Computer Science and Programming
151K subscribers
633 photos
29 videos
37 files
920 links
Channel specialized for advanced topics of:
* Artificial intelligence,
* Machine Learning,
* Deep Learning,
* Computer Vision,
* Data Science
* Python

Admin: @otchebuch

Memes: @memes_programming

Ads: @Source_Ads,
https://telega.io/c/computer_science
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Air Lab Simulator
A web-based simulator that replicates Air Lab firmware functionality, allowing users to interact with virtual environmental sensors through different simulated environments. The simulator includes device controls, USB connectivity simulation, and menu navigation features, providing a hands-on experience without requiring physical hardware.
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Read That F*cking Code!
AI coding tools like Claude Code enable developers to generate working code without reading it, but this practice leads to three critical issues: architectural decay, loss of domain knowledge, and security vulnerabilities. The author advocates for two responsible approaches: fast prototyping with post-session review for peripheral features, and synchronous pair-coding for core functionality. A comprehensive checklist covers architecture consistency, security scoping, meaningful tests, documentation, error handling, and performance considerations.
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everywhere.tools
A comprehensive collection of open-source tools tailored for designers and creative professionals to enhance their work.
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AI Is Not a Black Box (Relatively Speaking)
AI systems are actually more transparent than human intelligence when it comes to understanding their internal workings. While AI is often called a "black box," researchers can inspect every neural connection in open-source models, trace concept paths through networks, and determine input importance - capabilities far beyond what's possible with human brain analysis. Even closed-source AI models can be studied through controlled interrogation and distillation techniques. The human brain remains more opaque due to physical and ethical constraints on research, making AI the more interpretable intelligence despite popular perception.
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Open Data Standards: Postgres, OTel, and Iceberg
The post discusses emerging open data standards in the data world including Postgres, Open Telemetry (OTel), and Iceberg. These standards are underpinned by important open source tenets: OSI-approved licensing, the feasibility of self-hosting, and vendor neutrality. Postgres has become a standard due to its compatibility across platforms and non-ownership by any single entity. OTel is gaining traction among major cloud providers for its telemetry capabilities, while Iceberg is leading in OLAP standards. The emphasis is on achieving portability and interoperability, particularly with AWS's S3, enhancing data management and reducing vendor lock-in.
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anthropics/prompt-eng-interactive-tutorial: Anthropic's Interactive Prompt Engineering Tutorial
This tutorial provides a structured guide to mastering prompt engineering with Claude, including nine chapters with exercises and an appendix of advanced methods. Users will learn to create optimal prompts, recognize common errors, and utilize areas like an Example Playground to experiment. The tutorial uses Claude 3 Haiku and recommends using the Google Sheets extension for convenience.
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Openness (Open Data Architecture)
Openness in data architecture refers to building sustainable and trustworthy systems through open-source and standardized formats. It promotes collaboration, avoids vendor lock-in, and maximizes the utility of open-source tools. Key components include data lakes, data warehouses, and orchestration, which support data management ecosystems like the data lakehouse and modern data stacks
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The fastest was to learn is from writing not reading I truly recommend using this steps.

