AI Concepts Explained in 40 Minutes (youtu.be)

Gaurav Sen’s “AI Concepts Explained in 40 Minutes” is a tightly packed primer that walks viewers through 20 core AI/ML building blocks—from tokenization and vectorization to transformers, attention, and self‑supervised learning—then moves into applied topics like fine‑tuning, few‑shot prompting, Retrieval‑Augmented Generation (RAG) with vector databases, agents, and reasoning models. The video stitches together how raw text becomes tokens and embeddings, how attention and transformer architecture enable contextual understanding, and how prompt engineering (few‑shot, chain‑of‑thought) and the Model Context Protocol shape model behavior in practice. Technically useful for practitioners, the summary highlights trade‑offs and deployment concerns: RAG+vector DBs enable up‑to‑date, grounded responses; distillation and quantization make large models feasible on edge or cost‑sensitive stacks; small LMs plus efficient approaches (distillation, quant) can replace brute‑force scale in many applications. It also covers agents and reinforcement learning for action‑oriented systems, multi‑modal models for cross‑modal reasoning, and context engineering as a production discipline. Overall, the video is a compact roadmap linking theory to engineering choices—valuable for ML engineers, product builders, and learners wanting a cohesive view of modern NLP/AI tooling and trade‑offs.