Class 1 (Wed, Jan 8, 4:30-6:30pm)

Lecturer: Irina Rish 

Topic: Intro and Overview: A brief history of AI at Scale  (slides)

Papers:  The Bitter Lesson,   GPT-3 paper: Language Models are Few-Shot Learners

Class 5  (Wed, Jan 22, 4:30-6:30pm)

Part 1: Lecturer:  Daria Yasafova

Topic :  Scaling  Laws for Neural Language Models  (slides, video)

Additional video: Neural Scaling Laws and GPT-3

Class 7  (Wed, Jan 29, 4:30-6:30pm)

Part 1: Lecturer:  Prateek Humane

Topic:  DeepSeek-R1: Incentivizing reasoning capability in LLMs via reinforcement learning   (slides, video)

Additional Reading:
Open-R1: a fully open reproduction of DeepSeek-R1
DeepSeek-R1 explained (Medium article)

Class 9  (Wed, Feb 5, 4:30-6:30pm)

Part 1: Lecturer:  Prateek Humane

Topic:  Alignment faking in large language models  (slides, video)

Part 2: Lecturers:  Edward Habelrih  and Frederic Jarjour

Topic: Effect of scale on catastrophic forgetting in neural networks (slides, video - part 2)

Class 11  (Wed, Feb 12, 4:30-6:30pm)

Part 1: Lecturers:   Shruti Bibra and Yousef Kotp

Topic:  When Do We Not Need Larger Vision Models?  (slides, video)

Part 2: Lecturers:  Jiadi Yu and Mingze Li 

Topic: Zero-Shot Text-to-Image Generation (slides, video - part 2)

Class 13  (Wed, Feb 19, 4:30-6:30pm)

Part 1: Lecturers:   Ivan Anokhin and Shahrad Mohammadzadeh

Topic:  RLHF: How to Learn from Human Feedback with Reinforcement Learning (slides, video)

Part 2: Lecturers:  Rishika Bhagwatkar and Aditya Sharma

Topic: RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement Learning (slides, video - part 2)

Class 15  (Wed, Feb 26, 4:30-6:30pm)

Part 1: Lecturers:   Azalée Robitaille and Artur Kuramshin

Topic:  Data scaling laws in imitation learning for robotic manipulation (slides, video)

Part 2: Lecturers:  Manping Li and Yan Zhang

Topic: Simple and Scalable Strategies to Continually Pre-train Large Language Models  (slides, video - part 2)

Class 17 (Wed, March 5, 4:30-6:30pm)

Part 1: Lecturers:   Ivan Anokhin and Navid Hassan Zadeh

Topic:  Investigating Continual Pretraining in Large Language Models: Insights and Implications (slides, video)

Part 2: Lecturers:  Yorguin Jose Mantilla Ramos and Yousef Kotp

Topic: Progress measures for grokking via mechanistic interpretability (slides, video - part 2)

Class 19 (Wed, March 12, 4:30-6:30pm)

Part 1: Lecturers:   Jia Ao Sun and Hao Yu

Topic:  Constitutional AI: Harmlessness from AI Feedback (slides, video)

Part 2: Lecturers:  Sungjae Cho  and  Anirudh Jamkhandi

Topic: Brain-inspired replay for continual learning with artificial neural networks (slides, video - part 2)

Class 21  (Wed, March 19, 4:30-6:30pm)

Part 1: Lecturers:   Azalée Robitaille and Artur Kuramshin

Topic:  Robotic Control via Embodied Chain-of-Thought Reasoning (slides, video)

Part 2: Lecturers:  Edward Habelrih  and  Frederic Jarjour

Topic:   Large Language Models can Strategically Deceive their Users when Put Under Pressure (slides, video - part 2)

Class 23 (Wed, March 26, 4:30-6:30pm)

Part 1: Lecturers:   Juan David Guerra and Mauricio Rivera

Topic:  Rho-1: Not All Tokens Are What You Need (slides, video)

Part 2: Lecturers:  Sepehr Babapour

Topic:   Leveraging clinical data across healthcare institutions for continual learning of predictive risk models (slides, video - part 2)

Class 25 (Wed, April 2, 4:30-6:30pm)

Part 1: Lecturers:    Jiadi Yu and Mingze Li

Topic:  s1: Simple test-time scaling (slides, video)

Part 2: Lecturers:  Manping Li and Yan Zhang

Topic:   Learning Transferable Visual Models From Natural Language Supervision (slides, video - part 2)

Class 27 (Wed, April 9, 4:30-6:30pm)

Part 1: Lecturers:    Ankur Sikarwar and Ayush Agrawal

Topic:  Genie: Generative Interactive Environments (slides, video)

Part 2: Lecturers:  Michael Xi and Morteza Mahdiani

Topic:   Scaling laws for decoding images from brain activity (slides, video - part 2)

Class 29 (Wed, April 16, 4:30-6:30pm)

Part 1: Lecturers:    Mauricio Rivera and Juan David Guerra

Topic:  Dynamic Neural Regeneration (slides, video)

Part 2: Lecturers:  Navid Hassan Zadeh and Shahrad Mohammadzadeh

Topic:   Chronos: Learning the Language of Time Series  (slides, video - part 2)

Class 31 (Wed, April 23, 4:30-6:30pm)

Part 1: Lecturers:    Yajie Luo and Yihong Wu

Topic:  SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training  (slides, video)

Part 2: Lecturers:  Roger Creus

Topic:   Mastering Board Games by External and Internal Planning with Language Models  (slides, video - part 2)