𝗔𝗜 𝘃𝘀 𝗠𝗟 𝘃𝘀 𝗗𝗲𝗲𝗽 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝘃𝘀 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜

AI, Machine Learning, Deep Learning, and Generative AI are not separate things. They are circles nested inside each other.

I am a product manager. I am learning to become an AI PM in public. This is my first lesson.

Here is how the layers work:

• AI: Machines doing smart tasks. This includes old systems that follow human rules. Example: A thermostat. • Machine Learning (ML): A type of AI that learns patterns from data instead of rules. Example: Your email spam filter. • Deep Learning: A type of ML using neural networks. It works well with images and voice. Example: Face unlock on your phone. • Generative AI: A type of deep learning that creates new content like text or images. Example: ChatGPT or Claude.

Generative AI sits inside deep learning. Deep learning sits inside machine learning. Machine learning sits inside AI.

When people say they want to add AI to a product, they are often too vague. Ask these questions instead:

  • Which layer do we need? A simple rule might work better than a complex model.
  • Do we have enough data? ML and deep learning require massive amounts of data to work.
  • Is generative AI the right tool? Sometimes you only need to predict a number or classify an item.

Stop nodding along to the hype. Use this map to ask better questions.

Quick check: Where does a spam filter sit? Where does Claude sit? Tell me in the comments.

I am documenting my journey from a non-tech PM to an AI PM. Follow me to see every lesson.

Source: https://dev.to/ruturajpm/ai-vs-ml-vs-deep-learning-vs-generative-ai-the-map-that-finally-makes-it-click-2l0a

Optional learning community: https://t.me/GyaanSetuAi