Content I thought worth sharing. Some entries include my brief note.
This 2002 paper proposes a taxonomy for distinguishing near and far transfer of learning across knowledge domains, physical, temporal, functional, social, and modality contexts. It provides a framework for evaluating how learned skills, representations, and principles are applied in new situations.
An academic paper examining the emergence of large language model agents. The accompanying figure traces developments from early transformer architectures and language models to agent behaviors such as planning, negotiation, deception, and theory of mind.
A Nature paper associated with the AI Scientist research-automation project. From abstract: "We present The AI Scientist, which creates research ideas, writes code, runs experiments, plots and analyses data, writes the entire scientific manuscript, and performs its own peer review"
My note
The code is available here: https://github.com/SakanaAI/AI-Scientist
However, since it’s a bit old (compared to AI progress!), I guess it could be improved with claude code or codex.
How the Notes section is fed and what the different parts of each entry mean.
My note
I send links, posts, podcasts, and the occasional meme to a small Telegram bot. It writes a one-line summary, files the item here, and the site rebuilds. My own comment, when I have one, appears in this box. Everything here is also in the RSS feed.
My note
A paper published in 2002, and very relevant now! One research direction is to to apply and evaluate learning theories, developed years ago, on AI agents.