The AI Concepts Podcast
Sheetal ’Shay’ DharThe AI Concepts Podcast is my attempt to turn the complex world of artificial intelligence into bite-sized, easy-to-digest episodes. Imagine a space where you can pick any AI topic and immediately grasp it, like flipping through an Audio Lexicon - but even better! Using vivid analogies and storytelling, I guide you through intricate ideas, helping you create mental images that stick. Whether you’r... more
| Publishes | Daily | Episodes | 67 | Founded | a year ago |
|---|---|---|---|---|---|
| Number of Listeners | Categories | CoursesTechnologyEducation | |||
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Latest Episodes
This episode is about the step that every RAG system depends on. Before meaning can be stored or retrieved, your raw documents have to become clean text. What goes wrong here breaks the entire pipeline in ways that are surprisingly hard to catch.
This episode is about the infrastructure underneath every RAG system. It covers the purpose-built engine that stores all that meaning and searches millions of vectors in milliseconds, in a way no traditional database can. This is what makes retrieval... more
This episode is about the layer of RAG that makes semantic search possible. It covers how machines turn language into math that clusters similar ideas together, so a question and its answer can find each other even when they share no words in common.... more
This episode maps out the full RAG pipeline end to end using one concrete scenario, a defense contractor building an AI assistant for fighter jet maintenance crews. It walks through both phases of the architecture, offline and online, following a rea... more
This episode kicks off Module 6 with RAG (Retrieval Augmented Generation), the #1 architecture every serious enterprise actually uses. Discover why regular LLMs hallucinate on your private data and high-stakes queries, and how RAG fixes it by forcing... more
This episode covers reasoning models, the shift from manually guiding a model's thinking to letting the model reason through complex problems on its own before responding. It explains the concept of test-time compute, why reasoning models take longer... more
This episode covers structured output, how you get a model to respond in predictable, machine-readable formats like JSON instead of natural language paragraphs. It walks through three approaches, from simply asking in the prompt, to JSON mode, to sch... more
This episode covers system prompts, the invisible instruction layer that shapes every model interaction before the user says a word. It explains the three-role message format, why the model is trained to treat system instructions as higher authority ... more
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