Video lesson
AI Video Lessons
Watch a selected creator’s explanation, then use the AIViewer Lens to see what sources support it, what may have changed, what it leaves out, and what to try next.
Published video lessons
Creator-attributed videos paired with an original, source-aware AIViewer lesson.
4 articles
Education
AI Tutors After the Hype: What Sal Khan’s Vision Gets Right
Sal Khan’s strongest idea is not that a chatbot knows every answer. It is that a tutor can keep a learner reasoning while a teacher remains responsible. Current evidence supports incremental product gains—not the universal transformation forecast in the talk.
Learning outcome
Separate an AI-tutoring vision from current evidence, identify equity and safety limits, and design a short session that ends with independent learner work.
Technology
Spatial Intelligence: From Seeing a Room to Acting Inside It
Fei-Fei Li argues that AI’s next frontier is spatial: systems that perceive a 3D world, reason about relationships, predict consequences, and act. Research and products show real progress, but robust global maps and safe physical action remain unsolved.
Learning outcome
Distinguish object recognition, 3D representation, spatial reasoning, and action; interpret VSI-Bench cautiously; and test a model’s room understanding with verifiable questions.
Education
How Transformer Attention Works: A 3Blue1Brown Video Lesson
A Transformer turns tokens into vectors, repeatedly lets positions exchange information through attention, transforms each position through an MLP, and preserves a running representation through residual connections before predicting another token.
Learning outcome
Trace tokens through embeddings, queries, keys, values, weighted mixing, multiple heads, MLPs, and residual connections—and explain why an attention map is not a complete explanation.
Education
Understand LLMs with Andrej Karpathy: A Video Lesson
An LLM begins as a next-token predictor that compresses patterns from training text into parameters. An assistant adds post-training, instructions, safety behavior, context, and often tools; those additions improve usefulness without guaranteeing truth.
Learning outcome
Explain next-token prediction, the compression analogy, pretraining, post-training, and tool use; distinguish a base model from an assistant; and choose when to verify an answer.