Podcast interviews are one of the most effective tactics you can deploy when it comes to establishing your company as an industry thought leader.
In a typical media interview, you may speak with a journalist for 30 minutes and see that conversation reduced to a single quote buried deep in a long article.
With podcasts, you have the opportunity to speak directly to the audience for an extended period of time. They give you the opportunity to tell your story, share your expertise, and spread your vision for the future.
Our research team has put together a list of some of the top AI and machine learning podcasts to consider getting booked on. We recommend sorting through and finding podcasts where you can add value. Then, come up with a pitch and reach out to see if they would be open to having you as a guest.
Daniel Faggella hosts Artificial Intelligence in Industry, which brings listeners a realistic picture of how artificial intelligence is — or isn’t — shaping business today. Each episode drops weekly, with a new interviewee each week telling listeners how machine learning is impacting their company and industry. No sector is off-limits, as episodes to date have covered healthcare, manufacturing, education, the automotive industry, and the legal sector, to name a few.
The show doesn’t require a massive time commitment — 20 to 30 minutes once per week where listeners will hear directly from industry professionals how AI is forming the future of their industry.
AI Today is a weekly podcast focused on the latest news about artificial intelligence. Co-hosts Kathleen Walch and Ron Schmelzer check on the status of big-picture AI trends in episodes like ‘AI Adoption in Government and Beyond’, and ‘AI in the UK and Beyond’. Their use case series takes an industry-by-industry approach to examining AI’s potential role in education, law enforcement, and beyond. They also cover events like Amazon’s re:MARS conference.
Episodes tend to be on the shorter side — 15 to 20 minutes — with longer episodes lasting around 40 minutes.
AI With AI is a weekly podcast hosted by Andy Ilachinski and David Broyles. The hosts are about substance over variety, dissecting topics over multiple episodes to ensure the listener gets the full picture. Their ‘Shadow of What is Going to Be’ is a two-part exploration of the latest developments in facial recognition AI. Other multi-part episodes include ‘The Fake that Launched 1,000 Clips’ and ‘Who Manipulates the Manipulators?’.
AI With AI goes deep into how artificial intelligence is being implemented in the private and public sectors, where that implementation has hit snags, and what it means for our future. Each episode ranges from 15 minutes to around an hour in length.
AI with Lex Fridman is a weekly podcast that typically runs between one to two hours long. Each episode shines a spotlight on a new guest, with a roster that includes high-ranking employees at Microsoft, Spotify, the Google Self-Driving Vehicle team, and a theoretical physicist from Caltech — all these people have been on the show since July of this year.
The direction of each episode is dictated by the guest, which means listeners are exposed to a variety of topics from authorities with firsthand industry experience and knowledge the topic of the day. You can’t ask for much more than that from an AI podcast.
Artificially Intelligent is an audio forum to discuss the intersection of artificial intelligence, business, and the greater economy. Co-hosts Christian Hubbs and Stephen Donnelly center each episode around a narrative or topic that is prominent in mainstream discourse — universal basic income, the status of facial recognition technology, and the role of AI in sports analytics, to name a few.
There seems to be no set schedule for episode releases, as the time between episodes can range from a few days to two months. The typical show runs between 30 minutes and an hour long.
Paul Middlebrooks hosts Brain Inspired, a show that blends the fields of AI and neuroscience into one podcast. Each episode centers around the guest of the day, whether it’s a neuroscientist, a professional who works with AI, or someone in the fields of psychology or philosophy. Brain Inspired delves beyond the AI box, helping listeners better understand how emerging artificial intelligence is impacting our psyches.
Episodes are released on a rough ten-day schedule, with each show spanning somewhere between one and two hours. These are in-depth interviews, and the intended audience likely has some preexisting knowledge of AI and neuroscience.
Concerning AI takes a different approach than most AI podcasts, as it uses a central question as the launching pad for the show: ‘Is there an existential risk from Human-level (and beyond) Artificial Intelligence? If so, what can we do about it?’
Hosts Brandon Sanders and Ted Sarvata explore this question through interviews with guests and a dissection of the latest development in AI technology. In-episode discussions include ‘when human-level AI will exist (if ever)’, ‘The Seven Deadly Sins of Predicting the Future of AI’, and ‘Can Neuralink Save Us?’. Listeners can expect one to three new episodes per month, with each show runing around 40 minutes.
