Most people are aware that any AI system is only as good (accurate and unbiased) as the data that was used to train it. What people often overlook is that “data” isn’t a monolith, and neither is AI. The differences in data types and structure impact how they can be used for AI. And, the different types of AI impact how you need to structure your data.

This conversation explores:

- How organizations can connect the dots from data to AI.
- The questions organizations should be asking about data/AI technologies in order to gain maximum benefit from both.
- How different AI models require different data.
- How customers/users play a role in your data/AI strategy.

Similar episodes:

- Beyond generative AI: https://www.soundcloud.com/catalyte-sourcing-for-innovation/beyond-generative-ai
- AI risk management: https://www.soundcloud.com/catalyte-sourcing-for-innovation/ai-risk-management
- Probabilistic vs deterministic systems: https://www.soundcloud.com/catalyte-sourcing-for-innovation/probabilistic-vs-deterministic-systems
- What AI do you need?: https://www.soundcloud.com/catalyte-sourcing-for-innovation/what-ai-do-you-need

For more information on Catalyte’s AI advisory services, visit: https://www.catalyte.io/services/solutions/ai-advisory-services/

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