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AI technologies offer unprecedented opportunities for innovation, efficiency, and growth in such industries as advanced machine learning algorithms or intelligent automation systems. However, to harness the power of AI, effective communication becomes paramount.

The growing impact of AI in modern business is undeniable. Organizations leverage AI to automate processes, gain insights from vast amounts of data, personalize customer experiences, and make informed decisions. Yet, the complex nature of AI technology often creates a significant gap between AI capabilities and the understanding of its users.

Here the role of a technical writer becomes crucial. Technical writers act as a bridge between AI technology and its users, ensuring that complex concepts have a clear, concise, and user-friendly manner of speaking. They are the main participants in making AI accessible to a broader audience, facilitating adoption, and maximizing its potential.

Effective communication is essential to reduce the gap between AI technology and its users. While AI systems may be sophisticated and comprehensive, their impact can be weak without proper understanding and utilization. Technical writers contribute to the success of AI implementations by translating complex AI concepts into easily digestible documentation, user manuals, tutorials, and other communication channels.

Furthermore, technical writers understand the importance of tailoring information for different audiences. They communicate with non-technical stakeholders, including executives, decision-makers, and end-users, who may lack extensive technical expertise. Using the AI capabilities, benefits, and potential limitations, technical writers empower these stakeholders to make informed decisions and embrace AI solutions.

Generative AI is creating waves in the way we work, significantly revolutionizing the software development process. AI tools are appearing in various phases of software development, such as design, development, and testing. However, there aren't many tools specifically focused on software business analysis tasks.

But with a little creative thinking, we can put "one-size-fits-all" applications like ChatGPT to good use. It can definitely speed up execution of many typical tasks and free up analysts to focus on the more challenging, strategic aspects of the job.

I believe that every programmer has at least once heard about ChatGPT and its marvelous abilities to process, calculate and create huge amounts of data; if not, go check out this Wikipedia article - https://en.wikipedia.org/wiki/ChatGPT.

Can you imagine that some 50 years ago people could not even believe that there may be something artificial surpassing humans in so many areas? Nowadays, we have this marvel at the distance of a few tabs on a phone screen or a keyboard; however, there is still a sadly large number of people who do not fully—if at all— utilize all the perks of ChatGPT in their lines of work. This is mostly related either to people's reluctance to learn new technologies or the fear of losing coding skills they have previously gained—which is not the case with using ChatGPT properly.

In this article I want to give you some of the most useful uses of ChatGPT for your coding work. Remember, there is nothing shameful in using the AI, since this the development and further implementation of it in our day-to-day life is inevitable, so we should start adapting to it as early as we can to take the full advantage of this "magical" technology. Let's get started.

It hasn't been that long since my last cheat sheet was published and this is the day for the new one. This time I got a task to find a solution for backing up Kafka to S3 bucket, following the terms:

I'm Alex Movergan, DevOps team lead at Altenar. I focus on automation in general and on improving troubleshooting skills within my team. In this article, I'll share a captivating tale that revolves around Kubernetes, validation webhooks, kubespray, and Calico.

Join me on this DevOps journey as we explore real-world scenarios unraveling the intricacies of troubleshooting in a Kubernetes environment.

Hi, my name is Mikhail Emelyanov, I’m a Python programmer and I would like to show you my pet project — Flywheel, a micro-platform for learning foreign languages, a mixture of Duolingo and Anki, an application that can teach you to properly write in Spanish (or any other language you’re studying). Flywheel’s source code is available on GitHub.

As you may know, generalized knowledge of a foreign language can be broken down into four relatively independent components: reading, writing, listening, and speaking. Unfortunately, training one of these abilities has no direct effect on the other components, so, for example, by developing our reading skills, the effect on our writing skills is quite indirect. Flywheel is a ‘sharpener’ specifically for written Spanish.

If you’ve ever used Duolingo, you should have some idea of the format in which you’ll be studying. The formula is simple: here’s a phrase, translate it into the other language; the app will remember the last time you translated a phrase and how successful you were at it; and depending on the accuracy of your answer, it will determine when you should do the same phrase again. In my opinion, Duolingo and its approach are brilliant. However… There are certain aspects that somewhat spoil the learning experience, and Flywheel was specifically designed to address them.

I have been working in Agile since 2017 in several projects.
And I would like to note here a couple of moments from real experience through the eyes of developer role in project.
Hope it will be helpful for you!

Hello, my reading friends!

My previous post (rus) on Habr was about how the Business Continuity Management function started, as well as about its relations with other corporate functions. In fact, it was quite theoretical.

This time, I’d like to tell you about some practical vectors of procedures and tools implementation as regards to Business Continuity Management, or BCM, along with Operational Resilience, or OpRes. Plus some real initiatives that can follow the BCM & OpRes implementation in a company and the associated with it investigation of the corporate landscape and procedures.

In this article, I will cover basic work with MapView (and MapFragment) markers, learn how to implement marker clustering, i.e. group markers located close to each other, and display dynamic icons in the markers, i.e. load by url and display remote images. Ultimately, we will create such map with clusters and dynamic image loading (in background).

