The Sequence Scope: Meta’s Clever Idea to Handle Uncertainty in ML models

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📝 Editorial: Meta’s Clever Idea to Handle Uncertainty in ML models

Interpretability is one of the most important areas of the new generation of machine learning (ML) platforms. Within the space of interpretability, nothing requires more attention than handling uncertainty in ML models. Uncertainty is one of the top factors that breaks the performance of ML models and one that is particularly difficult to model. After all, how can you effectively plan for things you haven’t seen before? Dealing with uncertainty in the real world forces us to think in terms of probabilities. Can we use probabilistic programming languages (PPL) to improve interpretability in ML models? Meta (Facebook) thinks we can and should.