Measuring AI efficiency goes beyond mere throughput 📈. A key metric that has gained significance in recent years is the "Predictive Accuracy Gain to Training Time Ratio" (PAGTTR). This metric assesses the efficiency of a machine learning model by comparing its predictive accuracy gain to the time saved during training.
For instance, if a model achieves 95% predictive accuracy with 10% fewer training hours than a baseline model, its PAGTTR would be calculated as follows: (95 - 90) / (100 - 90) = 5 / 10 = 0.5. This indicates a moderate level of efficiency, suggesting that the model has made a significant improvement in predictive accuracy while sacrificing a relatively small amount of training time.
However, if the same model achieves 98% predictive accuracy with only 5% fewer training hours, its PAGTTR would be (98 - 90) / (95 - 90) = 8 / 5 = 1.6. This indicates a higher level of efficiency, as the model has made a substantial improvement in predictive accuracy while saving a consi...
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