🎯 PaddlePaddle/PaddleOCR landed on trending. Worth a proper look.

🔗 https://github.com/PaddlePaddle/PaddleOCR
📝 Turn any PDF or image document into structured data for your AI. A powerful, lightweight OCR toolkit that bridges the gap between images/PDFs and LLMs. Supports 100+ languages.
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PaddleOCR is a leading OCR toolkit and document AI engine that converts PDF documents and images into structured, LLM-ready data with industry-leading accuracy. Its key features include intelligent document parsing, universal text recognition, and a developer-centric ecosystem. With support for 100+ languages and production-ready efficiency, PaddleOCR is the go-to choice for building intelligent RAG and Agentic applications.

The toolkit includes PaddleOCR-VL-1.6, a SOTA vision-language model that achieves 96.3% accuracy on OmniDocBench v1.6. It also features PP-StructureV3 for structure-aware conversion and PP-OCRv5 for universal text recognition.

PaddleOCR is designed for developers, researchers, and businesses looking to integrate AI-powered document parsing into their applications. With its one-click deployment and support for various hardware backends, PaddleOCR makes it easy to get started with document AI.

Get ready to unlock the power of document AI with PaddleOCR - the ultimate toolkit for converting unstructured data into actionable insights!

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🧠 Channel: https://t.me/GithubRe

🔍 Deep-diving into github/spec-kit — fresh off the trending list.

🔗 https://github.com/github/spec-kit
📝 💫 Toolkit to help you get started with Spec-Driven Development
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Spec Kit is an open-source toolkit that enables you to focus on product scenarios and predictable outcomes, rather than building every piece from scratch. It introduces Spec-Driven Development, where specifications become executable, directly generating working implementations.

To get started, you can install the Specify CLI using uv tool install specify-cli, then initialize a project with specify init my-project. You'll then establish project principles using the /speckit.constitution command, create a spec with /speckit.specify, and provide a technical implementation plan with /speckit.plan.

Spec Kit supports 30+ AI coding agents and offers a range of slash commands for structured development, including /speckit.constitution, /speckit.specify, /speckit.plan, /speckit.tasks, and /speckit.implement. You can also tailor Spec Kit to your needs through extensions and presets, which add new capabilities and customize core commands and templates.

Spec Kit is designed for developers, product managers, and anyone looking to build high-quality software faster. With its focus on executable specifications, Spec Kit streamlines the development process, reducing the time and effort required to deliver working implementations.
One-liner takeaway: Spec Kit revolutionizes software development by making specifications executable, empowering you to build high-quality software faster and more predictably.

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🧠 Channel: https://t.me/GithubRe

💡 NVIDIA/cosmos just hit the trending charts — here's why it matters.

🔗 https://github.com/NVIDIA/cosmos
📝 NVIDIA Cosmos is an open platform of world models, datasets, and tools that enables developers to build Physical AI for robots, autonomous vehicles, smart infrastructure, and more.
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NVIDIA Cosmos is an open platform for building Physical AI, providing a suite of omnimodal world models, datasets, and tools. Cosmos 3 is the newest model family, designed to jointly process and generate language, images, video, audio, and action sequences within a unified Mixture-of-Transformers architecture. It exposes two runtime surfaces: Reasoner for world understanding and Generator for world generation.

Key features include world understanding, world generation, and action modeling. The model architecture is based on a unified Mixture-of-Transformers (MoT) architecture, combining an autoregressive (AR) transformer for reasoning with a diffusion transformer (DM) for multimodal generation.

The platform supports various use cases, such as text-to-image, text-to-video, and image-to-video generation, as well as action policy and forward dynamics prediction. It also provides a range of pre-trained models, including Cosmos3-Nano and Cosmos3-Super, with different capabilities and sizes.

To get started, users can follow the Quickstart guide, which includes setting up a Hugging Face access token, installing required libraries, and running example scripts. The platform is designed for developers, researchers, and users interested in building Physical AI applications, such as robotics, autonomous vehicles, and smart infrastructure.

In summary, NVIDIA Cosmos is a powerful platform for building Physical AI, and Cosmos 3 is a cutting-edge model family that enables highly flexible input-output configurations - unleash the power of omnimodal world models to revolutionize Physical AI.

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🧠 Channel: https://t.me/GithubRe

Join our livestream with Marina Wyss, Senior Applied Scientist at Twitch, as we discuss how to break into AI Engineering in 2026.

Sign up for FREE and save your seat here: luma.com/qgz4g4r7

Why should you join?

Many people interested in AI Engineering are asking the same questions:

❓ Where do I start?
🤔 Do I need deep math first?
🧠 Should I focus on ML, LLMs, RAG, or AI agents?
🧭 How do I avoid wasting time learning the wrong things?
🚀 How do I go from learning to becoming hireable?

If you’re interested in AI Engineering but unsure how to approach it, this livestream is for you.

What you’ll learn

✦ What AI Engineering really is
✦ Where beginners should start
✦ What skills and topics actually matter
✦ Common mistakes to avoid
✦ Self-study vs bootcamp vs MSc
✦ How to think about becoming hireable in AI
✦ Practical advice from someone already working in the field

Sign up for FREE and save your seat: luma.com/qgz4g4r7

📌 Spotted on GitHub Trending: lfnovo/open-notebook — let's break it down.

