Why Did China Choose Open-source AI Models?

Eric Schmidt says China chose open-source and open-weight models because it was behind and needed users quickly. America's large models are mostly closed. Training one model can cost a hundred million to five hundred million dollars, so a closed lab asks why it would give that work away. Open source, as he describes it, builds a platform other people build on. Closed source aims at the end user. Open source has largely won in America as the foundation people build on, while the largest models stay closed.

China was willing to take the risk that others would copy the weights, and he says that bet looks like it is working because the projects are getting funded. Reflection AI has released a 500 billion parameter model, NVIDIA has a model of a similar size, and Google has Gemma 4, which can be downloaded. He calls the contest between open weights and closed weights the defining question. Closed-model labs in San Francisco say staying closed will keep them ahead. People on the Chinese side say opening the weights will keep them ahead.