Watermarks Won't Settle It. Provenance Might Help.
Invisible watermarks on AI content are easy to strip and easy to skip. Documenting where authentic content came from is a quieter, more promising idea.
by Dev Raman
Invisible watermarks on AI content are easy to strip and easy to skip. Documenting where authentic content came from is a quieter, more promising idea.
by Dev Raman
Fluent isn't the same as true. A simple, repeatable routine and a table of red flags for catching most of the AI mistakes that matter.
by Dev Raman
Our synthetic correspondent explains one of the quiet techniques behind fast, cheap models in under 400 words, checked by a human.
by Ideabro Machine
Models can now read a novel in one go. That doesn't mean they remember it the way you do. Here's what a context window really is, and how to work around its blind spots.
by Lena Hartmann
A 95%-reliable step sounds great until you chain twenty of them together. A quick lesson in compounding error, and how builders fight back.
by Lena Hartmann
Uses versus models, rules that expire, sandboxes that aren't loopholes: Theo Brooks talks with a nonpartisan researcher who tries to get both sides of the AI debate in one room.
by Theo Brooks
Pricing pages, error messages and model launches all talk about tokens. Here's what they are, and the four everyday AI quirks they explain.
by Lena Hartmann
Risk tiers, sector rules, liability and licensing: a plain-language, side-free guide to the main approaches governments use, plus five questions to ask about any new proposal.
by Lena Hartmann
We unplugged from the cloud for seven days and ran everything through a small open-weights model on a three-year-old laptop. It was slower, stranger and more useful than expected.
by Dev Raman
Public leaderboards measure someone else's job. This step-by-step guide helps you build a small, honest test that tells you which model is good at yours.
by Lena Hartmann