cover of episode Creating tested, reliable AI applications

Creating tested, reliable AI applications

2024/11/13
logo of podcast Practical AI: Machine Learning, Data Science, LLM

Practical AI: Machine Learning, Data Science, LLM

Chapters

The episode discusses the challenges of creating reliable AI applications, focusing on the transition from prototype to production and the importance of behavior testing.
  • AI applications often work well 80% of the time but fail 20% of the time.
  • Behavior testing and the flow from prototype to production are crucial.
  • The release of frontier models has slowed down, affecting expectations.

Shownotes Transcript

It can be frustrating to get an AI application working amazingly well 80% of the time and failing miserably the other 20%. How can you close the gap and create something that you rely on? Chris and Daniel talk through this process, behavior testing, and the flow from prototype to production in this episode. They also talk a bit about the apparent slow down in the release of frontier models.

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