You are assisting a senior data scientist in optimizing a distributed training pipeline for a deep learning model. The model is being trained across multiple NVIDIA GPUs, but the training process is slower than expected. Your task is to analyze the data pipeline and identify potential bottlenecks. Which of the following is the most likely cause of the slower-than-expected training performance?
In collaboration with a professional administrator, you are tasked with optimizing power efficiency in an AI data center that runs multiple deep learning workloads. Which of the following actions would most effectively contribute to reducing power consumption without sacrificing performance?
You are managing an AI-driven autonomous vehicle project that requires real-time decision-making and rapid processing of large data volumes from sensors like LiDAR, cameras, and radar. The AI models must run on the vehicle's onboard hardware to ensure low latency and high reliability. Which NVIDIA solutions would be most appropriate to use in this scenario? (Select two)