Computer Science and Programming
الذهاب إلى القناة على Telegram
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
إظهار المزيد
الشبكة:📈 نظرة تحليلية على قناة تيليجرام Computer Science and Programming
تُعد قناة Computer Science and Programming (@computer_science_and_programming) في القطاع اللغوي الإنكليزية لاعباً نشطاً. يضم المجتمع حالياً 141 724 مشتركاً، محتلاً المرتبة 814 في فئة التكنولوجيات والتطبيقات والمرتبة 87 في منطقة إيطاليا.
📊 مؤشرات الجمهور والحراك
منذ تأسيسه في невідомо، حقق المشروع نمواً سريعاً وجمع 141 724 مشتركاً.
بحسب آخر البيانات بتاريخ 13 يوليو, 2026، تحافظ القناة على نشاط مستقر. خلال آخر 30 يوماً تغيّر عدد الأعضاء بمقدار -1 077، وفي آخر 24 ساعة بمقدار -26، مع بقاء الوصول العام مرتفعاً.
- حالة التحقق: غير موثّقة
- معدل التفاعل (ER): يبلغ متوسط تفاعل الجمهور 6.97%. وخلال أول 24 ساعة من النشر يحصد المحتوى عادةً 1.94% من ردود الفعل نسبةً إلى إجمالي المشتركين.
- وصول المنشورات: يحصل كل منشور على متوسط 9 885 مشاهدة. وخلال اليوم الأول يجمع عادةً 2 749 مشاهدة.
- التفاعلات والاستجابة: يتفاعل الجمهور بانتظام؛ متوسط التفاعلات لكل منشور يبلغ 14.
- الاهتمامات الموضوعية: يركز المحتوى على مواضيع رئيسية مثل sellerflash, github, developer, pricing, waybienad.
📝 الوصف وسياسة المحتوى
يصف المؤلف القناة بأنها مساحة للتعبير عن الآراء الذاتية:
“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_sc...”
بفضل وتيرة التحديث المرتفعة (أحدث البيانات بتاريخ 14 يوليو, 2026) تحافظ القناة على حداثتها ومستوى وصول مرتفع. وتُظهر التحليلات تفاعلاً نشطاً من الجمهور، ما يجعلها نقطة تأثير مهمة ضمن فئة التكنولوجيات والتطبيقات.
141 724
المشتركون
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جاري تحميل البيانات...
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| التاريخ | نمو المشتركين | الإشارات | القنوات | |
| 14 يوليو | 0 | |||
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| 12 يوليو | +38 | |||
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| 04 يوليو | +6 | |||
| 03 يوليو | +3 | |||
| 02 يوليو | +5 | |||
| 01 يوليو | 0 |
منشورات القناة
SkiaSharp for .NET
SkiaSharp 4.0 is now stable, marking the biggest release in years for the cross-platform rendering library that underpins .NET MAUI, WinUI 3, and Uno Platform. Built on Google's Skia engine (which also powers Chrome and Android), SkiaSharp provides a single GPU-accelerated, pixel-perfect rendering API across Windows, macOS, Linux, iOS, Android, and WebAssembly. Version 4.0 brings the native engine current through Skia milestone m148 (28 upstream milestones), a reworked object lifecycle that eliminates use-after-free crashes, variable font support, color font palettes, animated WebP encoding, and up to 24% faster GPU rendering (30% for Uno Platform apps). Uno Platform is now a formal co-maintainer alongside Microsoft's .NET team, ensuring predictable release cadence
| 2 | Hello everyone some of you may not know but now we started to expand to WhatsApp and we are inviting you to join our WhatsApp channel link here 👇👇👇👇👇
WhatsApp Computer Science and Technology
We welcome you all to be part of this family | 2 031 |
| 3 |  DuckDuckGo browser now blocks YouTube video ads
DuckDuckGo's browser now blocks most YouTube video ads, including pre-roll and mid-roll ads, across iOS, Mac, and Windows by default. Android users must enable it manually in Settings. The feature uses community-maintained filter lists from uBlock Origin, supplemented by DuckDuckGo's own compatibility rules. It works separately from the existing Duck Player feature, and both can be used simultaneously. DuckDuckGo joins Brave and Opera in offering built-in YouTube ad blocking without third-party extensions. Minor buffering delays may occur, and the feature may occasionally break as YouTube changes its ad-serving methods. | 6 345 |
| 4 | GigaChat 3.5 Ultra Publicly Released — The New Generation of the Flagship Model
The GigaChat team has released GigaChat 3.5 Ultra as open source—a new 432B model under the MIT license. This is the first open-source hybrid of GatedDeltaNet and MLA scaled to hundreds of billions of parameters, featuring a proprietary training recipe we refined through more than 1,500 experiments. The model has grown in terms of code, mathematics, agent scenarios, and application domains—yet it’s 40% smaller than GigaChat 3.1 Ultra.
