Learning effects: why getting more users isn't the only key to success

You've probably heard about network effects, but they aren't the only thing you need. Learning effects build the ultimate moat against your competition.

Learning notes from this episode:

  • You get better at speaking a language the more you practice and correct your mistakes. It is the same with algorithms: they get better with time and training.
  • The more time and data you have to train an algorithm the more accurate the algorithm’s output will be, and also, the more complex the problems it can solve.
  • “Learning effects can either capture or add value to existing network effects or generate value in their own right.” – Competing in the Age of AI, by Marco Iansiti and Karim Lakhani
  • Companies that have been training machine learning algorithms for longer are at a competitive advantage. Strong learning effects make it impossible for competitors to catch up.

Resources mentioned in this episode:

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(Photo by Tim Mossholder Unsplash)

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