Machine Learning Advocate is a weekly publication about machine learning and artificial intelligence. We make complex ideas easier to understand through patterns, mental models, and real-world examples, with a soft spot for Friday stories that remind us this field is human, weird, and wonderful.
Much of our work begins with a connection that catches our attention: the same pattern appearing in medicine and finance, a technical idea hidden inside an ordinary decision, or a model revealing something unexpected about how people think.
We follow those connections because they make difficult ideas feel less isolated. Once you can see the pattern underneath, a new concept becomes easier to understand, remember, and recognize somewhere else.
Machine Learning Advocate comes from years of hands-on technical work. There is already no shortage of material explaining the mechanics of AI and machine learning in detail, so we bring in technical depth when it helps make an idea clearer.
The rest of the time, we return to a few simple questions: What is really happening here? What does this help us understand? Where else does the same pattern appear?
We want readers to leave with more than an explanation. We want them to leave with a way of seeing.
We help you decide whether a problem is right for AI or machine learning before you reach for a model.
Tools change. Useful ways of thinking last. We help readers recognize the ideas that repeat across problems, industries, and everyday life.
We follow AI and machine learning into science, medicine, sports, business, culture, and the products people use every day.
Have a question, an idea, or a connection worth exploring? Send us a note.
