AI-Radar

works, reading many books and practicing via google Colab, Hugging Face and Kaggle, developing many AI related Apps, using VS Code . Here my small contribution.

Love this concept. How long have you been building it ?

Nice positioning for people building local-first AI stacks. A useful next step could be a filter by hardware class (e.g., M-series Mac mini vs GPU workstation) so readers can map model news to realistic deployment options.

interensting concept

Love the idea, keep it up!

interesting product!

This is a well-designed tool with a clear use case. The user interface looks clean and straightforward, making it easy for new users to get started. Would love to see more integrations in the future.

eing an AI Enthusiast, I started studying how LLMs works, reading many books and practicing via google Colab, Hugging Face and Kaggle, developing many AI related Apps, using VS Code . Here my small contribution.

interensting idea and implementation

The fully AI-managed pipeline is a compelling architecture choice — using Ollama locally for article coordination while offloading other logic to a cloud LLM is a pragmatic way to balance cost and capability. The hardware filter idea from comments above is spot on: a section grouping news by deployment context (edge, M-series, consumer GPU) would make this much more actionable for builders. The Chroma DB integration for semantic search over the archive is the killer feature here — would love to see a public API endpoint for querying the news archive.