DeepSeek’s AI breakthrough rivals top models at a fraction of the cost, proving open source innovation is reshaping AI’s future. Is this an AI race or an open vs. closed battle?
I view it as the source code of the model is the training data. The code supplied is a bespoke compiler for it, which emits a binary blob (the weights). A compiler is written in code too, just like any other program. So what they released is the equivalent of the compiler’s source code, and the binary blob that it output when fed the training data (source code) which they did NOT release.
I view it as the source code of the model is the training data. The code supplied is a bespoke compiler for it, which emits a binary blob (the weights). A compiler is written in code too, just like any other program. So what they released is the equivalent of the compiler’s source code, and the binary blob that it output when fed the training data (source code) which they did NOT release.
This is probably the best explanation I’ve seen so far and really helped me actually understand what it means when we talk about “weights” for LLMs.