Meta has announced the release of Bean Machine, a probabilistic programming system that ostensibly makes it easier to represent and learn about uncertainties in AI models.
Bean Machine can be used to discover unobserved properties of a model via automatic, “uncertainty-aware” learning algorithms. Probabilistic modelling, the AI technique that Bean Machine adopts can measure these kinds of uncertainty by taking into account the impact of random events in predicting the occurrence of future outcomes.
Compared with other machine learning approaches, probabilistic modelling offers benefits like uncertainty estimation, expressivity, and interpretability.
Read More: venturebeat
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