Assignments are listed by their due date.
| Week | Dates | Day and Topics | Assignments | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Sep. 3-4 | Day 1: Introduction to course
Intelligence: What is it, where do we find it? | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Day 2: Constraint Satisfaction
Backtracking search | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| 1 | Sep. 8-11 | Day 3: Current state of AI
TBA | BC: Vibe physics: The AI grad student summary | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Day 4: Introduction to Neural Networks, Perceptron | BC: Constraint
Satisfaction/ Sudoku assignment Day 5: Feed-forward networks, backpropagation
| 2
| Sep. 14-18
| Day 6: Deep blue discussion, brute force
solutions, pattern matching in chess
| BC: Deep Blue summary
| Day 7: Data set selection, OOD errors, GIGO,
Introduction to NN assignment
| Day 8: Discussion of paper, Introduction to
NN assignment cont'd, Data curation
| BC: Great A.I. Awakening summary
| Day 9: Ethics: Bias, Copyright issues,
Hallucinations
| 3
| Sep. 21-25
| Day 10: Introduction to Reinforcement Learning
| Value Iteration BC: Cutting-edge
work proposal
| Day 11: Reinforcement Learning:
| Markov Processes, Policy Iteration Day 12: Reinforcement Learning: Q-Learning
| Monte Carlo Tree search 23:59: FFNet assignment
| Day 13: Quiz 1
| 4
| Sep. 28-Oct. 2
| Day 14: CNNs
| Day 15: CNNs continued, Introduction to
CNN Assignment
| Day 16: AlphaGoZero discussion, More on
CNN Assignment
| BC: AlphaGoZero summary
| Day 17: Knowledge representation:
Embeddings, Paraphrases, Ontologies, Common sense
| 5
| Oct. 5-6
| Day 18: NLP, early work in NLP
| Day 19: NLP and LLM architectures
| 23:59: CNN - Forward pass
| 6
| Oct. 12-16
| Day 20: AI at the pinnacle of science:
| Last year's Nobel prizes Discussion of "What kind of Mind does ChatGPT have?" paper BC: What kind of Mind does ChatGPT have?
summary
| Day 21: Hopfield Networks
| Day 22: LSTMs, Encoder-Decoder, Attention
| Day 23: Introduction to Transformers
| 7
| Oct. 19-23
| Day 24: Quiz 2
| Day 25: Transformers continued
| 23:59: CNN - Backwards pass
| Day 26: Backpropagation in CNNs
| Day 27: Cutting-edge work presentations
| 8
| Oct. 26-30
| Day 28: Transformers cont'd
| Discussion of Attention paper, BC: Attention summary
| Day 29: Training LLMs
| Day 30: Reasoning in LLMs, Research
Directions for next breakthrough
| Day 31: Cutting-edge work presentations
| 9
| Nov. 2-6
| Day 32: Human Computer Interaction
| Day 33: Knowledge in LLMs
| BC: Evaluating AI systems
| Day 34: No class, instructor not available
| 23:59: Tiny LLM
| Day 35: Cutting-edge work presentations
| 10
| Nov. 9-13
| Day 36: Discussion of Dreyfus paper, Pattern
recognition, Superintelligence, AGI, High-level machine intelligence
| BC: Alchemy and AI summary
| Day 37: Quiz 3
| Day 38: Cutting-edge work presentations
| Day 39: Cutting-edge work presentations
| |