Data Crunch is the podcast from The Data Crunch Corporation, a company that provides data analytics business-level solutions. The podcast relies on the industry knowledge of co-hosts Ginette Methot and Curtis Seare, who chat with a slew of guests about ‘Running a Successful Machine Learning Startup’, ‘How to Win Hearts and Minds as a Data Leader’, and other AI/ML-related topics.
This is a podcast for do-ers looking for advice on how to begin, accelerate, or improve their professional path in data-driven sectors. Each episode runs in the 12-25 minute range and a new show arrives each month.
DataFramed is hosted by Hugo Bowne-Anderson and sponsored by interactive learning company DataCamp. The show is currently on hiatus, but its return is scheduled for Summer 2019 (clock’s ticking!). When it returns, you can expect a new guest each episode. Discussions usually center around data science. Instead of trying to pin down definitions of what exactly data science is (snooze), Bowne-Anderson chats with guests who personify what data science looks like in real life — data scientists, inventive scientists, and the like from companies such as AT&T and the BBC.
Each show is about an hour-long, and the new episodes arrived weekly pre-hiatus.
Host Francesco Gadaleta covers topics under the umbrella of technology, and machine learning specifically, on the weekly podcast Data Science at Home. Episodes range anywhere from 12 to 45 minutes, give or take, and noteworthy episode topics include ‘Beyond dep learning’, ‘Why do machine learning models fail?’, and ‘The dangers of machine learning and medicine’. This is a podcast aimed at those who want to expand their horizons on the topic of machine learning, plain and simple.
Data Science Salon is a data science podcast with a casual vibe. Topic genres include machine learning, data science (obviously), and AI, with a specific focus on how these technologies are being implemented and improved in the business world of today. The first ever Data Science Salon episode went live on July 12th. Guest host Q McCallum spoke to two data science specialists from Viacom and Nielsen, two well-know companies you’ve likely heard of.
The first episode ran just over an hour, and it’s fair to expect a similar format and runtime in upcoming episodes.
Itunes Link: podcasts.apple.com/us/podcast/id1472749960
Data Skeptic is the weekly podcast from the publication of the same name. The show aims to take a skeptical view of AI. Host Kyle Polich sometimes interviews guests about topics like deep neural networks, theory of mind, and the Endangered Languages Project, and sometimes fills the time on his own with overviews of AI-related concepts and stories. Interview episodes typically run between 20 and 30 minutes, while solo episodes tend to be a bit shorter.
Data Stories focuses primarily on data visualization and analytics, with co-hosts Enrico Bertini and Moritz Stefaner chatting up guests about the topic of the day. Some episodes focus on the state of data visualization software (‘A New Generation of DataViz Tools’), others focus on coverage of live events (‘IEEE VIS 2018’), while some shows are spent dissecting concepts related to data visualization and analytics (‘Visual Perception and Visualization’, ‘Storytelling with Data’).
Episodes typically run between 30 minutes and an hour, while yearly review shows trend towards the two-hour mark. Historical output is one or two episodes per month.
Disclaimer: Freakonomics Radio is not exclusively an AI podcast. You probably already knew this. But as work becomes increasingly intertwined with machine learning and artificial intelligence, the overlap between AI discussion and Freakonomics Radio grows.
Stephen J. Dubner co-authored the Freakonomics books, so its fitting that he hosts the radio series. Episodes span between 35 minutes and just over an hour, with new episodes launched each week. Even without episodes alluding directly to AI, you’ll find that many of the podcast’s discussions about the future of the workforce inevitably touch on the role AI could play in our future economy.
The Future of Data is a podcast from AnalyticsWeek, a digital publication centered around, of all things, analytics. Though the show has veered from its onetime status as a weekly podcast, listeners with a thirst for data ops, AI, and the future of data in general should give the show a try. Interviews with professionals in IT and data analytics bring an air of authority to the show.
Episodes typically run somewhere around an hour, and topics vary from show to show, though most fall under the umbrella of “the future of data”.
Staying true to the “101” element of its title, Learning Machines 101 is a monthly introductory course to artificial intelligence and machine learning. It wouldn’t be off the mark to characterize Learning Machines 101 as a “how to” podcast for the artificially intelligent systems that increasingly populate our world. A rundown of episodes includes ‘How to Build a Machine that Learns to Play Checkers’, ‘How to Design Gradient Descent Learning Machines’, and ‘How to Catch Spammers Using Spectral Clustering’. The typical episode runs between 20 and 30 minutes long and are hosted by Dr. Richard Goldman.
