Pandemic Machine Learning Pitfalls

News recommendation algorithms influence far more than what stories we click—they can shape our understanding of the world. In this episode, Kyle Polich speaks with Andreea Iana about responsible AI, filter bubbles, multilingual news recommendation, and her open-source NewsRecLib ...  Show more

What if you could simply tell a recommendation system what you want instead of relying on likes, dislikes, and watch history? Kyle Polich talks with Fuyuan Lyu about the DPR framework, which combines large language models and traditional recommender systems to give users direct c ...  Show more

In episode nine we talk with George Dahl, of  the University of Toronto, about his work on the Merck molecular activity challenge on kaggle and speech recognition. George recently successfully defended his thesis at the end of March 2015. (Congrats George!) We learn about how net ...  Show more

I speak with Dan Shiebler who works as a machine learning engineer at Twitter Cortex and at the same time, is doing a Ph.D. on applying category theory in machine learning. We discuss his work at Twitter, the importance of academics, and the future of machine learning. In this e ...  Show more

<span style="color: #333333;">Kevin is a Computer Scientist, part-time lecturer at Paul G. Allen School of Computer Science & Engineering, and research partner at OSAM. Our discussion with Kevin revolves around:
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Andy and Dave discuss the latest in AI news and research, including:

0:57: The Allen Institute for AI and others come together to create a publicly available "COVID-19 Challenges and Directions" search engine, building off of the corpus of COVID-related research.