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Use energy efficient AI/ML models

Description

Large AI/ML and deep learning network models have a significant carbon footprint. Evaluate and use alternative, more energy efficient, models that provide similar functionality.

Solution

Evaluate energy efficient AI/ML models for development and inference. For example, DistilBERT provides similar functionality to the BERT model, running 60% faster while preserving 97% of BERT's performance. GPT-Neo 125M provides balanced results for energy consumption and accuracy compared to GPT-J 6B or GPT Neo 2.7B models.

SCI Impact

SCI = (E * I) + M per R

Software Carbon Intensity Spec

Using energy efficient AI/ML models impacts SCI as follows:

  • E: Having an energy-efficient AI/ML model would provide efficient resource utilization and reduces the energy consumption of the compute resources and consequently, the E number should decrease.

Assumptions

None

Considerations

None

References