Practical AI · Thursday, August 6, 2026
The discussion clarifies the distinction between open-weight/open-source AI models and closed models. Open models release both software and parameters (weights/biases), allowing local execution, while closed models restrict access to these components, typically accessed via APIs.
“And maybe one distinction too that's really important with these models is some are what's called open weight or open source models. Some are closed models.”
“One is you have to have software that runs that model and actually executes it. The other thing is that you need parameters or weights and biases. These are just a data set of numbers that configures that software function to operate in the way that it operates.”
“Other models are not released either the software component or the data component of the weights are not released. And those are generally called closed models, often just accessed through a managed API, programmatic interface, or a chat interface or other interfaces.”
“And they keep that proprietary as their IP.”