Search this site
Embedded Files
Towards AGI
  • Home
  • Schedule
  • Projects
  • Topics&Papers
    • Adversarial Robustness
    • Alignment and Safety
    • CompPsych-FoMo
    • Compression and Fast Inference
    • Continual Learning at Scale
    • Emergence & Phase Transitions in ML
    • Foundation Models
    • Generalization (iid and ood)
    • High Performance Computing
    • Knowledge Fusion
    • Neural Scaling Laws
    • Out-of-Distribution Generalization
    • Scaling Laws in Nature
    • State Space Models
    • Time Series Foundation Models
  • Reading Group
Towards AGI
  • Home
  • Schedule
  • Projects
  • Topics&Papers
    • Adversarial Robustness
    • Alignment and Safety
    • CompPsych-FoMo
    • Compression and Fast Inference
    • Continual Learning at Scale
    • Emergence & Phase Transitions in ML
    • Foundation Models
    • Generalization (iid and ood)
    • High Performance Computing
    • Knowledge Fusion
    • Neural Scaling Laws
    • Out-of-Distribution Generalization
    • Scaling Laws in Nature
    • State Space Models
    • Time Series Foundation Models
  • Reading Group
  • More
    • Home
    • Schedule
    • Projects
    • Topics&Papers
      • Adversarial Robustness
      • Alignment and Safety
      • CompPsych-FoMo
      • Compression and Fast Inference
      • Continual Learning at Scale
      • Emergence & Phase Transitions in ML
      • Foundation Models
      • Generalization (iid and ood)
      • High Performance Computing
      • Knowledge Fusion
      • Neural Scaling Laws
      • Out-of-Distribution Generalization
      • Scaling Laws in Nature
      • State Space Models
      • Time Series Foundation Models
    • Reading Group

 Topics & Papers  

This pages provides some resources on recent papers related to the topics of this course, that could help you choose papers to present in class. Also, if you would like to suggest a relevant paper which not in the list, please contact the instructor and/or the TAs (contact info on the course descriptions page). 

Research Topics & References  

  1. Adversarial Robustness

  2. Alignment and Safety;  AI, Philosophy & Ethics

  3. Compression and Fast Inference

  4. Computational Psychology & Foundation Models

  5. Continual  Learning  at Scale

  6. Emergence, Phase Transitions and Stat Physics of ML

  7. Foundation Models

  8. Generalization (in-  and  out-of-distribution)

  9. HPC and Distributed Model Training

  10. Knowledge Fusion Across  Foundation Models 

  11. Neural Scaling Laws

  12. Out-of-Distribution Generalization

  13. Scaling  Laws  in  Nature

  14. State Space Models

  15. Time Series Foundation Models

Other Resources: Courses, Blogs

Other Relevant Courses on Scaling and Alignment Topics

AGI Safety Fundamentals    (2022 AI Safety Fundamentals course at Cambridge)

Jacob Hilton's Deep Learning Curriculum


Scaling bibliography by Gwern


Other recent courses:

U Waterloo course


Blogs

Scaling: Motivation

  • The Bitter Lesson 

  • Scaling Hypothesis

  • The scaling hypothesis: a plan for building AGI


Large-Scale Pretrained Models

  • ChatGPT: Optimizing Language Models for Dialogue - OpenAI 

  • OpenAI's GPT-3 Language Model: A Technical Overview

  • Conversations with GPT-3

  • Do large language models understand us? 

  • The FLOPs Calculus of Language Model Training

  • New Scaling Laws for Large Language Models - LessWrong 

  • All Machine Learning Algorithms You Should Know for 2023


  • GPT 3 Demo and Explanation - An AI revolution from OpenAI

  • GPT-3 Language Models are Few-Shot Learners (Paper Explained) - by Yannic Kilcher

  • OpenAI GPT-3 Now Open to Public [FREE]

  • Neural Scaling Laws and GPT-3

  • GPT-3 Demo: New AI Algorithm Changes How We Interact With Technology

  • 14 Cool Apps Built on OpenAI's GPT-3 API

  • AI Chat Goes Horribly Wrong (GPT-3 interview)

  • AI Robin Williams 2021 (GPT-3 / GPT 3 / GPT-J-6B) artificial intelligence


On alignment

  • Alignment Research Center (lead by Paul Christiano) : blog

  • AI Alignment Forum

  • LessWrong

  • Concepts Portal: Alignment Terminology

  • Why AI alignment could be hard with modern deep learning  (Ajeya Cotra)

  • Forecasting Transformative AI from Biological Anchors (Ajeya Cotra)

  • Draft report on AI timelines (Ajeya Cotra)

  • The Billion Dollar AI Problem That Just Keeps Scaling  (Ajeya Cotra)


  • How does bee learning compare with machine learning?

  • What failure looks like (Paul Christiano)

  • Another (outer) alignment failure story (Paul Christiano)

  • Christiano, Cotra, and Yudkowsky on AI progress

  • Transformative AI and Compute

  • Welcome to LessWrong 

  • AGI Ruin: A List of Lethalities

  • Simulators

  • The Best Textbooks on Every Subject


Plans for AI Future: Different Perspectives

Toward Next-Generation Artificial Intelligence: Catalyzing the NeuroAI Revolution

The Alberta Plan for AI Research 

Toward Next-Generation Artificial Intelligence 

General Intelligence Requires Rethinking Exploration

Books

Formal Aspects of Language Modeling

Google Sites
Report abuse
Page details
Page updated
Google Sites
Report abuse