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Building Products You Can Trust in a Probabilistic World

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  • Artificial Intelligence

About This Event

As AI moves from experimentation into real-world implementation, organizations need approaches that make systems more observable, measurable, and accountable without losing the flexibility that makes AI valuable in the first place.

What you’ll take away

  1. Why deterministic thinking breaks down in probabilistic systems

  2. The differences between traditional software and AI-enabled systems

  3. How orchestration frameworks can reduce risk while preserving flexibility

  4. Which metrics matter most for measuring AI reliability, including grounding, task success, and hallucination rates

  5. How observability helps teams understand and monitor AI behavior

  6. Practical approaches for determining whether an AI system is ready for production

  7. Real-world examples of trustworthy AI systems in practice

Presenters

  • Brian Graves

    Vice President, Engineering

    Forum One

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