Understanding the differences between probabilistic and deterministric AI will help manufacturers make more informed choices and achieve measurable results.

Probabilistic models, such as hidden Markov models or Bayesian networks, are commonly used to model biological data. Much of their popularity can be attributed to the existence of efficient and robust ...

Decision-making inherently involves cause–effect relationships that introduce causal challenges. We argue that reliable algorithms for decision-making need to build upon causal reasoning. Addressing ...

Jennifer Simonson is a business journalist with a decade of experience covering entrepreneurship and small business. Drawing on her background as a founder of multiple startups, she writes for Forbes ...