INSIGHTS
Notes on technology trade-offs, the problems we meet in the field, and how we read the industry. Each article is maintained once and published to both the website and our WeChat account.
Filter by topic, or simply scroll through everything.
Most intelligence projects open with a discussion about model selection. What actually stalls them is that the data was never flowing steadily in the first place. Onboarding isn't a transitional step — it's the precondition for everything that follows.
Model decay is almost never an algorithm problem. It's that the environment changed and the model didn't. This article explains what data drift actually looks like in engineering terms, and how to turn it into a routine you can manage.
Replacing the hardware isn't intelligence, and displaying the data isn't decision-making either. These three misconceptions appear most often at project kick-off, and they are the quickest way to spend a budget in the wrong place.