Solution of the day.
LeetCode 956 (Hard). Tallest Billboard.

The code uses dynamic programming to solve the problem. It maintains a dictionary dp, where the keys represent the possible height differences between the two billboards, and the values represent the maximum sum of heights achieved for each height difference.

Recently, The BCI, one of the leading institutes working in the field of organizational resilience and business continuity, issued its regular report BCI Operational Resilience Report 2023 in collaboration with Riskonnect, who work with risk management solutions.

One of the questions they asked the respondents was if there was a difference between organizational resilience and operational resilience. As the answers demonstrated, for most respondents (and in most companies) these terms were used as synonyms. Having studied the report, the colleagues brought up another matter – The BCI introduced the new term of "organizational resilience" in addition to "business continuity" and "operational resilience".

If we search Habr for "Business Continuity", "DRP", "BCP", or "BIA", we’ll find quite enough posts by my colleagues (I’ve met some of them face to face and worked with the others) about data system recovery, data system testing, fault-tolerant infrastructure, and some other things. Yet, hardly any of them explain where all of it has come from, how it is changing, where it is heading – and why.

I thought the time has come to change the situation for the better and answer some of the questions like where business continuity provisions and operational resilience has come from, how they are changing, and where this trend is heading and why. To share my thoughts about development of the industry and its current de-facto state in case of a mature (or not too mature) introduction level – some things I’ve stated for my own use.

Openjob is a distributed and high-performance task scheduling framework that supports multiple cronjob, delay task, workflow, lightweight distributed computing, unlimited horizontal scaling, with high scalability and fault tolerance. Also has perfect permission management, powerful alarm monitoring, and support multiple languages

Hash, salt, SHA-1, SHA-2, std::hash.. To a non-programming person that may come up as some kind of a recipe that just does not seem to add up. In a sense, this is indeed supposed to be a gibberish to any third party and a strong, helpful mechanism for us, programmers. 

At the start of writing this article, I had one clear idea to get across the table: to finally unveil this mystery of hashing in C++ for beginners. I, a beginner myself, also wanted to solidify my knowledge in this area; so let’s get started.

3.What's an ugly smiling face?

It's the cat from curved space.

V. Komen, I. Tikhonenkov

Here we are discussing in general the majority of metrics for a stationary gravitation fields in one dimension. The only accepted approach so far to apply the equations of field (A. Einstein):

Today I would like to discuss the games Chess and Go, the world's champions, algorithms and Al.

In 1997, a computer program developed by IBM Deep Blue defeated the world Chess champion Garry Kasparov. Go remained the last board game in which humans were still better than machines.

Why is that?

Chess is primarily distinguished from Go by the number of variations for each move. Chess, the game is more predictable with more structured rules: we have value for each figure (e.g bishop = 3 pawns, rook = 5 pawns -> rook > bishop), some kind of openings and strategies. Go, in turn, has incredibly simple rules, which creates the complexity of the game for the machine. Go is one of the oldest board games. Until recently, it was assumed that a machine was not capable of playing on an equal footing with a professional player due to the high level of abstraction and the inability to sort through all possible scenarios - exactly as many valid combinations in a game on a standard 19×19 go-ban are 10¹⁸⁰ (greater than the number of atoms in the visible universe).

However, almost 20 years later, in 2015, there was a breakthrough. Google's Deep Mind company enhanced AlphaGo, which was the last step for the computer to defeat the world champions in board games. The AlphaGo program defeated the European champion and then, in March 2016 demonstrated a high level of play by defeating Lee Sedol, one of the strongest go players in the world, with a score of 4:1 in favour of the machine. A year later, Google introduced to the world a new version of AlphaGo - AlphaGoZero.

lsFusion platform is designed for rapid development of business applications. It is distributed under the terms of a Lesser General Public License (LGPLv3). The source code of the platform is available on Github.

lsFusion is best suited for creating complex systems with large numbers of entities and forms, where users need to input and process large amounts of data. However, the platform can also be used to quickly create simple applications instead of spreadsheets when Excel’s functionality is not enough.

At the same time the use of the platform will not give a great advantage when developing applications aimed at interaction with a large number of “external” users or without the need for any complex calculations. You should also take into account that the web interface is a single page application using JavaScript. Therefore, the lsFusion platform is not well-suited for creating websites, for example.

This article aims at explaining the mathematical sense of the Principal Component Analysis (PCA) in practice.

In my previous article, I showed you how to deploy your project to Firebase and use it for free. Now, let’s explore additional benefits of Firebase. In the upcoming article, I will show you how to set up a custom domain name for your project and utilize a free SSL certificate from Firebase.

Faced with the situation when calling Mono::block leads to deadlock - in debug I can just see how it stands on Unsafe::park and no more movement at all.

V. Komen, I. Tikhonenkov

In the previous post we've considered a model example of a motion of a free particle within a uniform gravitation field where a coupling to the field is defined by an observed inertion mass (see eq. (2) in https://habr.com/en/articles/739714/). The equation of motion was: