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Do you want to know how to build an AI image analyzer? Then read this article till the end! I'm going to show you how to build AI analyzer tools really simply, so you almost don't have to have any prior knowledge. I will take you step by step, and we will use Project IDX and the Gemini API. This means you don't have to set up anything; everything we will do is on the cloud. If you're ready, then let's get started!

Creation of a UX design for a software product is an ongoing process: it doesn’t stop after the product is released. In order for an app or a website to always remain comfortable to use while corresponding to the constantly changing trends, its UX design must be improved from time to time, and in some cases even rethinked and radically changed. An outdated, old-fashioned design with unimproved bugs will definitely spoil user experience and lead to loss of audience. Design improvements include not only bug fixing and “brushing up” the facade of a product, but also constant research and implementation of new ideas that can contribute to its growth. Let’s discuss a few simple steps that can improve the UX design of any product. 

Recently, there has been a lot of talk about the success of artificial intelligence (AI), although this usually means another achievement in the field of generative neural networks.

And few people, speaking about AI, try to explain what they themselves understand by the term “artificial intelligence.” After all, it’s one thing to write about “AI problems,” and quite another to endow an ordinary computer algorithm with at least the rudiments of intelligence.

After all, the etymology of the established phrase “artificial intelligence” is not unambiguous and can take on different meanings depending on what meaning the author is trying to put into it.

Quantum computers have gradually migrated from “natural” quantum objects like ions and quantum dots to “artificial” objects like transmons, where natural frequencies of LC circuit mimic energy levels. Coaxial cables attached to such circuits excite the system, read their state, and adjust their properties. They are still quantum objects and operate at low temperatures.

I wondered if a similar system can be built with large “classical” mechanical objects. Here I demonstrate 2 -qubit quantum computer built of coupled pendulums.

Gowin has clear advantages over Xilinx in the educational FPGA board market: Gowin boards are several times less expensive, the synthesis speed is several times faster, and the EDA package is two orders of magnitude smaller: we are talking about 1G versus 100G disk space. Of course, Xilinx is still the king of high-end prototyping boards that cost $10K-100K, but for the students such boards are irrelevant; such boards are for ASIC design companies. A beginning EE student needs a board for less than $100, and Gowin not only fits the bill but also covers all the needs, specifically:

In today's fast-paced world of software development, integrating third-party APIs and services is a common practice. These integrations can enhance functionality, improve user experience, and provide additional features that would be time-consuming and costly to develop in-house. However, ensuring these integrations work seamlessly with your software is crucial, and this is where the importance of a test environment, or sandbox, comes into play.

A sandbox environment allows developers to test the integration between their software and third-party services without risking the stability and security of the production environment. This controlled setting enables thorough testing, helping to uncover issues before they affect end-users. By covering as many test cases as possible, developers can ensure robust and reliable integrations.

But what if your third-party provider, such as a bank or government e-system, does not offer a sandbox environment? This scenario can pose significant challenges, but there are several strategies you can employ to mitigate these issues.

In this article, I want to introduce you to something truly amazing—Perplexity AI. This AI tool has incredible potential, and I believe it can be a game-changer for many of you. I'll walk you through how to use Perplexity AI and highlight some of its great features.

In the world of IT services, the idea that operations must run 24/7 is often taken for granted. However, for business-to-business (B2B) services, this assumption needs to be rethought. By reconsidering the need for around-the-clock processing services, companies can achieve significant benefits in efficiency, security, and sustainability.

In this article, we are going to do something really cool: we will build a chatbot using Python and the Gemini API. This will be a web-based assistant and could be the beginning of your own AI project. It's beginner-friendly, and I will guide you through it step-by-step. By the end, you'll have your own AI assistant!

In this article, we'll explore Project IDX, a new code editor developed by Google. It has the potential to change the way we write and manage code.

Hi Everyone!

In this article we a little bit will analyze of code of Windows XP and will compile the calculator application using GCC x64 in Windows 10 environment. We will look what kind of errors I faced during the build and the methods how to solve them. At the end we will launch the build of the calc.exe application.

Have a nice reading!

Sometimes it seems that jokes about management implementing Agile to do more with less aren't far from the truth. I've rarely seen development teams understand Agile as anything more than a set of ceremonies, most often associated with Scrum.

In my experience, attempts to optimize team performance often boil down to changing the internal processes within the team itself. Meanwhile, critical decisions are made outside the team, remaining in a waterfall model. This creates a disconnect: on one hand, company management strives for the flexibility of Agile, while on the other, they continue to follow rigid patterns, limiting the team and preventing it from fully realizing its potential.

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.

Governments in many countries restrict citizens' access to information and services on the Internet in one way or another. Combating such censorship is an important and difficult task. Usually simple solutions cannot boast about high reliability or long-term efficiency. More complex methods of overcoming blocks have disadvantages in terms of usability, low performance, or they do not allow you to maintain the quality of Internet use at the proper level.

A group of American scientists from the University of Illinois has developed a new method of overcoming blocks, which is based on the use of proxy technology, as well as segmenting users by trust level to effectively identify agents working for censors. We present you with the main theses of this work.

Description of the approach

Scientists have developed the Salmon tool, a system of proxy servers operated by volunteers from countries without restrictions on Internet use. In order to protect these servers from blocking by censors, the system uses a special algorithm for assigning a level of trust to users.

The method involves exposing potential censor agents that pose as ordinary users in order to find out the IP address of the proxy server and block it. In addition, countering Sybil attacks is carried out through the requirements to provide a link to a valid social network account when registering in the system or to receive a recommendation from a user with a high level of trust.

How it works

It is assumed that the censor is a state–controlled body that has the ability to take control of any router within the country. It is also assumed that the task of the censor is to block access to certain resources, and not to identify users for further arrests. The system cannot prevent such a course of events in any way – the state has plenty of opportunities to find out what services citizens use. One of them is the use of honeypot servers to intercept communications.

It is also assumed that the state has significant resources, including human ones. The censor can solve tasks that require hundreds and thousands of full-time employees.

A few more basic theses: