Improving Natural Language Understanding through Adversarial Testing

On-demand

Summary

Artificial intelligence is one of the most disruptive technologies of our time. New applications and use cases are being developed at a stunning pace, extending into virtually every industry. But, according to Stanford Professor Christopher Potts, while we are living in a golden age of AI research, major breakthroughs are still ahead of us.

Join Professor Potts for an overview of his course, Natural Language Understanding (XCS224U). He will focus specifically on the topic of "adversarial testing" in which developers challenge top-performing systems with examples that they suspect will trip up the systems, thus revealing their weaknesses.

We will also hear from students who have completed the course. They will present original projects that they developed in the course, and describe how the course structure guided their research.

You Will Learn:

The current state of the development of Natural Language Understanding
How adversarial testing can be utilized to improve natural language systems
How the framework of XCS224U can guide you to develop an original project
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Presented By

The Stanford Artificial Intelligence Professional Program

Questions?

[email protected] | 650-204-3984

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Christopher Potts

Christopher Potts is a Stanford Professor of Linguistics and, by courtesy, of Computer Science, and Director of the Center for the Study of Language and Information (CSLI) at Stanford. In his research, he develops computational models of linguistic reasoning, emotional expression, and dialogue. He is the author of the 2005 book The Logic of Conventional Implicatures as well as numerous scholarly papers in linguistics and natural language processing.

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