Closed Source AI
AI models where the architecture, weights, and training details are proprietary and not publicly available. Users access them only through APIs or products controlled by the developer.
Why It Matters
Closed-source models often lead on capability benchmarks. The open-vs-closed debate shapes the future of AI access, competition, and safety.
Example
GPT-4 and Claude are closed-source — you can use them through APIs but cannot download, inspect, or modify the underlying models.
Think of it like...
Like proprietary software (Microsoft Office) — powerful and polished, but you cannot see or modify the code that makes it work.
Related Terms
Open Source AI
AI models and tools released with open licenses that allow anyone to use, modify, and distribute them. Open-source AI democratizes access and enables community-driven improvement.
API
Application Programming Interface — a set of rules and protocols that allow different software applications to communicate with each other. In AI, APIs let developers integrate AI capabilities into their applications.
Foundation Model
A large AI model trained on broad data at scale that can be adapted to a wide range of downstream tasks. Foundation models serve as the base upon which specialized applications are built.
Model Weights
The collection of all learned parameter values in a neural network. Model weights are what you download when you get a pre-trained model — they encode everything the model learned.