Table of contents
Our team of deep learning engineers is always on the hunt to keep up with the latest research, industry news and applications, and future outlook of machine learning, deep learning, and artificial intelligence on our quest to create an industry best Speech-to-Text API.
Below, our team has rounded up a few of their top machine learning podcasts, ranging from the minutely technical to the more universally appealing.
Top team picks include:
- The AI Podcast
- Concerning AI
- Data Stories
- Partially Derivative
- Gradient Dissent
- Machine Learning Street Talk
- Linear Digressions
Keep reading to learn more about each machine learning podcast, including a round-up of some of our favorite episodes.
1. The AI Podcast
The AI Podcast connects listeners to leading machine learning scientists and AI experts. Podcast episodes include AI and machine learning topics that range from how the technology works to current trends to ethical implications. The monthly podcast is produced by AI computing company NVIDIA.
Length: 20-30 minutes
- Researchers Chris Downm and Leszek Pawlowicz Use Deep Learning to Accelerate Archaeology
- GE’s Danielle Merfeld and Arvind Rangarajan on AI and Renewable Energy
- NVIDIA’s Simon Yuen Talks about the Future Horizon of Digital Humans
- Getting Clever with Kaolin: Researchers Accelerate 3D Deep Learning with New Tools
2. Concerning AI
Hosted by Ted Sarvata and Brandon Sanders, Concerning AI examines the ethical and practical implications, and risks, of today’s AI research. Episodes include interviews with field experts as well as individual commentary. Though the podcast is currently paused, it is still worthwhile to peruse through the archives.
Length: 30-40 minutes
- We Don’t Get to Choose
- Will Bias Get Us First?
- Peter Scott’s Timeline for Artificial Intelligence Risks
- Predictions of When
3. Data Stories
Data Stories is a podcast by NYU professor and acclaimed researcher Enrico Bertini and data science expert Moritz Stefaner. Together, the two discuss data visualization, big data, and other machine learning topics, as well as host numerous other guest experts to discuss hot topics.
Length: 45 minutes
- Data Visualization Accessibility with Sarah Fossheim
- Visualizing Fairness in Machine Learning with Yongsu Ahn and Alex Cabrera
- Future Data Interfaces with David Sheldon-Hicks
- Cognitive Science for Data Visualization with Lace Padilla
4. Partially Derivative
Hosts Chris and Vidja discuss machine learning and everyday data about the world around us in the Partially Derivative podcast. Popular topics include artificial intelligence and crime, deep learning and its relation to mathematics, the future of deep learning, and data science and security.
Length: 25-35 minutes
- Learning Machine Learning
- Particle Physics and Machine Learning at CERN with Michael Kagan
- The Limits of Deep Learning
- Interview: Machine Bias with Jeff Larson, Data Scientist at ProPublica
5. Gradient Dissent
In the Gradient Dissent podcast, host Lukas Biewald interviews machine learning experts to delve into deep learning, training models, and AI approaches at companies like Google, Lyft, Facebook, and more. Topics include robotics, machine learning models, biomedicine, responsibility and bias, language models, and more.
Length: 45 minutes
- Language Models and Linguistics
- Clement Delangue, CEO of Hugging Face, on the power of the open source community
- Graphcore’s Phil Brown on how IPUs are advancing machine intelligence
- Stanford’s Polly Foryce on microfluidic platforms and machine learning
Mathematician and scientist Dr. Hannah Fry hosts DeepMind: The Podcast, a series that highlights topics in AI research, machine learning, and neuroscience. In the podcast, Fry interviews researchers, engineers, and program managers to discuss these controversial and cutting-edge topics.
Length: 35 minutes
Frequency: YouTube Series
7. Machine Learning Street Talk
Machine Learning Street Talk is a technical podcast hosted on YouTube and managed by Dr. Tim Scarfe, Dr. Yannic Kilcher, and Dr. Keith Duggar. The show’s hosts believe in diversity of thought and opinions and try to bring an array of voices in each episode.
Length: 1+ hours
- Self Supervised Vision Models with Dr. Ishan Misra
- Francois Chollet on Intelligence and Generalization
- Professor Max Welling on Symmetries, Physics, and Manifolds in ML
- Professor Melanie Mitchell on Why AI is Harder than We Think
8. Linear Digressions
Hosted by Ben Jaffe and Katie Malone, Linear Digressions delves into data science and machine learning problem solving, real world applications, and recent discoveries. Though new episodes of this podcast officially ended last year, its archives still contain a wealth of intriguing content for first time listeners.
Length: 20-30 minutes
- A Reality Check on AI-driven Medical Assistants
- Procella: YouTube’s Super-system for Analytics Data Storage
- The Data Science Open Source Ecosystem
- Convolutional Neural Networks
Listen to the playlist on Spotify here: