Failure is an opportunity to learn

Failure is an opportunity to learn" has been strengthened to "No, rather, failure is an opportunity to learn.

• I wonder if this difference in nuance can be translated into English.

When AI deliverables work and when they don't.

• Learning from what went wrong is hard to share.
• Stable operation phase? The data and the work to be entrusted become more contextualized and harder to share once you enter the - Tools of the trade
  • When you start doing a lot of AI work, you can't talk about AI. - As quality improves, it becomes invisible.

Roughly twice as many failures as successes.

relevance - People who are missing opportunities don't see opportunities.

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