Best AI Engineering Podcasts: Unsupervised Learning to Substack Picks
By
Liz Fujiwara
•
Sep 23, 2025
Want to deepen your understanding of unsupervised learning through podcasts? This article highlights some of the best podcast episodes that explore unsupervised learning in depth, featuring expert insights, real-world applications, and the latest techniques in the field. Whether you are a student, researcher, or AI enthusiast, these episodes provide valuable perspectives on clustering, dimensionality reduction, anomaly detection, and other unsupervised learning methods. See how you can use this must-listen resource to boost your knowledge of AI and machine learning.
Key Takeaways
Podcasts are essential for AI engineers to stay updated on industry trends. Top picks such as Unsupervised Learning, The TWIML AI Podcast, and Data Skeptic offer valuable insights into unsupervised learning techniques and broader AI advancements.
Fonzi revolutionizes AI hiring by connecting top-tier engineers with companies through a structured and efficient Match Day process, focusing on high-quality talent.
The platform emphasizes fairness and transparency, incorporating bias auditing and rapid candidate screening to support faster and more equitable hiring decisions.
Top Unsupervised Learning Podcasts
Podcasts have become a key resource for AI engineers. Among the many options available, unsupervised learning podcasts stand out for their focus on advanced techniques and practical applications.
These podcasts often feature in-depth discussions and interviews with industry leaders, providing valuable lessons and insights for AI professionals.
Unsupervised Learning by Daniel Miessler
Hosted by Daniel Miessler, the Unsupervised Learning podcast explores topics related to cybersecurity, technology, and society. Episode No. 395, released on August 21, 2023, illustrates how Miessler integrates insights on unsupervised learning techniques into broader discussions. The podcast is known for its engaging and informative content, making it a valuable resource for those interested in the intersection of AI and cybersecurity.
Miessler’s discussions provide practical insights into the application of unsupervised learning, making complex topics accessible and understandable. Whether you are an AI engineer or a tech enthusiast, Unsupervised Learning offers lessons that can be applied across various fields, increasing understanding and expertise.
The TWIML AI Podcast (This Week in Machine Learning & AI)
The TWIML AI Podcast, formerly known as This Week in Machine Learning, provides a platform for discussions on advanced machine learning techniques. Since its inception in 2016, the podcast has released over 686 episodes covering a wide range of AI and machine learning topics, including episodes focused on unsupervised learning.
Its detailed discussions offer comprehensive insights into unsupervised learning techniques, enhancing understanding of both the methods and their practical applications. The TWIML AI Podcast is essential listening for AI professionals and enthusiasts alike.
Data Skeptic
The Data Skeptic podcast, which began in 2014, emphasizes critical thinking in data science and has aired over 532 episodes. Key aspects include:
Episodes exploring unsupervised learning methods.
Expert interviews offering deeper insights into each topic.
A focused production team ensures each episode provides a detailed exploration of specific subjects.
From discussing the latest AI tools and techniques to examining real-world applications, Data Skeptic delivers valuable perspectives for developers and data scientists. Whether new to the field or an experienced professional, this podcast provides the knowledge and insights needed to stay current in the evolving world of AI.
Best AI Engineering Podcasts: Unsupervised Learning to Substack Picks
To help navigate the vast world of AI engineering podcasts, we’ve curated a list of the best options. This makes it easier to find the right podcast for your needs, covering topics from unsupervised learning to the latest industry insights.
Podcast Name | Host | Focus Area | Number of Episodes |
Unsupervised Learning | Daniel Miessler | Cybersecurity, Tech, Society | 395 |
The TWIML AI Podcast | Sam Charrington | Machine Learning, AI | 686 |
Data Skeptic | Kyle Polich | Data Science, Critical Thinking | 532 |
Chris Benson | AI Topics, Practical Insights | Weekly | |
Various | AI Frameworks, Community Engagement | Since 2023 |
Each of these podcasts provides unique insights and valuable lessons for AI engineers. Whether you are interested in deep technical discussions or practical applications, there is a podcast on this list to meet your needs. These shows can enhance your understanding of AI and keep you informed about the latest trends and technologies.
