A thread you can test
What Open Source Actually Opens
3 notes move from the word to a real choice at work — understand it first, then decide whether to use it.
Each note stands alone, or becomes the next step in this thread.
THE QUESTION THIS PAGE ANSWERS
ANSWER FIRSTWhat is What Open Source Actually Opens, and which AI decisions does it change?
The file that months of training finally condenses into: what it looks like, how big it is, and why holding the weights means holding control This page keeps the related concepts, common mistakes, and practical notes in one reading thread.
First decide whether you are blocked by a definition, a choice, or verification; then choose the closest of the 3 notes below.
Start with “What Are Weights? Everything a Model Knows How to Do,” then restate the conclusion using your own task.
Do not treat every method in a topic as interchangeable. The answer changes with the input, risk, and acceptance bar.
THIS QUESTION THREAD
Put the word back inside the choice it changes.
What Are Weights? Everything a Model Knows How to Do
The file that months of training finally condenses into: what it looks like, how big it is, and why holding the weights means holding control
Real vs. Fake Open Source: How to Read a License
Three questions that locate how open a model is; the same yardstick applied to Qwen, Mistral, DeepSeek, Llama, and API-only models
Open Source Is a Business: What Each Vendor Is After
Six vendors' open-source strategies and paths to revenue; why the number of derivative models says more than download counts