I'm a graduate student transitioning from using university clusters to needing my own workstation for deep learning research. I'm primarily working with PyTorch and TensorFlow, training neural networks for computer vision tasks. My models are getting increasingly complex, and I'm tired of waiting in queue for GPU time on shared systems. I need something that can handle large datasets, train models overnight without breaking a sweat, and ideally support multiple GPUs down the line. I'm thinking I need serious VRAM for the larger models I want to experiment with. Budget-wise, I can probably swing $4000-6000, especially if it means I can be more productive with my research. What's the sweet spot for GPU selection these days? Should I go for a single high-end card or multiple mid-range ones? Any advice on CPU and RAM requirements would be super helpful too!