What’s inside:
🔘A proprietary hybrid MLA + Gated DeltaNet architecture with a dedicated stabilization framework, without which this hybrid setup would not train reliably at this scale;
🔘 Gated Attention: the model can locally down-weight overly strong signals from the attention layer;
🔘GatedNorm: normalization with an explicit gate that controls signal magnitude across features;
🔘Approximately 4x lower KV cache per token: with the same memory budget, the model can support 2.14x longer context and deliver a 20% throughput increase under load;
🔘Two MTP heads, enabling up to 2.2x faster generation;
🔘FP8 across all training stages with no quality degradation compared with bf16, enabled by custom Triton and CUDA kernels;
🔘A new online RL stage after SFT and DPO.
Results:
🔘 GigaChat-3.5-Ultra-Base outperforms DeepSeek V3.2 Exp Base and DeepSeek V4 Flash Base on average across a set of general, math, and code benchmarks:
🔘 GigaChat-3.5-Ultra-Instruct is comparable to DeepSeek V3.2 in terms of average score, despite having half the size;
🔘 According to the MiniMax-M2.7 LLM judge, the average win rate against GigaChat 3.1 Ultra is 75.9%, and against GPT-5 is 68.7%.
The entire stack — data (our own LLM-filtered Common Crawl, 600+ programming languages in the code), architecture, training methodology, and infrastructure — was built end-to-end by GigaChat team.
➡️ HuggingFace | 10 755 |
| 5 |  ⚠ Message was hidden by channel owner | 1 |
| 6 | Announcing SkiaSharp 4.0
SkiaSharp 4.148.0 is now available on NuGet as the first stable release of SkiaSharp v4. The release brings a Skia engine updated to milestone m148, delivering up to 24% faster GPU rendering (65→80 FPS for shadowed UIs), 6x faster CPU Perlin-noise shaders, variable font support, color font palettes, animated WebP encoding, and a cleaned-up API with fixed use-after-free crashes. Uno Platform is a co-maintainer alongside Microsoft's .NET team, meaning faster issue resolution and a predictable release cadence tied to Chrome's Skia milestones. Uno Platform users can opt in by setting the SkiaSharpVersion MSBuild property to 4.148.0. The next preview (4.150.0 Preview 2) is already available and introduces the Graphite next-gen GPU backend. | 7 869 |
| 7 | ⚠ Message was hidden by channel owner | 8 026 |
| 8 |  ⚠ Message was hidden by channel owner | 7 298 |
| 9 |  ⚠ Message was hidden by channel owner | 3 178 |
| 10 |  What's new in Git 2.55.0?
Git 2.55.0 introduces several notable features: a new `git history fixup` subcommand that amends staged changes into an existing commit and auto-rebases stacked branches; fsmonitor daemon support for Linux using inotify(7); the ability to push to a group of remotes with fsmonitor d aat's new in Git 2.55.0option for in Git 2.55.0?
