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

Big Data LDN 2019 | Research vs. Reality in AI: Would You Trust Your Model with Your Life? | Heather Gorr
Course info
Level
Intermediate
Updated
Dec 13, 2019
Duration
26m
Table of contents
Research vs. Reality in AI: Would You Trust Your Model with Your Life?
Description
Course info
Level
Intermediate
Updated
Dec 13, 2019
Duration
26m
Description

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.

About the author
About the author

Big Data LDN is the UK’s largest data and analytics conference and exhibition.

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