Hosts Ben Jaffe and Katie Malone cover the latest in machine learning and data science in this weekly podcast. Unlike many AI podcasts, Jaffe and Malone typically run the show without assistance from guests — it’s a good thing that their chemistry is strong enough to carry episodes that typically come in around 20-25 minutes.
Occasionally an interviewee will drop in, but the typical episode finds the hosts tackling subjects like ‘Google X, and Taking Risks the Smart Way’, ‘The Black Hole Algorithm’, and questions such as ‘Are machine learning engineers the new data scientists?’.
Machine Learning Guide is a podcast for those seeking actionable instruction. Host Tyler Renelle describes the show as a “middle-level” overview of machine learning, describing the target audience as aspiring developers but also anybody interested in the fundamentals of machine learning. The show is also described as a “syllabus” that can guide listeners through the big-picture map of machine learning and development. Most episodes run around an hour in length, and are released on a non-fixed schedule.
Machine Learning is the podcast from digital publication Software Engineering Daily. There is no set schedule for new episodes, but their runtime is consistent, ranging between 50 minutes and an hour and ten minutes. The content of each episode skews toward the technical, with show titles including ‘WebAssembly on IoT’, ‘Stripe Machine Learning Infrastructure’, and ‘Computer Architecture’. This is not the podcast for those looking for surface-level information or a news-centric approach to machine learning, but instead for those looking to learn the deeper intricacies of ML.
Ahh, simplicity. Many podcasts have made their mark dumbing down seemingly complex topics for the average Joe. Perhaps “dumbing down” isn’t the best term to describe the Making Data Simple podcast, but it is one of the more accessible AI-centric shows, and it’s sponsored by perhaps the biggest name in AI today: IBM.
Host Al Martin is the VP of Data and AI Development at IBM, credentials that establish him as an authority — so794 any guests of the show is a cherry on top of the audio AI sundae. The ‘Stories From the Field’ segment brings a dose of reality from industry professionals, while ‘The Art of Teaching AI’ takes a look at the technology through the professorial lens. The weekly, roughly half-hour-long podcast grants access to guests and resources that most shows don’t offer, and it shows in the final product.
Host August Bradley explores transformational technologies through this weekly, interview-style show. The show differs from some of its peers in that the host isn’t hesitant to shine a light on the effect that emergent technologies are having on us from philosophical, moral, and sociological perspectives. The guests are diverse compared with most AI-centered podcasts too, as they include at least one film director and multiple authors. Episodes typically run about an hour long and are released weekly.
NLP = Natural Language Processing. Once you get that, you get what this podcast is all about. The show is produced by the Allen Institute for Artificial Intelligence, a research and engineering institute created by Microsoft co-founder Paul Allen. A word of advice: be into natural language processing if you’re going to seriously consider adding this podcast to your library.
Hosts Matt Gardner and Waleed Ammar are research scientists at the Allen Institute (or A.I., get it?), and they regularly welcome guests to talk NLP-related research papers, developments, and trends. Episodes like ‘(Executable) Semantic Parsing’, ‘Pathologies of Neural Models Make Interpretation Difficult’, and ‘Second language acquisition modeling’ say a lot about this show — it’s pretty high-level stuff.
So yeah, a baseline knowledge of NLP will help any listener hoping to understand any of the conversations on this podcast. If you have that knowledge, this 30 to 40-minute audible celebration of NLP should do the trick once or twice a month.
Co-hosts Roger Peng and Hilary Parker cover an array of AI, data science, and data analysis-related topics on this bi-monthly, hour-long podcast. They talk about everything from the latest events (Women in Analytics conference, for one) technical subjects (the significant of statistical significant), and even mix in some light stuff (updates about coffee and oat milk). It’s not the most in-deoth, technically-oriented show (see episodes like ‘Cat Shenanigans’), but the hosts have strong chemistry and plenty to say about AI.
To understand the Numenta on Intelligence podcast, it helps to understand Numenta’s mission: “reverse engineering the neocortex.” Staying on brand, the podcast is an exploration of intelligence. What is it? What in our brains gives rise to intelligence? How does understanding these things help us improve machine intelligence and learning?
In the first 12 episodes of the show, host Matt Taylor has interviewed several different guests, including the CEO of Numenta. Topics covered include natural language processing (NLP), what Numenta does and how it does it, and a discussion centred on the thalamus. Episodes are between 20 and 45 minutes long and drop monthly.