🔗 https://github.com/lfnovo/open-notebook
📝 An Open Source implementation of Notebook LM with more flexibility and features
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The Open Notebook project is a private, multi-model, and 100% local alternative to Google's Notebook LM. It empowers users to control their data, choose from 18+ AI models, and organize multi-modal content. The platform offers a range of features, including advanced podcast generation, intelligent search, and context-aware chat.

To get started, users can follow the quick start guide and deploy the application using Docker. The project is built with Python, Next.js, and React, and offers a comprehensive REST API for custom integrations.

The target audience for Open Notebook includes researchers, students, and professionals who value privacy and data sovereignty. With its flexible and customizable design, Open Notebook is an ideal solution for anyone looking for a self-hosted and open-source alternative to traditional note-taking and research tools.

In short, Open Notebook is the ultimate tool for those who want to take control of their research and data - privately, securely, and with total flexibility.

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🧠 Channel: https://t.me/GithubRe

🔍 Deep-diving into Open-LLM-VTuber/Open-LLM-VTuber — fresh off the trending list.

🔗 https://github.com/Open-LLM-VTuber/Open-LLM-VTuber
📝 Talk to any LLM with hands-free voice interaction, voice interruption, and Live2D taking face running locally across platforms
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Open-LLM-VTuber is an innovative, voice-interactive AI companion that combines real-time voice conversations, visual perception, and a lively Live2D avatar. This project is designed to be a personal AI companion, offering a range of features and functionalities.

Key Features:
- Cross-platform support for macOS, Linux, and Windows
- Offline mode support for complete privacy and security
- Advanced interaction features, including visual perception, voice interruption, and touch feedback
- Extensive model support for Large Language Models, Automatic Speech Recognition, and Text-to-Speech
- Highly customizable with simple module configuration, character customization, and flexible Agent implementation

To get started, you can refer to the Quick Start section in the documentation. The project is under active development, with a focus on v2.0 development.

Audience:
This project is suitable for developers, AI enthusiasts, and anyone looking for a unique AI companion experience. It offers a range of features and customization options, making it an attractive choice for those interested in AI technology.

Technical Highlights:
- Modular design for easy extension and customization
- Support for GPU acceleration on macOS
- Integration with various LLM, ASR, and TTS solutions

In summary, Open-LLM-VTuber is a cutting-edge AI companion project that offers a unique blend of features, customization options, and technical capabilities. With its cross-platform support, offline mode, and advanced interaction features, it's an exciting project to explore. Join the community, contribute to the development, and experience the future of AI companionship - your personal AI friend is just a conversation away!

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🧠 Channel: https://t.me/GithubRe

🔥 jwasham/coding-interview-university is trending — and it deserves your attention.

🔗 https://github.com/jwasham/coding-interview-university
📝 A complete computer science study plan to become a software engineer.
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The jwasham/coding-interview-university repository is a comprehensive study plan for becoming a software engineer, covering everything you need to know for a technical interview at top companies like Amazon, Facebook, Google, and Microsoft. The plan is designed for those with some coding experience, and it's meant to be completed in a few months, with dedication and persistence.

The repository includes a step-by-step guide on how to use it, with tasks lists to track progress, and it covers a wide range of topics, from data structures and algorithms to system design and scalability. It also provides additional resources for further learning, including books, video series, and computer science courses.

The best part? You don't need to be a genius programmer to follow this plan - the creator of the repository, John Washam, is a self-taught software engineer who used this plan to get hired at Amazon. So, don't feel like you aren't smart enough - with dedication and hard work, you can achieve your goal of becoming a software engineer.

Get started with the jwasham/coding-interview-university repository today and land your dream job in no time - with persistence and dedication, the sky's the limit!

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🧠 Channel: https://t.me/GithubRe

🔥 github/copilot-sdk is trending — and it deserves your attention.

🔗 https://github.com/github/copilot-sdk
📝 Multi-platform SDK for integrating GitHub Copilot Agent into apps and services
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The GitHub Copilot SDK is a game-changer for developers, allowing you to embed Copilot's intelligent workflows into your applications. With SDKs available for Python, TypeScript, Go, .NET, Java, and Rust, you can define agent behavior and let Copilot handle the heavy lifting.

The SDKs communicate with the Copilot CLI server via JSON-RPC, managing the CLI process lifecycle automatically. You can install your preferred SDK using the provided commands and get started with the Getting Started Guide.

The GitHub Copilot SDK supports multiple authentication methods, including GitHub signed-in user, OAuth GitHub App, and BYOK (Bring Your Own Key). It's production-ready, following semantic versioning, and has a CHANGELOG for release notes.

Whether you're looking to speed up development or extend the functionality of Copilot, this SDK has got you covered. So, what are you waiting for? Get started today and unlock the full potential of GitHub Copilot - Automate your workflow, amplify your code.

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🧠 Channel: https://t.me/GithubRe