifying electricity meters, yet built using 1980s-era technology.

We’ll take a closer look at its design, principles of operation, and how discrete-analog solutions were used to achieve high accuracy. The Energomera is a fascinating example of engineering and ingenuity, giving us a unique perspective on the evolution of electrical measurement devices.

While pg_probackup 3 is still in the works and not yet available to the public, let’s dive into what’s new under the hood. There’s a lot to unpack — from a completely reimagined application architecture to long-awaited features and seamless integration with other tools. 

A lot of people around me spend time trading on the stock market. Some trade crypto, some trade stocks, others trade currencies. Some call themselves investors, others call themselves traders. I often see random passersby in various cities and countries checking their trading terminals on their phones or laptops. And at night I sometimes write analytical or backtesting software—well, I did up until recently. All these people share a common faith and a set of misconceptions about the market.

In this article, I'll take you through everything you need to know about Hugging Face—what it is, how to use it, and why it's a game-changer in the ever-evolving landscape of artificial intelligence. Whether you're a seasoned data scientist or an enthusiastic beginner eager to dive into AI, the insights shared here will equip you with the knowledge to Hugging Face's full potential.

Lately, tons of new Telegram channels, bots, and mini-apps in English have been popping up. Just a year ago, this trend was barely starting — most English-speaking users couldn’t even tell the difference between a Telegram channel and a group.

And now? They’re all in, growing their channels, bots, and mini-apps like crazy. Telegram is turning into a massive platform.

Often at work, I encounter services that provide offerings such as resident proxies. Yet, I have never delved deeply into the topic. I have always simply consumed the product “as is,” as some lazy authors like to say.

I have a general understanding of how this type of service works at a layman’s level, and I became interested in exploring the topic more deeply and attempting to share the conclusions I reached through a deeper understanding of what resident proxies are. Let’s see what comes out of it. No recommendations here—just the subjective, evaluative opinion of yet another “specialist.”

Proxy servers are intermediaries between your device and the internet, allowing you to hide your real IP address and alter the appearance of your connection. Think of it as a white camouflage coat in snowy weather, if we speak in very simplistic terms. Let’s start from that—options for camouflage. However, comparing with camouflage coats would be rather dull; instead, let’s recall animals and insects that use camouflage and try to draw a parallel. In fact, I’ve already done so.

For many years, the PostgreSQL community was skeptical about using this database management system (DBMS) for high-transaction environments. While PostgreSQL worked well for lab tests, mid-tier web applications, and smaller backend systems, it was believed that for heavy transactional loads, you’d need an expensive DBMS designed specifically for such purposes. As a result, PostgreSQL wasn’t particularly developed in that direction, leaving a range of issues unanswered.

However, the reality has turned out differently. More and more of our clients are encountering problems that stem from this mindset. For example, in the global PostgreSQL community, it’s considered that 64 cores is the maximum size of a server where PostgreSQL can run effectively. But we’re now seeing that this is becoming a minimum typical configuration. One particular bottleneck that has emerged is the transaction counter, and this is a far more interesting issue. So, let’s dive into what the problem is, how we solved it, and what the international community thinks about it.

Have you ever heard of Gemini Code Assist? It’s an AI-powered coding assistant from Google that helps with writing, completing, and debugging code. The best part? It’s now free for individuals, freelancers, and students!

In this article, I’ll show you how to set up and use Gemini Code Assist inside VS Code. Whether you’re new to coding or an experienced developer, this tool can save you time and make coding easier. Let’s get started!

Anti-detect browsers emerged as a response to the spread of browser fingerprinting technologies – the covert identification of users based on a combination of their device’s parameters and environment. Modern websites, besides using cookies, track IP addresses, geolocation, and dozens of browser characteristics (such as Canvas, WebGL, the list of fonts, User-Agent, etc.) to distinguish and link visitors. As a result, even when in incognito mode or after changing one’s IP, a user can be detected by their “digital fingerprint” – a unique set of properties of their browser.

In fact, when I first started my journey in these internet realms, my expertise in digital security was evolving—and continues to grow—and I eventually came to understand browser fingerprints. At first, I believed cookies—collected by those pesky search engines that tracked what I viewed—were to blame, then I learned about browser fingerprints and long denied that I needed to learn to work with and understand them. Really, just when you finally figure out proxies, learn how to change and preserve cookies, here comes a new twist. Moreover, it turns out that fingerprints are also sold, and the price is not exactly low. In short, money is made on everything! But that’s beside the point now!

An anti-detect browser is a modified browser (often based on Chromium or Firefox) that substitutes or masks these properties (fingerprints), preventing websites from unequivocally identifying the user and detecting multi-accounting.

Proxy servers have long become an integral part of the modern network. They are used to enhance anonymity, bypass blocks, balance loads, and control traffic. However, not everyone understands that there is a fundamental difference between HTTP(S) proxies and SOCKS proxies. In this article, I will attempt to examine in detail the technical aspects of both types, review their advantages and limitations, and provide examples of configuration and usage – though this part is more of an elective (optional, if you will, but I really feel like including it).

This article explores the concept of equivalence classes from the perspective of mathematical analysis and their application in QA testing. The author explains how properly defining equivalence classes helps optimize test design, reducing the number of test cases while maintaining thorough verification.

Using the example of currency conversion from rubles to euros, the article demonstrates how to construct equivalence classes, verify their compliance with mathematical properties (reflexivity, symmetry, transitivity), and identify errors in data partitioning.

This article is useful for QA engineers, developers, and analysts who want to gain a deeper understanding of logical testing principles and improve the efficiency of their test strategies.

There have been many discussions about which programming language is better in terms of security and correctness of source code (by "correctness and security" we mean the absence of various errors in the program that manifest themselves at the stage of its execution and lead to the issuance of an incorrect result or unexpected behavior). And some programming languages, such as SPARK or OCaml, were even specially developed to facilitate the proof of program correctness.

Is it possible to write programs without errors at all?