Nameet
22K posts
new project — pdfmux pdf·mux / transitive verb to route a PDF to the best extractor for each page, and verify the result automatically. No single PDF tool wins at everything. PyMuPDF is fast but chokes on tables. Docling nails tables but crawls on simple text. Marker handles scans, but is overkill for digital docs. pdfmux selects the right tool for each page, audits the output, and re-extracts if confidence is low. It doesn't compete with these libraries; it orchestrates them. Tinkerin. Still early but you can try it: pip install pdfmux
Built out an Instagram / LinkedIn carousel generator off @claudeai + @paper MCP + @fal MCP. Give it a brand guidelines skill and off it goes to the races. Now let’s see if we can do the same with reels.
you’re like 6 prompts away from infinitely customizable personal agi. anthropic gave you a world class agentic harness for free. use it!!!
someone just open-sourced a tool that converts pdfs to markdown at 100 pages per second. 100% free. runs entirely on cpu. no expensive gpus needed.
Introducing 𝑨𝒕𝒕𝒆𝒏𝒕𝒊𝒐𝒏 𝑹𝒆𝒔𝒊𝒅𝒖𝒂𝒍𝒔: Rethinking depth-wise aggregation. Residual connections have long relied on fixed, uniform accumulation. Inspired by the duality of time and depth, we introduce Attention Residuals, replacing standard depth-wise recurrence with learned, input-dependent attention over preceding layers. 🔹 Enables networks to selectively retrieve past representations, naturally mitigating dilution and hidden-state growth. 🔹 Introduces Block AttnRes, partitioning layers into compressed blocks to make cross-layer attention practical at scale. 🔹 Serves as an efficient drop-in replacement, demonstrating a 1.25x compute advantage with negligible (<2%) inference latency overhead. 🔹 Validated on the Kimi Linear architecture (48B total, 3B activated parameters), delivering consistent downstream performance gains. 🔗Full report: github.com/MoonshotAI/Att…
