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:

• Sophia Matveeva's LinkedIn
• Listen to The Business of AI podcast episode with Harvard Business School Prof Marco Iansiti
• Tech for Non-Techies YouTube channel

To attend Tech for Non-Technical Founders in London on May 10 2022 in London, book your ticket here and use PODCAST to get £5 off the price.

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