i donโt think you understand
you train a small model on scikit-learn
it gets 80% accuracy
you fine-tune a huggingface transformer
it gets 90% accuracy
you build a custom data pipeline
it gets 93% accuracy
you ensemble three models with voting
it gets 95% accuracy
you throw in feature engineering and SHAP
it gets 96% accuracy
you replace it with a gradient boosting tree
it gets 97% accuracy
you build a custom loss function for your niche problem
it gets 98% accuracy
you realize the labels were wrong
fix them, retrain
it gets 99% accuracy
you make a tiny architecture change
it beats human baseline
you remove half the parameters
it runs in real-time
you quantize the model
it runs on a potato
you distill it
it fits in a JavaScript bundle
you deploy it to edge
it autocompletes before users even type
you realize
you havenโt written a paper
but you built god
i donโt think you understand