If you’re learning something new-coding, design, strategy, systems, writing about it will double the speed and depth of your learning.
It doesn’t have to be public. It doesn’t have to be pretty.
But it has to be real.
Because writing forces you to slow down, organize your thoughts, spot your blind spots, and sharpen your understanding in ways passive consumption never will.
Passive learning ≠ real learning
You can binge a 3-hour YouTube
Scroll 20 well-crafted Twitter threads on business models.
Maybe even highlight a few Medium articles.
And you’ll feel smart afterward.
But until you try to explain the concept in your own words, you won’t know what you actually understand - and what you’ve just memorized.
“If you can’t write it clearly, you don’t understand it deeply.”
Writing is the cheapest, fastest test of comprehension. No grades. No teacher.
Just a blinking cursor asking, “Do you actually get this?”
Ever try explaining something and halfway through…your brain just blanks?
That’s not failure - it’s discovery. It’s your mind running into a gap you didn’t know existed. And once you see it, you can fix it.
Writing makes those invisible gaps visible. It turns “I think I get it” into “I know where I’m lost.”
This is where compounding kicks in
After 10 write-ups on how you built or solved something, you start seeing patterns:
→ The same problems keep showing up
→ Certain assumptions fail every time
→ The same tools quietly carry the weight
Those patterns become systems. And once you have systems, learning stops being a linear grind - it starts compounding.
You don’t have to be a “writer”
Pick a simple rhythm and stick to it:
Mon → “What did I struggle with today?”
Wed → “What finally clicked?”
Fri → “What would I tell someone learning this?”
Keep each entry under 200 words. Don’t over-edit. The goal isn’t to look clever - it’s to think clearly.
The people who learn fastest aren’t the ones with the most raw talent.
They’re the ones who write.
Not for likes. Not for followers. But because writing is how they process, refine, and absorb faster than everyone else around them.
Thinking is messy. Writing makes it real.
Do you write while you’re learning - or only once you feel ready to “share”?
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How To Review Code
A comprehensive guide to effective code reviewing based on two decades of experience. Emphasizes focusing on big picture design over syntax, the critical importance of good naming, being decisive when rejecting changes, and treating reviews as iterative communication processes. Key principles include running code locally when possible, asking clarifying questions, avoiding nitpicking on formatting, and continuously learning from the review process.
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facebook/docusaurus: Easy to maintain open source documentation websites.
Docusaurus is a static site generator built by Meta for creating and maintaining documentation websites. It offers simple setup with npm initialization, built-in localization support, customizable themes, and includes essential pages like docs, blog, and home sections. The project is open source, actively maintained, and designed to help developers focus on content rather than website infrastructure.
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Gemini 2.5 and the future of AI reasoning for frontend devs
Google's Gemini 2.5 Pro introduces advanced reasoning capabilities for frontend development, featuring a 1 million token context window and multimodal processing. The model leads current AI leaderboards for web development tasks and offers competitive pricing compared to GPT-4o and Claude. Key advantages include native step-by-step reasoning, ability to process entire codebases, and integration with Google's custom TPU hardware for faster, cheaper inference. Practical demonstrations show the model can generate complete web applications, 3D games, and recreate popular social media interfaces from single prompts
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Faster Dashboards with Multi-Column Approximate Sorting
Advanced multi-column sorting techniques using space filling curves (Morton and Hilbert encodings) and truncated timestamps can significantly improve query performance on columnar data formats. These methods enable approximate sorting across multiple columns simultaneously, allowing diverse dashboard queries to benefit from min-max indexes and row group pruning. Experiments on flight data show Hilbert encoding provides the most consistent performance across different query patterns, while sorting by truncated timestamps (year-level granularity) combined with Hilbert encoding works best for time-filtered queries.
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google/mangle
Mangle is Google's open-source programming language that extends Datalog for deductive database programming. It enables querying data from multiple sources uniformly and supports recursive rules, aggregation, and function calls. The language is particularly useful for vulnerability detection, dependency analysis, and knowledge graph modeling. Implemented as a Go library, Mangle can be embedded into applications and offers practical extensions beyond traditional Datalog while maintaining accessibility for developers.
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Building an MCP-powered Financial Analyst
Explore the process of building a financial analyst powered by MCP (Multi-agent CP), which integrates AI components like DeepSeek-R1 LLM and CrewAI for multi-agent orchestration. The system setup includes agents for query parsing, code writing, executing, and visualization of financial data. The tech stack utilizes various tools to create a locally functional financial analyst that can perform complex stock analysis and generate visual outputs.
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Google wants you to vibe code now

Google launched Firebase Studio, an AI-assisted development platform that builds on Project IDX with enhanced Gemini-powered features for full-stack app development. The platform offers blueprint-first prototyping, integrated Firebase services, and free access during its initial phase. Meanwhile, Postman unveiled new AI tools at POST/CON 25, including MCP server generation and agent mode for API testing. The newsletter also covers various developer resources, including TypeScript team updates, frontend testing guides, and React's 12th anniversary celebration.
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Nitrode – AI Game Engine: AI Game Engine to Prototype 3D Games in a Day
Nitrode is an AI-powered game engine designed to help developers rapidly create playable 3D games within hours rather than weeks or months. The platform enables 'vibe coding' for quick prototyping, targeting developers who want to build games they've envisioned but lacked the time or resources to develop using traditional methods.
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How server actually works?
NGINX serves as a powerful web server and reverse proxy that handles three critical functions: load balancing (distributing traffic across multiple servers using methods like round robin and least connections), caching (storing frequently requested content for faster delivery), and security (encrypting communications and hiding backend infrastructure). The article explains how these features work together to keep websites fast and reliable, using real-world analogies like restaurant kitchens and nightclub bouncers to make complex concepts accessible to beginners.
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Bash Explained: How the Most Popular Linux Shell Works
Bash (Bourne Again Shell) is a command-line interpreter and scripting language that serves as the default shell on most Linux distributions. It provides both an interactive interface for executing commands and a scripting environment for automation tasks. The guide covers Bash's history, features like command history and tab completion, differences from other shells, and practical applications in modern DevOps workflows including CI/CD pipelines, system administration, and cloud automation. It includes hands-on examples, common troubleshooting tips, and best practices for writing robust scripts.
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Self-Host Weekly (1 August 2025)
Weekly roundup of self-hosted software updates and new releases, featuring major updates to popular applications like Navidrome's multi-library support, Tandoor Recipes v2 frontend rewrite, and Immich's custom share URLs. Covers 18 software updates, 19 new tools, and recently discovered projects spanning categories from media streaming to container management, plus community content and tutorials.
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