Ever feel like you’re drowning in a sea of AI acronyms? LLM, RAG, NLP… it can feel like everyone’s speaking a different language!
I just stumbled upon a super helpful post from a LinkedIn creator that cuts right through the confusion. This savvy professional put together a simple glossary to get anyone up to speed, and I was blown away by how clear it is.
This is a game-changer for anyone feeling a little lost.
The mind behind it shared a bunch of terms, but here are a few of my favorites that really nail the basics:
- 📌 Model: The expert describes this as the final program that can do tasks after learning from data.
- 📌 Training: This is the process where the AI learns from examples to get better at its job. Think of it like studying for a test!
- 📌 Dataset: A big collection of information that the AI learns from. The bigger and better the dataset, the smarter the AI.
- 📌 Token: The post’s author explains these are the words or pieces of words an AI uses to read and write text.
- 📌 Bias: This is a crucial one. It’s when an AI unfairly prefers some answers over others, usually because of skewed data it was trained on.
I think this is fantastic because it makes complex ideas accessible to everyone. You don’t need a PhD to understand the basics of the tech that’s changing our world.
The original poster shared a list of 40 terms in total, plus a handy infographic.
If you want to get 10x smarter on AI today, you’ve got to check out the full post from the person who shared it for the complete list! 👇