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.
Admit it, how many times have you wanted to quickly create an image for a post or presentation, but instead got stuck in an editor or endless searches for a suitable image on Google? Wouldn't it be great if the picture in your head could just appear instantly? Time is money, inspiration is on pause, and that's where AI comes to the rescue. Neural networks can generate anything you want, including the craziest ideas. No need to spend hours searching when, with a few clicks, you can see what was in your thoughts just a second ago.
By the way, notice the cover with the dinosaur? Let's call him Rex. Rex is himself a product of neural network creation. Today he'll be the main star of our experiments. But what will we do? Remember I mentioned crazy ideas? Well, to understand all the possibilities of generation, let's give AI a difficult task. We'll send Rex somewhere in space, for example to the Moon, let him put on a spacesuit and and have him grill some barbecue with Earth in the background. Interested? Then buckle up, we're heading into the world of image generation.
Historically, we’ve ended up using a few rather obscure PHP extensions—written and barely (if at all) maintained by their original authors—that aren’t available in standard Debian package sources.
We stick to the principle of “do it right, and it’ll work right,” which means Slackware-style dropping binaries into the system outside of package managers is frowned upon.
So instead, we’ll be building proper .deb packages for PHP extensions—without breaking compatibility with the existing environment.
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.
We are a brokerage platform operating in a dynamic and complex domain. This specificity comes with a set of challenges. On the one hand, it entails a high variability of scenarios and potentially significant risks associated with errors. On the other hand, it has short development iterations with frequent delivery cycles.
In this article, we will share how we maintain the quality of our numerous backend services, which provide essential information to our trading terminals.
Gen Z – a generation of young people born between the last few years of the 20th century and the first ten years of the 21st, are the primary users of a modern-day Internet. They started using technology since their early childhood, being almost constantly glued to their smartphones and tablets, which led to them being very demanding users that have their own requirements in UX. At the same time, they are known for their sense of humor and straightforwardness – which means they love using products that are both easy to navigate but full of interactive elements. Below we’ve collected a few things you should consider when creating a UX design aimed at a young audience.
In today's interconnected development world, secure authentication is not just a luxury—it's a necessity. Whether you're a seasoned DevOps engineer or a junior developer just starting your journey, understanding SSH key pairs is crucial for your daily workflow. They're the unsung heroes that keep our git pushes secure, our server access protected, and our deployments safe from prying eyes.
But let's be honest: SSH keys canbe confusing. With terms like “public key infrastructure,” “cryptographic algorithms,” and “key fingerprints” floating around, it's easy to feel overwhelmed. This guide aims to demystify SSH key pairs, breaking down complex concepts into digestible pieces that will help you make informed decisions about your security setup.
This article is the first in the series about the upcoming PostgreSQL 18 release. Let us take a look at the features introduced in the July CommitFest.
Planner: Hash Right Semi Join support
Planner: materializing an internal row set for parallel nested loop join
Planner support functions for generate_series
EXPLAIN (analyze): statistics for Parallel Bitmap Heap Scan node workers
Functions min and max for composite types
Parameter names for regexp* functions
Debug mode in pgbench
pg_get_backend_memory_contexts: column path instead of parent, new column type
Function pg_get_acl
pg_upgrade: pg_dump optimization
Predefined role pg_signal_autovacuum_worker
Firebase Performance offers a free, comprehensive solution for tracking app performance. As part of the Firebase suite, it provides seamless integration with other Firebase services like Crashlytics, making it easier to manage all performance and crash data in one place. This not only simplifies access but also streamlines team collaboration without the need to manage multiple platforms.
Recently I have bought starfive visionfive-2 SoC for my own experiments, honestly speaking
I am striving to work with risc-v. After some time I decided to share my experience. Here my bulletpoints:
Small preparation USB-to-Serial connector Write image to microSD/SSD Set boot mode settings
Boot Update bootloader Build kernel Native build Pod build Cross-build on amd64: fast and handy
Chroot to risc-v system from amd64 and install packages
Bonus 1: run qemu with risc-v
Bonus 2: build deb packages for risc-v
Bonus 3: kernel build script
Conclusions
I came across a script on the Internet that allows you to parse product cards from Amazon. And I just needed a solution to a problem like that.
I wracked my brain while looking for a way to parse product cards from Amazon. The problem is that Amazon uses different design options for different outputs, in particular – if you need to parse the cards with the search query "bags" – the cards will be arranged vertically, as I need it, but if you take, for example, "t-shirts" – then the cards will be arranged horizontally, and in such way the script falls into an error, it works out opening the page, but does not want to scroll.
A story about evolving our CI process for a monolithic Python repo with tests, challenges faced, and solutions. Discussing Docker, linters, Allure TestOps, and more.
I’ve been wanting to sort it out about String memory optimization and all these ways to improve the performance and memory usage for Collections and Arrays in C#(as you remember String is an array of chars, loaded a bit differently but anyway) code. I finally managed to find some time to dive deeper into the System.Span.
I have put together this guide to share what I’ve learned. It’s filled with practical tips and examples to help you leverage Spans in your own projects. If you want to optimize your C# code, this guide is a great place to start!
Code Push in Flutter
In the fast-paced world of mobile app development, the ability to quickly push updates to users is crucial. Enter Code Push - a game-changing technology that allows developers to update mobile apps instantly without going through the traditional app store review process. This article explores how to implement Code Push in Flutter applications using Shorebird, a powerful tool that brings this capability to the Flutter ecosystem.
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.
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.
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?
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.
In this report we describe our implementation experience of a stopwatch system executing on an FPGA board. We programmed this device in the Quartus Prime II software environment by using Verilog hardware description language. The program is tailored to the Altera MAX 10 FPGA board, as well as uses a set of other peripheral devices for progress visualization purposes.
This is a step-by-step research of a clear and intuitive approach to validate custom data in .NET applications with help of the Minimal API filters and the FlatValidator.
