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Hi! My name is Slava. I am currently working as a leading Product and Senior Project Manager at Uzum Bank. One of the leading digital banks in Uzbekistan.

We are growing fast. Really fast. Speaking in numbers, our interest income has increased x10 over the past year (!).

And, as in any similar projects with rapid growth, we constantly lack qualified personnel. So I and my colleagues always have a lot of work to do.

I have two teams with completely different products, and I also manage some projects as a project manager. And I have my own small business – an online tea and coffee shop. And in conclusion, I am the father of two small children)

So, I hope this makes it clear to you that I have faced all the problems, such as working at night, lack of sleep, working in a noisy environment, calls with crying children in the background, calls during breakfast on the wheels, when I take a child to kindergarten (never do that!) etc. and so on and so forth XD

You can ask me: how do you manage to do everything?
The answer is simple: I don't XD

But. This forces me to build a system that helps me quickly switch between different types of tasks, focus quickly and complete them over and over again.

So, today I want to tell you about one of the things, that can completely ruin your day. And sometimes – whole week. It's called "context switching".

Machine Learning (ML) technologies are becoming increasingly popular and have various applications, ranging from smartphones and computers to large-scale enterprise infrastructure that serves billions of requests per day. Building ML tools, however, remains difficult today because there are no industry-wide standardised approaches to development. Many engineering students studying ML and Data Science must re-learn once they begin their careers. In this article, I've compiled a list of the top five problems that every ML specialist faces only on the job, highlighting the gap between university curriculum and real-world practice. 

Spring is in full swing as we bring you the hottest winter news of the January Commitfest. Let's get to the good stuff right away!

Previous articles about PostgreSQL 17: 2023-07, 2023-09, 2023-11.

Today, I would like to share my personal story. I hope it helps you get to know me better and maybe benefits your own journey.

Wearable Digital Health Technologies for Monitoring in Cardiovascular Medicine

This review article presents a three-part true-life clinical vignette that illustrates how digital health technology can aid providers caring for patients with cardiovascular disease. Specific information that would identify real patients has been removed or altered. Each vignette is followed by a discussion of how these methods were used in the care of the patient.

In this article, I’m going to discuss something really important. If you’re a data analyst or you want to learn data analysis, please watch this video till the end because it’s really important.

Few days ago, Mira Murati, Chief Technology Officer at OpenAI, introduced the company's latest GPT model - GPT-4o. A new flagship model set to change how people interact with AI.

Hi Everyone.

Recently I got Asus E200H laptop, which I would like to use as a portable computer to work with a high-precision equipment.

Within the scope of the article we will perform the experiment about the upgrade of the default 32 GB eMMC capacitor to 256 GB and will test it.

Have a nice reading!

According to the Oxford Dictionary, empathy is “the ability to understand and share the feelings of another”. In UX, there is a special term “user empathy”. It refers to the ability of UX designers to fully understand what users need from a particular software product. Having user empathy and basing design solutions around users” comfort is one of the most true indicators of a designer”s professionalism. Without that, any product a designer works on has a high chance of turning out to be pointless. Apart from having empathy as a soft skill in general, there are several ways a designer can practice user empathy through different UX methods and techniques. In this article we would like to talk on how a UX designer can treat users with empathy and make the product more accessible for different groups of target audience.

Welcome to my latest article. If you haven't caught my previous ones, I highly recommend checking them out for some really useful content. Today, I'm excited to dive into something special: my top 10 favorite VS Code extensions. These tools are incredibly popular among developers globally, and I believe they're essential for anyone serious about coding.

Recent research published in the journal Patterns has shown examples of how artificial intelligence (AI) systems are learning to manipulate information and deceive people. The concept of deception by AI dates back to Alan Turing's famous 1950 paper, which introduced the "Imitation Game" - a test that evaluates whether a machine can demonstrate human-like intelligence.

It's been a while since my last appearance, but I'm excited to be back and to share something truly special with you. In this article, we'll explore my top 10 Google Sheets features that are guaranteed to boost your productivity, speed up your workflow, and make your data handling more efficient. So, without further ado, let's dive into these game-changing tools!

I always pay attention to assessing the complexity of programming in a particular language. Programming is indeed not an easy task and this is perceived as a fact and usually does not require any confirmation.

But the concept of “complexity” is akin to the term “heap”. For some, five coconuts is not so much, but for someone who ate one and “didn’t want any more,” this means that even one coconut will be too much for him.

The same goes for the complexity of programs. It seems that the constant increase in the complexity of programs is obvious to everyone and is observed in all areas of application of IT technologies, and programming languages themselves become more and more complex as they develop, but assessing “complexity” using numerical metrics is a problem. obviously a thankless task, but also “You can’t manage what you can’t measure...”

Typically, talk of “complexity” only implies value judgments without any numerical evaluation. And since I am personally interested in the issue of the complexity of programming languages, I decided to calculate the complexity of implementing the gcc compiler on some conditional “parrots”. What if we could see some patterns of difficulty changing over time?

Practically all programming languages are built either on the principle of similarity (to make like this one, only with its own blackjack) or to realize some new concept (modularity, purity of functional calculations, etc.). Or both at the same time.

But in any case, the creator of a new programming language doesn't take his ideas randomly out of thin air. They are still based on his previous experience, obsession with the new concept and other initial settings and constraints.

Is there a minimal set of lexemes, operators, or syntactic constructs that can be used to construct an arbitrary grammar for a modern general-purpose programming language?

