EPISODE 170 | 10.11.2022 | 64 MIN

Why is causality important for artificial intelligence?

Michael explains, what we need to understand causal relationships, he shares examples where people - when analyzing data – often draw false conclusions on causality based on correlations, and he provides means to collect data to obtain best possible insights on causality.

The podcast is growing and we want to keep growing. That's why our German-language podcast is now available in English. We are happy about new listeners. 

Shownotes: 

More AI in the industry? --> in our book (german)

TAGS
  • #AI
  • #Siemens
  • #Xplain Data
  • #causality
  • #correlation
  • #data
  • #deep mind
  • #industrial AI
  • #industrial usecase
  • #machine learning
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