Month September 2025

In this video, Dr. Matthew Hudnall breaks down the three main types of artificial intelligence, explaining their distinct capabilities and potential impacts to help you better understand both the present and future of AI.

In this video, Dr. Matthew Hudnall introduces retrieval-augmented generation (RAG), a technique that combines AI’s ability to generate text with real-time information retrieval, addressing one of the biggest limitations of traditional models.

In this video, Dr. Matthew Hudnall shares how AI understands complex relationships between words, images, and sounds through multidimensional encoding, a mathematical technique that enables AI to translate languages, recognize patterns, and generate content with remarkable human-like understanding.

Dr. Matthew Hudnall explains how the blanket term “AI” makes up a diverse ecosystem of specialized systems, from Netflix recommendation engines to self-driving car sensors to creative content generators. Understanding these different types of AI helps you choose the right tool for each task and set realistic expectations for what each system can actually do.

Dr. Matthew Hudnall explores how supervised and unsupervised learning differ, and why both are essential to understanding how AI solves problems and reveals hidden patterns.

Dr. Matthew Hudnall explains how reinforcement learning from human feedback (RLHF) teaches AI models to align with human expectations, making them more accurate, polite, and useful while also highlighting its ethical challenges.

In this video, Dr. Matthew Hudnall demystifies generative AI, showing how it learns patterns from massive datasets to create original stories, images, music, and more, not through magic, but through powerful prediction at scale.

Dr. Matthew Hudnall explains why guardrails are essential to ensure safety, fairness, and ethical use as AI becomes more prominent and powerful.