A structured reference to the individuals shaping artificial intelligence across research, industry, governance, ethics, and public discourse. Curated as a resource for professionals navigating the AI landscape. For more see the full list at AI People.

Large Language Models and Foundation Architectures

Ashish Vaswani, Noam Shazeer, Jakob Uszkoreit, Llion Jones, Niki Parmar, Aidan Gomez, Illia Polosukhin & Lukasz Kaiser | Transformer Architecture | United States/Canada The eight co-authors of "Attention Is All You Need" (2017), the paper that introduced the transformer architecture. This single innovation enabled GPT, BERT, and virtually every modern language model. Several have since founded AI companies: Shazeer (Character AI), Gomez (Cohere), Polosukhin (NEAR Protocol). Key works: "Attention Is All You Need" (2017)

Alec Radford | Language Models | United States Principal author of GPT-2 and key contributor to GPT research at OpenAI. His work on unsupervised language model pretraining demonstrated that scaling up simple models on large text corpora could produce surprisingly capable systems. Key works: GPT-2 technical report, CLIP

Jacob Devlin | Pretraining Methods | United States Created BERT at Google, introducing bidirectional pretraining that dramatically improved NLP benchmarks. BERT's approach of pretraining on masked language modelling became standard practice and influenced countless subsequent models. Key works: "BERT: Pre-training of Deep Bidirectional Transformers" (2018)

Christopher Manning | NLP Foundations | United States Co-authored foundational NLP textbooks and led Stanford's NLP group for decades. His work bridges linguistic theory and practical NLP systems. Trained many leading researchers and built infrastructure (Stanford CoreNLP) used throughout the field. Key works: "Foundations of Statistical Natural Language Processing" (1999), Stanford NLP tools

Tomáš Mikolov | Word Embeddings | Czech Republic Created word2vec, demonstrating that neural networks could learn meaningful word representations capturing semantic relationships. The famous "king - man + woman = queen" analogy emerged from his work, reshaping how NLP systems represent meaning. Key works: word2vec papers (2013)

Percy Liang | Model Evaluation, Research Infrastructure | United States Leads Stanford's Center for Research on Foundation Models (CRFM) and created HELM, the most comprehensive evaluation framework for language models. His work on understanding and measuring what foundation models can and cannot do provides essential infrastructure for the field. Key works: HELM benchmark, foundation model evaluation, CRFM leadership

Andrej Karpathy | ML Education, Applied AI | United States Former Tesla AI Director and OpenAI researcher whose educational content (lectures, tutorials, nanoGPT) has taught millions to understand deep learning. Bridges cutting-edge research and practical engineering with exceptional clarity. Key works: CS231n lectures, nanoGPT, educational content

Jason Wei | Prompting Methods, Emergent Abilities | United States Pioneered chain-of-thought prompting, showing that asking language models to reason step-by-step dramatically improves their performance on complex tasks. His research on emergent abilities in large models shaped understanding of what scaling enables. Key works: Chain-of-thought prompting, emergent abilities research

How to Use This Directory

For research: Each entry includes key works and affiliations for deeper investigation.

For event planning: Filter by geographic base, domain, or public engagement experience.

For understanding the field: The categorisation reveals how different communities, from technical researchers, ethicists, policymakers, industry leaders all shape AI development.

For identifying perspectives: Note whose voices are included and whose might be missing from any particular AI conversation.

This directory is maintained as a resource for the AI age. Last updated: 2026.

Curated by Rahim Hirji for thesuperskills.com.

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