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Hacker Podcast is an AI-powered project that turns top Hacker News stories into a Chinese podcast. It automatically fetches trending posts each day, processes the content with AI, and generates concise summaries before converting them into audio. This creates a hands-free way to stay updated on tech, startups, and developer discussions without reading long threads. Hacker Podcast combines content aggregation, natural language processing, and text-to-speech to deliver clear and digestible updates. Users can listen through web interfaces or podcast platforms, while also accessing written summaries for deeper reading. Built with modern web technologies, the project focuses on automation, speed, and accessibility. It supports continuous updates, allowing listeners to receive fresh insights daily. As an open-source tool, it also encourages community contributions and customization for developers who want to adapt or extend its workflow for similar AI-driven content pipelines.
Features
- Automatically fetches daily trending Hacker News posts
- Uses AI to generate concise summaries of articles and discussions
- Converts summaries into audio using text-to-speech
- Provides both podcast audio and readable text versions
- Updates content daily for continuous fresh insights
- Built with modern frameworks and supports open-source customization
Project Samples
