7 AI podcasts to tune into in 2018
Where else to start but with AIIA Netowork's own dynamic series? Our host, Seth Adler, is a highly experienced podcaster who encourages his guests to open up about all things AI, machine learning and intelligent automation - as well as general business excellence - in his frank and entertaining in-depth interviews.
The podcast is also available on iTunes.
AI has been described as “Thor’s Hammer“ and “the new electricity.” But it’s also a bit of a mystery – even to those who know it best. This podcast, produced by NVIDIA, the AI computing company, connects with some of the world’s leading AI experts to explain how it works, how it’s evolving, and how it intersects with every facet of human endeavor. Multiple episodes are released every month.
Kyle’s Polich's Data Skeptic podcast will keep you up-to-date on the news, topics and discussions of all things data science, machine learning and AI. His episodes discuss a relevant machine learning or data science problem and then critiques the application/topic. The discussions can be quite technical, but no doubt useful for analysts, data scientists and computer scientists who have at least some working knowledge or deeper exposure to the industry. Data Skeptic releases weekly and has a run time of 30–60 mins.
Released weekly with a run time of 30–60 mins, the show is hosted by Dan Faggella, CEO and founder of TechEmergence, a market research and consulting firm focused on artificial intelligence. His company, based in San Francisco, helps executives refine strategic procurement of AI and machine learning technologies. His podcast is more an introduction to AI designed for non-practitioners, executives and leaders who want to develop a very wide, yet shallow understanding of artificial intelligence applications.
A high-quality show that includes segments on technique explanation, listener questions and a main interview. The show brings together Katherine Gorman (a "story teller") and Ryan Adams (a machine learning academic). The interviews are with other academics from NIPS or similar conferences (recorded in batch) and can be very technical, so not for everyone. That said, it does a great job of rounding up unique insights into machine learning, which is sometimes lost in the wider topic areas of other AI and related tech shows.
Partially Derivative is a podcast about data science in the world around us. Episodes are a mix of explorations into the techniques used in data science and discussions with the field's leading experts. The podcast is a personal project hosted by Jonathon Morgan (software architect), Vidya Spandana (engineer), and Chris Albon (data scientist), whose expert takes shed some seriously interesting light on the topic.
This podcast series originally began with Sam Charrington giving a rundown of top stories in machine learning and artificial intelligence each week, making it very easy to digest. Charington has recently changed the format and now interviews top machine learning people from industry and academia. The interviews are eduicational for those looking for insider insight. It's also available on iTunes.