Gitto cap lane width; batched blob downloads for partial clones in git-grep and git-cherry; and Rust is now a required build dependency unless explicitly disabled. | 7 720 |
| 11 |  New Features in Java 26
Java 26 introduces a range of improvements spanning performance, security, and language features. Key highlights include: restrictions on reflective modification of final fields to strengthen encapsulation; removal of the long-deprecated Applet API; AOT object caching now available with any garbage collector including ZGC; HTTP/3 support in the HTTP Client API via QUIC; G1 GC throughput improvements reducing thread synchronization overhead; a second preview of PEM encoding APIs for cryptographic objects; sixth preview of Structured Concurrency; second preview of Lazy Constants for faster startup; eleventh incubator of the Vector API for SIMD-based computation; and a fourth preview extending pattern matching to primitive types in instanceof and switch. | 9 757 |
| 12 |  Your first MCP server with ASP.NET
A step-by-step guide to building an HTTP-based MCP (Model Context Protocol) server using ASP.NET and the ModelContextProtocol.AspNetCore NuGet package. Covers project setup, registering the MCP server in Program.cs, creating tool classes with McpServerToolType and McpServerTool attributes, writing descriptive parameter annotations so AI clients can discover and invoke tools, and connecting the server to AI clients like GitHub Copilot or VS Code via a .mcp.json config file. Uses a product catalog search as a concrete example, showing how a natural language question gets translated into a tool call and back into a human-readable answer. | 12 170 |
| 13 |  EF Core Performance Best Practices in .NET 10
A comprehensive guide to EF Core performance optimization in .NET 10, covering ten key techniques: using AsNoTracking() for read-only queries, compiled queries for hot paths, compiled models for large schemas, fixing N+1 problems with eager loading, AsSplitQuery() to avoid cartesian explosion, bulk operations with ExecuteUpdateAsync/ExecuteDeleteAsync, Select() projections to avoid over-fetching, proper DbContext lifetime management with IDbContextFactory, parameterized queries for plan cache reuse, and logging slow queries with Serilog. Includes a prioritized action plan and FAQ addressing common misconceptions. | 12 038 |
| 14 | Hello everyone some of you may not know but now we started to expand to WhatsApp and we are inviting you to join our WhatsApp channel link here 👇👇👇👇👇
WhatsApp Computer Science and Technology
We welcome you all to be part of this family | 16 005 |
| 15 |  pg_kpart version 1.0
pg_kpart is a new PostgreSQL extension (v1.0) that enforces partition key usage by rejecting queries that would scan all partitions of a partitioned table. Without a usable predicate on the partition key, such queries cause full-hierarchy scans that saturate I/O and degrade performance for all connected users. The extension turns a fragile developer convention into a database-enforced guarantee, with features including an audit mode for gradual rollout, blacklist/whitelist scoping to target specific tables, and a dedicated SQLSTATE for application-level error handling. It is open source under the PostgreSQL license and available on GitHub. | 14 794 |
| 16 |  Using My Fucking Brain
A software engineer reflects on a moment where they let Claude handle an entire bug investigation and fix end-to-end — without ever reading the Sentry issue, the code, or the diff — and only realized it after merging. Claude happened to be correct, but the workflow would have looked identical if it had been wrong. The post argues that AI tools are valuable when they sharpen your thinking, but dangerous when they become a way to skip the cognitive work entirely. The author's new rule: if you can't explain the change, you can't ship it. | 13 250 |
| 17 |  Chrome for Developers
Chrome 146 introduces three notable features for web developers. Scroll-triggered animations enable declarative CSS-based control of animations based on scroll position, replacing common JavaScript-based scroll detection patterns. Scoped custom element registries allow multiple custom element definitions for the same tag name within a page, preventing naming conflicts when using libraries from multiple sources. The Sanitizer API provides a built-in way to strip script-executing content from user-supplied HTML, making it easier to build XSS-free web apps — this updated version is also available in Firefox. | 14 216 |
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| 20 |  A thousand Postgres branches for $1
Xata has reduced Postgres database branching times from 20+ seconds to 1-2 seconds through a combination of custom storage (Xatastor using ZFS over NVMe-oF) and warm pools of pre-provisioned Kubernetes pods. Branches use copy-on-write storage so you only pay for diffs to the parent. With scale-to-zero billing per minute, 1,000 short-lived branches cost roughly $1. Real-world customers like AI coding agents and CI/CD preview environments are using thousands of branches per week for under $30/month. The architecture separates compute from storage, allowing volumes to be hot-connected to waiting pods in milliseconds. | 15 537 |
