Sunday, 20 September 2026 | التحديث اليومي نظرة ثاقبة للذكاء الاصطناعي، مكتوبة للبناة

اسم المؤلف Mustafa Ihsan

Mustafa Ihsan is the founder and editor of Convly.ai. He built and maintains the site's live AI models database, its price-performance index, and its free calculators for VRAM requirements, API costs and self-hosting economics. He writes about model pricing, benchmark results and the hardware needed to run AI models locally, and consistently prefers measured numbers to vendor claims.

OpenAI Codex — explained. OpenAI Codex Open Source Release Cuts Developer.
أدوات الذكاء الاصطناعي

إطلاق إصدار OpenAI Codex مفتوح المصدر يقلل تكاليف واجهة برمجة التطبيقات للمطورين

OpenAI has reportedly fully open-sourced its Codex Harness, according to 36 Kr, opening the AI coding orchestration framework to independent deployment and inspection. The move has significant implications for how engineering teams manage API costs and build AI coding workflows.

10× — the spread we measured. LM Studio.
الدروس التعليمية

LM Studio: دليل شامل لتشغيل نماذج الذكاء الاصطناعي المحلية

TL;DR:LM Studio is a free desktop application for running large language models locally on your computer without coding or command-line workDownload models directly from Hugging Face through the built-in browser, supports GGUF format with automatic quantization selectionIncludes chat UI, local API server (OpenAI-compatible), and automatic hardware acceleration (CUDA, Metal, CPU)Requires sufficient VRAM/RAM based on model size—typically 8GB minimum for 7B models, 24GB+ for 13B modelsLM Studio is a desktop application that lets you download, run, and interact with large language models on your own computer.

2× — the spread we measured. Ollama GPT OSS.
الدروس التعليمية

أولاما جي بي تي أوس: الدليل الشامل لتشغيل النماذج المفتوحة من شركة أوبن إيه آي

TL;DRgpt-oss:20b runs in ~16GB memory (fits most gaming GPUs), gpt-oss:120b needs ~70GB (single 80GB GPU or split across consumer cards)Install with ollama pull gpt-oss:20b or ollama pull gpt-oss:120b, then run with ollama run gpt-oss:20bBoth variants use MXFP4 quantisation at 4.25 bits per parameter and support 128K context windowsReleased by OpenAI as open-weight models in partnership with Ollama, comparable to Llama 3.1 and Qwen 2.5 in quality OpenAI released gpt-oss as open-weight models in August 2025, distributed exclusively through Ollama.

DeepSeek Harne — explained. DeepSeek Harness Launches MIT-Licensed, Every Component a.
الذكاء الاصطناعي الصيني

إطلاق DeepSeek Harness بموجب رخصة معهد ماساتشوستس للتكنولوجيا (MIT)، حيث يُطبَّق كل مكوِّن على شكل إضافية قابلة للتبديل

DeepSeek AI has released the DeepSeek Harness into developer preview, an MIT-licensed agent framework where every component is implemented as a plugin. The release expands DeepSeek’s open-source developer tooling beyond its language models.

10% — measured, not claimed. Hugging Face Datasets.
الدروس التعليمية

مجموعات بيانات Hugging Face: دليل المطوِّرين

A Hugging Face dataset is a structured data collection hosted on the Hugging Face Hub, searchable at huggingface.co/datasets — over 300,000 public datasets as of 2026. Load any dataset in one line: from datasets import load_dataset; ds = load_dataset(‘stanfordnlp/imdb’)Each dataset ships with typed splits (train/validation/test), a features schema (text, image, audio, labels), and optional streaming for terabyte-scale files. Push your own data with ds.push_to_hub(‘your-username/your-dataset’) after running huggingface-cli login. A Hugging Face dataset is a versioned, structured data collection stored on the Hugging Face Hub and consumed through the datasets Python library.

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