最新款的 MacBookpro，哪一个配置最有性价比，不打游戏，专注 ai 应用的研发

For developing AI applications on a MacBook Pro, especially if gaming is not a priority, the focus should be on configurations that maximize performance for machine learning tasks. Based on the content from WWDC, here are some considerations:

1. Apple Silicon: The latest MacBook Pros with Apple Silicon, such as the M3 Ultra, are highly recommended for AI development. They offer powerful GPUs and unified memory architecture, which are beneficial for training and running large models efficiently. The unified memory allows both the CPU and GPU to access the same memory, which is advantageous for machine learning tasks.

2. Unified Memory: A configuration with a large amount of unified memory is crucial. For instance, the M3 Ultra with 512GB of unified memory is highlighted for its ability to handle large models, such as those with hundreds of billions of parameters, directly on the device.

3. Framework Support: Apple Silicon supports popular machine learning frameworks like PyTorch, TensorFlow, JAX, and MLX, which are optimized to take advantage of the hardware acceleration provided by Apple Silicon.

4. Performance Enhancements: Sessions like Train your machine learning and AI models on Apple GPUs discuss improvements in training efficiency and support for transformer models, which are relevant for AI development.

In summary, for AI application development, a MacBook Pro with the latest Apple Silicon (such as M3 Ultra) and a large amount of unified memory would provide the best performance and value.