Misc.

We’re living in a golden age of documentation. Markdown files, detailed wikis, man pages, vendor PDFs, config examples—all right there, one ctrl+f away.\nAnd still, somehow, people would rather take a screenshot, toss it into ChatGPT, rub it like a fucking magic lamp and hope for the best.

I’ve been thinking about the usual characters / fauna you find in office life, and one in particular came to mind, the guy from Dilbert who carries a coffee mug around. That led me to reflect on a certain kind of workplace survivorship, where laziness and efficiency blur in interesting ways. I asked ChatGPT for some background and random insights (LLMs are quite big classification engines and they absolutely can find connections between things that seem unrelated), and ended up writing this:

I’ve been experimenting with Self-Similarity Matrices (SSMs) to explore structural patterns in music. SSMs are a visualization technique where each point in the matrix represents the similarity between two segments of a song, typically using spectral features like mel-frequency content. By overlaying this with a matrix derived from lyrics or spoken features (e.g., repeated words or syllables), it's possible to get a multi-layered view of how songs are structured — musically and linguistically.