Where I write down what I am reading and thinking about. Mostly AI at work.
This is the concept that convinced me small enough to do the job is often wiser than large and cumbersome.
This is a fine example of how being cleverer sometimes means doing less, in the right place.
This is the most fundamental cure for the chatbot that keeps making things up, which many people hit when bringing AI into their work.
One research result has stayed with me, because it proves that how we ask matters no less than the model itself.
This is the question I am asked most when a business starts using AI: do we need to retrain a model of our own? In most cases, the answer is not yet.
Every time an AI image turns out unexpectedly beautiful, I remember it was not painted the way we imagine. It was lifted out of a mess.
You hand a very capable person your company's entire file and ask them to find one detail in the middle. They read all of it, and remember the beginning and the end best.
Something small throws most people the first time they use AI: a model that can draft a whole contract miscounts the letters in a simple word.
Have you ever typed a vague search into Google, the keywords all wrong, and it still understood and gave you exactly what you needed?
Nearly every AI tool we use daily stands on one idea, published in 2017 by a group at Google under a very modest title.
In the early days of AI, every task needed its own model built almost from zero: one to translate, one to recognise images, another to filter spam.
The field has a stock phrase so blunt it sounds like a joke: garbage in, garbage out.
Mỗi sáng tôi gửi một việc nhỏ bạn làm được ngay hôm đó với AI. Đọc hết trong hai phút.