Episode Details

Last episode explored how your brain runs an ML training pipeline during sleep. This week, the hosts realize they use AI constantly but don't actually understand how it works—and spoiler, they're not alone. This episode is the 'map' before the hike: we define machine learning basics, explain why supervised and unsupervised learning are different, and give you the framework to actually understand what's happening under the hood when you use AI tools. 00:00:00 - Intro & Brain/ML Recap 00:02:30 - The Confidence Gap: Using AI Without Understanding 00:05:15 - This Episode is the Map, Not the Hike 00:07:45 - What Machine Learning Actually Is 00:10:20 - Supervised vs Unsupervised Learning 00:13:45 - Why This Matters for Daily AI Use 00:16:00 - Your Next Steps --- Sources & further reading: • Andrew Ng / DeepLearning.AI — Machine Learning Specialization (Coursera): https://www.coursera.org/specializations/machine-learning-introduction • Jeremy Howard & Rachel Thomas — Practical Deep Learning for Coders (fast.ai): https://course.fast.ai/ • Andrej Karpathy — Neural Networks: Zero to Hero: https://karpathy.ai/zero-to-hero.html • Grant Sanderson (3Blue1Brown) — Neural Networks series: https://www.3blue1brown.com/lessons/neural-networks/ • IBM — The 2026 Guide to Machine Learning: https://www.ibm.com/think/machine-learning • IBM — What is the Bias-Variance Tradeoff?: https://www.ibm.com/think/topics/bias-variance-tradeoff • IBM — What Is Self-Supervised Learning?: https://www.ibm.com/think/topics/self-supervised-learning • Vaswani et al. — "Attention Is All You Need" (2017) — (original paper available on arXiv) • Rumelhart, Hinton, Williams — "Learning representations by back-propagating errors" (1986, Nature) • Krizhevsky, Sutskever, Hinton — "ImageNet Classification with Deep Convolutional Neural Networks" (2012) • 365 Data Science — How to Learn Machine Learning in 2026: https://365datascience.com/tutorials/how-to-learn-machine-learning/ • Michael Nielsen — Neural Networks and Deep Learning (online book, Chapter 2: Backpropagation): http://neuralnetworksanddeeplearning.com/chap2.html • DigitalOcean — Types of Machine Learning: https://www.digitalocean.com/resources/articles/types-of-machine-learning This podcast episode was fully generated by AI — research, script, voices, and production. Built with Claude, Piper TTS, and automated pipeline tooling.