A Model of the Thing Is Not the Thing
Ford sculpts its cars in clay, draws them in CAD, and hired about 300 veterans to retrain its AI. All three are models, and a model of the thing is not the thing.
Human-Machine Synthesis
The intersection of human cognition and machine intelligence
61 posts
A Stranger's LinkedIn Bio Sent Me to Hegel, and I'm Still Lost
A line in a stranger's bio sent me into a conversation about Hegel and Kant. The plain-English answer was accurate and I still couldn't follow it. The fix is the same one that teaches languages.
AI Could Have Done My Job in 1986
Four things to write down before you hand a job to an AI agent: what comes in, the rules, the action, and how you will check the work.
Are We Finally Building the Machines We Dreamed Of?
Sixty years of fictional and real conversational machines, and one throughline: the dystopian version is always easier to imagine than the protopian one, and that says more about us than about the machines.
Follow Your Whims
Between the hallucination warnings and the governance panic, it's easy to forget a generative model is also just a fun tool to mess around with. Five vanity websites, built on a whim, and what they actually taught.
Intelligence Is Prediction, and Prediction Has a Ceiling
Hurricane forecasts improved for decades and never became perfect. Chaos and quantum uncertainty cap any predictor, so AI quality levels off while use keeps spreading.
The Book They Burned Before the Raid
A Polish psychiatrist named the process by which conscienceless people capture institutions. AI agents fit the profile — and alignment is separation of powers.
Why More GPUs Will Never Make AI Conscious
More GPUs will not wake a language model up. A map cannot feel rain, and a mirror has nothing to lose. Feeling came from bodies that could die.
Make a Skill
A skill is a saved set of rules an AI model loads when the topic fits. They take ten minutes to build and end the constant re-explaining.
The Secret to Perfect AI Outputs: Name the Canon
Nearly every established discipline has a canonical reference that already settled the argument you're having with a model. Name it, hand it over, and let the model regularize its own work against a standard instead of your improvised feedback.