References & Citations
Credible, primary-source references that support the concepts discussed throughout this resource
Foundational Research
Attention Is All You Need
Vaswani, Ashish et al. (2017)
Introduced Transformer architecture
https://arxiv.org/abs/1706.03762Language Models are Few-Shot Learners (GPT-3)
Brown et al. (2020)
Demonstrated few-shot learning capabilities
https://arxiv.org/abs/2005.14165GPT Series Papers
Radford et al. (2018–2020)
Early OpenAI LLMs and language modeling advancements
https://cdn.openai.com/research-covers/language-unsupervised/language_understanding_paper.pdfTraining & Alignment
Training language models with human feedback (RLHF)
Ouyang, Long et al. (2022)
Reinforcement learning from human feedback
https://arxiv.org/abs/2203.02155Constitutional AI
Bai et al. (2022) - Anthropic
Self-supervised alignment methods
https://arxiv.org/abs/2212.08073Sparks of Artificial General Intelligence?
Bubeck et al. (2023) - Microsoft Research
Analysis of emergent capabilities in large models
https://arxiv.org/abs/2303.12712Industry Resources
Google Research / Brain Team
Transformer & language model research archive
https://research.google/pubs/Data Sources & Ethics
Anthropic Constitution
Anthropic
Responsible AI & data pipeline standards
https://www.anthropic.com/constitutionRegulation & Governance
White House AI Executive Order
The White House
U.S. executive guidance on AI governance
https://www.whitehouse.gov/briefing-room/NIST AI Risk Management Framework
National Institute of Standards and Technology
Framework for managing AI risks
https://www.nist.gov/itl/ai-risk-management-frameworkBusiness & Strategy
McKinsey AI Insights
McKinsey & Company
AI maturity and business value
https://www.mckinsey.com/capabilities/quantumblack/our-insightsChapter 5: SEO & AEO
Google Search Central
E-E-A-T and Helpful Content standards
https://developers.google.com/search/docs/fundamentals/creating-helpful-contentMicrosoft Research
Microsoft
Human preference and answer systems
https://www.microsoft.com/en-us/research/Chapter 6: Myths vs Realities
Microsoft Research
Microsoft
AI hallucination mitigation work
https://www.microsoft.com/en-us/research/Chapter 7: Regulation & Governance
White House AI Executive Order
The White House
U.S. executive guidance on AI governance
https://www.whitehouse.gov/briefing-room/NIST AI Risk Management Framework
National Institute of Standards and Technology
Framework for managing AI risks
https://www.nist.gov/itl/ai-risk-management-frameworkMcKinsey AI Insights
McKinsey & Company
AI maturity and business value
https://www.mckinsey.com/capabilities/quantumblack/our-insights