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Research vs. Reality in AI: Would You Trust Your Model with Your Life?

by Big Data LDN

Big Data LDN 2019 | Research vs. Reality in AI: Would You Trust Your Model with Your Life? | Heather Gorr

What you'll learn

There are many considerations before deploying deep learning models into the real world, especially in safety-critical environments like automated driving, smart medical devices, aerospace, and biomedical applications. A deep learning researcher can achieve 99% accuracy on a deep learning model, but what about the edge cases? What if those edge cases represent someone's life? Is AI ready to move from research to reality? Model accuracy is only one part of a production-ready system, which also includes: model justification and documentation, rigorous testing, use of specialized hardware (GPUs, FPGAs, cloud resources, etc.), and collaboration between multiple people with various expertise related to the project and system. In this session, Heather Gorr will discuss the importance of explainable models, system design, and testing before an AI system is production-ready.

Table of contents

Research vs. Reality in AI: Would You Trust Your Model with Your Life?
26mins

About the author

Big Data LDN (London) is a free to attend conference and exhibition, hosting leading data and analytics experts who are ready to equip you with the tools you need to deliver your most effective data-driven strategy. Discuss your business requirements with 130 leading technology vendors and consultants, hear from 150 expert speakers in 9 technical and business-led conference theaters, and network with thousands of fellow data experts.

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