AI models use extensive data for training, and their energy consumption rises with the complexity and popularity of the model.
By 2030, AI model development will consume 13% of global power usage, contributing to 6% of global carbon emissions.
Enhancing storage, memory, and GPU pipeline with computational storage-enabled SSDs is crucial for achieving energy efficiency and sustainability goals.
Arm-based computing, with lower power consumption and scalability, is ideal for AI and machine learning tasks compared to traditional x86 architecture.
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