25. O’Reilly Data Show
The O’Reilly Data Show is the AI, big data, and data science-focused podcast from O’Reilly Media. Host Ben Lorica steers episodes that run between 20 and 30 minutes long, covering subjects like ‘Bringing scalable real-time analytics to the enterprise’ and ‘Why companies are in need of data lineage solutions’.
New episodes come out twice per month, and guests regularly join Lorica to talk about trends shaping AI and big data trends. It’s not all technical, with shows like ‘Why your attention is like a piece of contested territory’ appealing to the non-enthusiast listener who wants to learn more about AI.
Practical AI is an AI-centric podcast from Changelog Media. Hosts Chris Benson and Daniel Whitenack cover topical, AI-specific stories of the day like ‘Exposing the deception of DeepFakes’, while they also get further into the AI weeds on episodes such as ‘Visualizing and Understanding RNNs’ and ‘Deep Reinforcement Learning’.
The show does a solid job toeing the line between technicality and broad appeal, with episodes such as ‘How to get plugged into the AI community’ and ‘The White House Executive Order on AI’ showing the more accessible side of the Practical AI podcast. New shows are released each week, and they typically run between 40 minutes and an hour.
SuperDataScience is a blend of lifestyle, motivational audio, and data science in one podcast. It’s an interesting combo, to say the least.
Host Kirill Eremenko chooses his guests based on their inspiration factor, with the goal being “to bring you (the listener) the most inspiring Data Scientists and Analysts from around the World to help you build your successful career in Data Science.” So clearly, the target demo is those seeking to make a career in data science. If that’s you, then this show releases new episodes every five to seven days or so, with each episode running either 15 minutes or over an hour — there’s no real in-between.
Talking Machines is a podcast in its fifth season that continues to give listeners a “window into the world of machine learning” through interviews and coverage of ML trends and news. Co-hosts Katherine Gorman and Neil Lawrence educate listeners on machine learning events around the globe, like Data Science Africa. They come up with original ideas (see: The Bezos Paradox) and regularly take time to address listeners’ questions.
The Talking Machines formula is proving strong after five years. Something’s working, whether it’s the variety of ML-related topics, the attention paid to guest interaction, the 30 to 60-minute episode times, the bi-monthly release schedule, or all of the above.
Nvidia is one of the most well-known names in machine learning and AI, as the company implements practical AI solutions in partnership with the likes of Tesla. Their AI podcast is definitely one of, if not the most reputable that you’ll find. Host Michael Copeland has served as a technology journalist for many years, and he keeps it interesting through topics that blend popular culture and the realities of AI implementation.
Episodes run between 15 and 30 minutes, and there’s no clear schedule to their release. To get an idea of the show’s pop culture-synchronized content, episodes include ‘Making “Iron Man” Interface Real’, ‘How Grownetics Automates Cannabis Cultivation’, and ‘Ready for the Playoffs? Swish Analytics Can Help You Clean Up’.
TWIMLAI is an interview-style podcast that comes out roughly three times per week, with each show running between 25 minutes and a bit over an hour. Host Sam Charrington tailors the topics of the day to each guest’s expertise, which makes for a fairly wide range of AI and ML-related subject matter. Episodes include ‘Environmental Impact of Large-Scale NLP Training’, ‘Inspiring New Machine Learning Platforms’, and ‘Transforming Oil and Gas with AI’.
Unsupervised Thinking is a podcast where computational neuroscientists get together to chat. Hosts Grace Lindsay and Yann Sweeney touch on all sort of interesting topics and ideas, including how we choose which organisms’ brains to study, the state of global collaboration in science, predictive coding, and how we study behavior. Not all episodes focus exclusively on AI or ML, but many do. Each show is about an hour long, and new shows come out each month.
Host Byron Reese is the point man for Voice in AI, where every two weeks a new guest joins him to discuss their role deploying or covering artificial intelligence. The show doesn’t take a stance on AI’s impact, as some guests preach wariness while others espouse optimism. Reese is a published author on the topic of AI, so he brings foreknowledge to each conversation. This ultimately produces some of the more thought-stimulating interviews you’ll find of any AI podcast. Each show runs between 25 minutes and an hour, give or take.
The Women in Data Science Podcast is the scion of the Women in Data Science Conference, held annually at Stanford University and more than 150 other locations across the world. Margot Gerritsen is a professor of Energy Resources Engineering at Stanford, and she’s the host of this podcast. Each new show features a new (female) guest who is making waves in the world of data science. This is the women’s empowerment-minded podcast the data science world deserves. The typical interview runs between 30 and 45 minutes, with new episodes dropping weekly.