The challenge of natural language processing

Will Adobe survive the decompiling revolution? Reed Albergotti (Semafor and Future Proof), Kyle Chayka (Infinite Scroll, New Yorker), and Taylor Lorenz (User Mag) pull up to the roundtable, uncertain of how soon we’ll really see nuclear reactors on the moon—but sure that there’s ...  Show more

Why are the people most afraid of artificial superintelligence racing to build it? After interviewing more than 150 AI insiders, former New York Times tech columnist and podcast host Kevin Roose found a race fueled by fear, bitter rivalries, and one recurring belief: if we don’t ...  Show more

This episode reboots our podcast with the theme of Natural Language Processing for the next few months. We begin with introductions of Yoshi and Linh Da and then get into a broad discussion about natural language processing: what it is, what some of the classic problems are, and ...  Show more

AIs built on Large Language Models have wowed by producing particularly fluent text. However, their ability to do this is limited in many languages. As the data and resources used to train a model in a specific language drops, so does the performance of the model, meaning that fo ...  Show more

What does it mean to solve a problem in our universe? That's a trickier question than you might think, with some fairly high-stakes ramifications in the worlds of computing and even philosophy. In this episode of Stuff to Blow Your Mind, Robert and Joe explore the inherent log ...

In this episode, I'll be discussing the capabilities and limitations of ChatGPT, an advanced language AI model. I'll go over its power to understand and respond to natural language, and its applications in tasks such as language translation and text summarization. However, I ...