Understanding Neural Networks

In the final episode of our Recommender Systems season, we explore the growing questions of trust, manipulation, privacy, fairness, sustainability, and user control. From fake reviews and shilling attacks to explainable recommendations and user-selected algorithms, we look at wha ...  Show more

In part two of the Data Skeptic Recommender Systems season finale, Kyle asks a deceptively difficult question: what should recommender systems actually optimize for? Drawing on conversations from across the season, the episode explores engagement, filter bubbles, popularity bias, ...  Show more

Why is it so hard to define concepts like artificial intelligence and machine learning? What do those even mean? And how does it work? We take a very high level look at AI and machine learning.

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Why is it so hard to define concepts like artificial intelligence and machine learning? What do those even mean? And how does it work? We take a very high level look at AI and machine learning. Learn more about your ad-choices at https://www.iheartpodcastnetwork.comSee omnystudio ...  Show more

The latest on the philosophy, science and technology of AI and AGI. ChatGPT, Deep Learning, Neural Networks and Large Language Models (LLMs). What do we know? Where is it going? 

TechStuff listener Nate wanted to know about natural language processing. How can computer scientists teach machines to understand human language and why is it so hard to do? Learn more about your ad-choices at https://www.iheartpodcastnetwork.comSee omnystudio.com/listener for p ...  Show more