From lab to life: Why translating AI advances to the real world is a major challenge

All the training data in the world can’t account for every possibility when AI systems interact with people and the environment.

By: Bo Wang, University of Mississippi, The Conversation

Outlets: The Conversation

Published: September 28, 2026

Words: 1,435

Last Updated: 2 weeks, 6 days ago

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By Bo Wang, University of Mississippi

Turning artificial intelligence research into real-world tools isn’t always straightforward, despite the remarkable progress in recent years ranging from self-driving cars to large language models. Systems that perform well in controlled lab settings often fall short when deployed in homes, in hospitals or on city streets.

Vision-based systems, for example, hold promise for improving safety, monitoring health and aiding rehabilitation. For example, a camera-based system could help a clinician assess …

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