Lessons Learned from Top AI Engineers
Top AI engineers frequently share valuable lessons from their experiences, offering important insights for anyone in the field. One key lesson is the importance of blending deterministic systems with AI to design solutions that are both intelligent and reliable.
Another critical lesson is the need to mitigate risks from compounded errors in AI pipelines. Implementing strategies to address these challenges helps developers build more accurate and dependable AI systems. Insights from AI-driven systems can also enhance security practices in cybersecurity, highlighting AI’s value across multiple domains.
Incorporating these lessons can improve productivity and effectiveness as an AI engineer. From working with large language models to developing technical and soft skills, these insights provide a comprehensive perspective on what it takes to succeed in the dynamic world of software engineering, leadership, and development. Reflecting on these lessons can help you strengthen your capabilities and plan for a successful future in the field.
How to Stay Updated with AI Engineering Trends
Keeping up with the latest AI engineering trends is essential for developers to remain competitive and informed. Listening to podcasts focused on emerging AI technologies is an effective way to stay updated. Unsupervised learning podcasts, in particular, offer valuable insights into the latest developments in AI and machine learning.
Podcasts and newsletters provide regular updates on AI trends and techniques. The TWIML AI Podcast covers a wide range of AI and machine learning topics, offering comprehensive insights into current trends and new techniques. Last Week in AI delivers weekly updates, helping professionals stay informed.
Other notable resources include Masters of Work, which highlights AI tools and trends that can increase productivity. Subscribing to these resources helps professionals stay ahead in the fast-paced world of AI engineering.
What is Fonzi?
Fonzi is a specialized marketplace designed to connect high-caliber AI engineers with leading tech companies through a structured hiring event called Match Day. Unlike traditional job boards, Fonzi focuses on quality talent and efficiency, ensuring a streamlined and effective hiring process. Pre-vetted engineers are matched with top-tier companies, saving time and enhancing the overall hiring experience.
On Match Day, companies engage with top-tier AI engineers in a structured environment, making the process efficient and productive. The platform’s curated approach ensures that only the best candidates are considered, emphasizing quality and efficiency in AI hiring.
How Does Fonzi Work?
Fonzi uses structured evaluations to connect companies with pre-vetted AI engineers, providing transparency and actionable insights. Unlike black-box AI tools or traditional job boards, evaluations deliver clear information about each candidate’s capabilities. Incorporating fraud detection and bias auditing ensures fairness and equity throughout the hiring process.
Rapid candidate screening completes evaluations within hours, enabling companies to fill roles quickly, often within three weeks. This structured and efficient approach makes Fonzi an unparalleled solution for companies competing in the fast-paced AI landscape.
Why Choose Fonzi for Hiring AI Engineers?
Fonzi offers fast, consistent, and scalable hiring, with most positions filled within three weeks. Bias auditing promotes fairness, diversity, and inclusion, while pre-vetted candidates reduce sourcing challenges and ghosting.
Candidate experience is prioritized through flexible interview scheduling and consistent feedback, ensuring engagement and optimal matching. Fonzi supports both startups and large enterprises, providing access to competitive job offers through a single application, supported by a personal recruiter.
Summary
In the rapidly evolving field of AI, staying informed and connected is essential. AI engineering podcasts provide an engaging way to keep up with the latest trends, techniques, and insights from industry leaders. From unsupervised learning to practical AI applications, these podcasts offer a wealth of knowledge that can enhance understanding and expertise.
Fonzi, with its innovative approach to hiring AI engineers, is a game-changer in the industry. By prioritizing quality, efficiency, and a positive candidate experience, Fonzi helps companies find the right talent quickly and effectively. Structured evaluations, bias auditing, and screening make Fonzi an invaluable recruitment tool for any organization looking to remain competitive in the AI landscape.
Exploring recommended podcasts and leveraging platforms like Fonzi can significantly enhance your journey in AI. Stay curious, keep learning, and embrace the endless possibilities this field has to offer.