The director Denis Villeneuve and cinematographer Greig Fraser in their Dune: Part Two movie made a curious decision to film the scenes on the surface of the Giedi Prime planet in the infrared spectrum. It turned out to have interesting aesthetics and there are some interesting related physics to discuss and speculate about how realistic the look of it is.

S.B. Pshenichnikov

The article outlines a new mathematical apparatus for verbal calculations in NLP (natural language processing). Words are embedded not in a real vector space, but in an algebra of extremely sparse matrix units. Calculations become evidence-based and transparent. The example shows forks in calculations that go unnoticed when using traditional approaches, and the result may be unexpected.

The use of IT in Natural Language Processing (NLP) requires standardization of texts, for example, tokenization or lemmatization.

After this, you can try to use mathematics, since it is the highest form of standardization and turns the objects under study into ideal ones, for example, data tables into matrices of elements. Only in the language of matrices can one search for general patterns in data (numbers and texts).

If text is turned into numbers, then in NLP these are first natural numbers for numbering words, which are then embedded into real vectors is irreversible ed in a real vector space.

Perhaps we should not rush to do this but come up with a new type of numbers that is more suitable for NLP than numbers for studying physical phenomena. These are matrix hyperbinary numbers. Hyperbinary numbers are one of the types of hypercomplex numbers.

Hyperbinary numbers have their  own  arithmetic,  and  if  you get used to  it,  it  will  seem  more  familiar  and  simpler  than  Pythagorean arithmetic.

In Decision Support Systems (DSS), the texts are value judgments and a numbered verbal rating scale. Next (as in NLP), the numbers are turned into vectors of real numbers and used as sets of weighted arithmetic average coefficients.

Every programmer is familiar with the concept of "reference." This term usually refers to a small object whose main task is to provide access to another object physically located elsewhere. Because of this, references are convenient to use, they are easily copied, and they make it very easy to access the object to which the reference points, allowing access to the same data from different parts of the program.

Unfortunately, manual memory management, or more precisely, manual memory control, is the most common cause of various errors and vulnerabilities in software. All attempts at automatic memory management through various managers are hampered by the need to control the creation and deletion of objects, as well as periodically run garbage collection, which negatively affects application performance.

However, references in one form or another are supported in all programming languages, although the term often implies not completely equivalent terms. For example, the word "reference" can be understood as a reference as an address in memory (as in C++) and a reference as a pointer to an object (as in Python or Java).

Although there are programming languages that try to solve these problems through the concept of "ownership" (Rust, Argentum, or NewLang). The possible solution to these and other existing problems with references will be discussed further.

In the ever-evolving landscape of software development, communication between processes has been a fundamental requirement since the inception of computer networking. As technology advanced, the need for efficient and reliable inter-process communication (IPC) mechanisms became increasingly crucial. One such mechanism that has stood the test of time is the socket.
Sockets trace their origins back to the early days of computer networking in the 1970s. The concept was first introduced in the Unix operating system by researchers at the University of California, Berkeley, as part of their work on the ARPANET project, which eventually evolved into the modern internet. Sockets were designed to provide a standardized interface for network communication, allowing processes to exchange data across different machines and networks.
Initially, sockets were primarily used for network programming tasks, such as building client-server applications and facilitating communication between distributed systems. However, their versatility soon became apparent, and sockets found their way into various domains, including inter-process communication (IPC) within a single machine.
Over the years, sockets have undergone numerous enhancements and standardizations, with the Berkeley Software Distribution (BSD) sockets becoming the de facto standard for network programming. This standard was later adopted by other operating systems, including Microsoft Windows, ensuring cross-platform compatibility and enabling widespread adoption.
In the world of software development, communication between processes is a common requirement, whether it’s a client-server architecture, distributed systems, or inter-process communication (IPC). Sockets provide a powerful mechanism for processes to exchange data efficiently and reliably. This article explores a simple implementation of a TCP client-server communication using sockets in C#, showcasing the versatility and robustness of this time-tested technology.

Navigating the intricacies of UI testing in the world of Flutter web applications can be a daunting task. If you've ever found yourself scratching your head, wondering how to apply your Selenium expertise to a Flutter-rendered interface, this article is for you. We're going to explore a method that bridges the gap between Flutter's unique rendering process and the robust testing capabilities of Selenium. Whether you're a seasoned tester or just starting out, the insights shared here will equip you with the knowledge to streamline your testing process and enhance the quality of your Flutter web apps. So, grab a cup of coffee, settle in, and let's unravel the mysteries of UI testing for Flutter web applications together.

Hello everyone!

A year ago, I became curious about whether it was possible to earn money in crypto by copying the trades of other traders. Instead of investing money right away, I decided to thoroughly explore this by writing a parser that monitored about 2,000 portfolios in real-time over the course of a year.

Initially, I parsed the Traderwagon site, which unfortunately shut down. I then switched to Binance's copy trading, which was just starting out at the time.

The number of portfolios available for investment on Binance is continually growing; currently, there are over 10,000. My script only parsed a portion of these to maintain about 2,000 consistent portfolios. This was necessary to track changes in traders' positions at least every 20 minutes with the server resources I had allocated for the project.

There are several peculiarities in how my parser operates. For example, when a trader hides their positions, my script also closes them since it can't monitor hidden trades. When a trader significantly adjusts their position, such as a complete turnaround, the script exits the trade. I chose to save time on developing a more complex follow-algorithm and planned to refine it later if the testing stage proved successful. I also limited the time a trader could stay in a deal to a few days and forcibly closed positions if this period was exceeded. I observed that staying in a trade longer slightly increased the average profit/loss, whereas reducing the time allowed for reinvesting the same funds into a greater number of traders and their deals.