AI Weekly Malaysia

UK-based developer Alex Morley-Finch built Marlin, an open-source personal search engine that indexed ~560,000 homepages for ~$10 in cloud GPU time using under 1GB of storage. It uses a small OpenAI-compatible local LLM to generate summaries, categories, and tags for each page, with four components: a fetcher, a worker, a steward for filtering bad pages, and an API with web UI. His first crawl went wrong—90% corporate sites and docs—so he added a weighting system to prioritize pages he actually cared about, like portfolios and indie projects.

Why: If you want a search index scoped to your own interests—e.g., Malaysian indie dev portfolios, local startup pages, or niche technical blogs—this shows it's feasible for ~$10 and a weekend, with a crawl-weighting approach to avoid drowning in generic corporate content. The main unresolved pain point is LLM-generated tagging quality, which is worth discussing before you replicate the architecture.

A Show HN project by Alen (github: alenvelocity) renders all 43,252,003,274,489,856,000 Rubik's Cube permutations in a scrollable 2D/3D viewer, with presets like Superflip and Checkerboard and scale markers at 1.1×10¹⁹ through 4.3×10¹⁹.

Why: Not actionable for shipping work, but a neat example of compressing an astronomically large state space into a browsable UI — useful as inspiration for how to visualize and navigate huge combinatorial datasets in a web app.

A community-built page maps publicly accessible webcams along the path of the 2026 total solar eclipse using OpenStreetMap tiles and Leaflet 1.9.4 markers. The article text itself contains no prose — only map tile and marker image references — so details about which webcams are listed or how they were sourced are not available from the text.

Why: There is no actionable technical or business takeaway in the provided text. Builders interested in geospatial side projects could note the pattern of combining OSM tiles with Leaflet markers for lightweight map mashups, but the article does not explain implementation details.