Long-form analysis at the intersection of AI and life sciences — all spells, sorted by time.
agentic-markdown embeds variable substitution and conditional blocks into Markdown syntax. A neat concept, but with only 15 GitHub stars, no loop support, and mature alternatives like Jinja2 already covering the same ground, it is hard to recommend for any serious workflow.
An assistant professor shares how an AI-powered literature management pipeline transformed manual PubMed searching into an automated digestion workflow, systematically processing 50+ academic papers per week through tiered reading.
Auto-PPT turns each slide into a React TSX file that AI agents can read and edit directly, no GUI or screenshot loops needed. Solid concept and well-designed agent protocol, but still early-stage (29 stars, 0 releases). Worth tracking, not yet worth depending on.
Starting from the everyday experience of watching ChatGPT type out words one by one, this article uses six everyday analogies to break down KV Cache, Paged Attention, Flash Attention, GQA, Continuous Batching, and Speculative Decoding — explaining how large language models serve more users faster on the same GPU.
docmd turns any Markdown folder into a production-ready docs site with one command, ships at ~18kb initial payload, and includes a built-in MCP Server so AI agents can search and read your docs natively. Best for developers and researchers who want fast, lightweight documentation without configuration overhead.
How can academic researchers use AI tools to speed up literature management, paper writing, statistical analysis, and presentations? A practical perspective from an assistant professor with four concrete entry points.