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Bringing AI into Healthcare
Learn about the challenges of integrating AI into healthcare in a way that maximizes its potential while also protecting patient safety and privacy.

NLU Project Showcase and AI Program Q&A
Listen in as learners present original projects that they developed in our Natural Language Understanding professional course.

How Artificial Intelligence Can Improve Healthcare
AI researchers are actively developing models that can innovate health and medicine, but hospitals need to know that they will be cost-effective and beneficial for patients. That’s where usefulness analysis comes into play.

Turning data into value: building an AI-enabled organization
Learn why AI has become such a high priority and how business leaders can think about developing and adopting AI solutions.

AI Ethics
As AI is integrated into more aspects of modern life it's critical to consider the ethical implications of its use.

Lifelong learning and boundless curiosity
A conversation with Catherine Wang, AI Professional Certificate

Autonomous Robotic Manipulation
Reflecting on her journey as a researcher in vision-based robotic grasping, Assistant Professor Jeannette Bohg discusses what we can learn from the failures and limitations of existing approaches to autonomous robotic manipulation.

Design & AI: Envisioning AI-augmented Products
For every AI success story there are numerous spectacular failures. So, how do you ensure that you're team is pursuing the best opportunities?

How autonomous systems are changing day-to-day life in the U.S.
Explore the practical and ethical implications of automation.

How to use AI to enhance user experience
Learn how to design better, smarter user interactions by integrating artificial intelligence into your user experience.

Looking ahead toward the future of robotics
Learn how we create robots and autonomous systems that can interact with humans and safely navigate our world.

Improving Natural Language Understanding through Adversarial Testing
Join Professor Christopher Potts for a discussion of how adversarial testing can improve natural language systems.