Debunking common misconceptions
30 posts
Halfway through a long session, stop and ask for the five-year-old version. You find out whether you are still working on the same problem — and whether the reasoning underneath survives being said in short words.
How you configure your AI assistant — what you make it call you — says nothing about the AI. It's a bumper sticker. You're the truck owner.
LLMs say "honestly" most where they're most likely to confabulate. Here's the mechanism — and why it backfires exactly like a sociopath's professions.
Losing your temper at a model does not produce a worse version of the same answer. It produces a different kind of answer — one built to end the argument rather than solve the problem.
Karpathy built the foundations of modern AI and says he can't keep up with it. That's the most credible signal the field has produced.
Arnold's most famous line is a Spanish phrase in an English-language film spoken in a thick Austrian accent. What it tells us about how language acquisition actually works — and how you can learn from his mistake.
Hand the model a list of phrases it must not use. It turns a vague complaint into a rule the machine can follow — and mine is at the bottom of this piece, all hundred and fifty lines of it, free to copy.
A German court ruled Google liable for AI-generated defamation. The slippery slopes are real. So is the principle behind the ruling.
In 2013 the talking point was coal. Now it's water. The structure of the argument is identical. So is the physics problem with it.
AI is making cognitive labor cheap. The meritocracy was built on it being scarce. Something has to give — and for once, that might be good news.