AI Bites: The Academic Series

We’ve reached the finish line! 🏁 In our final installment of the Stanford CS221 series, we tackle the last pieces of the AI puzzle: moving from probabilistic reasoning to actual learning, and revisiting the power of symbolic logic. Key Topics: Deep Dive into Bayesian Learning: How we move beyond just using networks to actually learning their parameters and structures from data. Logic Problems: A...

We are moving from logic to probability! This week in Stanford’s CS221, we transition from the rigid rules of Constraint Satisfaction Problems (CSPs) into the flexible world of Probabilistic Graphical Models. We explore how AI handles uncertainty and models complex relationships between variables. Key Topics: Transition to Markov Networks: Moving beyond constraints to undirected graphical models t...

How does AI play to win? This week in Stanford’s CS221, we shift gears from simple pathfinding to navigating adversarial environments and solving complex logic puzzles with strict boundaries. Key Topics: Games: Exploring strategic decision-making, game trees (Minimax/Expectimax), and how AI predicts an opponent’s next move in competitive scenarios. Introduction to CSPs: An entry into Constraint Sa...

We’re leveling up the complexity this week in Stanford’s CS221. We move from basic search into "smart" search and start exploring how AI handles sequences and uncertainty through Markov models. Key Topics: • Structured Perceptron: Moving beyond simple classification to predicting complex, structured outputs (like tags in a sentence or parts of an image).• A Search: * The "gold stand...

We’re diving deeper into the engine room of Artificial Intelligence this week. We continue our journey through Stanford’s CS221, moving from basic ML foundations into the math of optimization and the logic of search algorithms. Key Topics: • Machine Learning 2 & 3: A deep dive into loss functions, gradient descent, and how we actually "train" a model to improve.• Search Problems 1 &a...

New course alert! We are moving from NLP into Stanford’s flagship AI course: CS221 (Principles of AI) . We kick things off by looking at the "big picture"—where AI came from, the ethics of what we’re building, and the start of our Machine Learning journey. Key Topics: • Course Introduction: Defining the "Principles" of Artificial Intelligence.• AI History: Tracing the path from...

In our third installment, we look at how NLP and AI interact with the broader world, from human speech recognition to the algorithms that decide what shows up in your social feed. Key Topics:• Speech Recognition: Converting audio to data.• Recommendation Systems: The AI behind "You might also like..."• Social Networks & Web Links: How PageRank organizes the internet. Note: This is an...

Things get "deep" this week. We trace the evolution of how AI understands the meaning of words—moving from simple vectors to the revolutionary Transformer architecture that powers today’s LLMs. Key Topics:• Vector & Contextual Embeddings: Mathematical meaning.• Neural Networks: Biological inspiration.• LLMs & Transformers: The breakthrough that changed everything. Note: This is a...

We kick off our deep dive into Stanford’s CS124 with the building blocks of NLP. This episode covers how computers "read" and organize language before moving into the math behind search. Key Topics:• Words & Tokens: How we break down language.• N-gram Language Modeling: Predicting sequences.• Logistic Regression: The classification workhorse.• Information Retrieval: How search engine...