Tag : AI Lifecycle
The growing environmental impact of AI, mainly in terms of energy-related calculations, can be mitigated by improving model performance, using renewable energy, optimizing hardware, and promoting responsible practices.
AI model optimization makes AI models faster, smaller, and more efficient by improving performance and reducing resource requirements. Key techniques include pruning, quantization, knowledge distillation, and hyperparameter tuning. This enables deployment on resource-constrained devices and reduces costs.
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