There’s a reason why the saying “garbage in, garbage out” is still relevant—especially in AI.
Too many believe that just having lots of data is enough. It’s not.
The real power comes when you turn raw, messy data into something meaningful—a structured, logical, and informative story. That’s when AI starts to learn properly, and deliver real, valuable results.
Think of it like teaching children. You don’t just throw a pile of books at them and hope they learn. You guide them with structure, clarity, and logic. AI is no different.
Getting data into shape is 80% of the work in any AI project. Ignore that, and your model fails—no matter how fancy the architecture.
Good data isn’t optional. It’s everything.
I think Ryan Yockey captured it perfectly in this image.
