References
Edward Feigenbaum Oral History — Computer History Museum
SOFT: Selective Data Obfuscation for Protecting LLM Fine-tuning — USENIX 2025
What happens when our computers get smarter than we are? — Nick Bostrom
Understanding the Limitations of AI — Timnit Gebru at WiDS Stanford
History, Motivation and Evolution of Deep Learning — Yann LeCun
AlphaFold: Grand Challenge to Nobel Prize — John Jumper
AI is solving science’s biggest problems — Claire Malone
Accelerating Scientific Discovery with AI — Demis Hassabis
Writing AI Constitutions: Joe Carlsmith at Yale Law School
CodeX FutureLaw 2026: Building Legal AGI
CodeX FutureLaw 2026: Computational Law as a Blueprint for AI Reasoning
CodeX FutureLaw 2026: Dynamic Law for AI
Deep Learning: Beyond the Hype
Stanford CS329A: Planning and Multi-Step Reasoning
Amp: The Emperor Has No Clothes
Art Machines: Machine Learning and Art Panel 1, Gene Kogan and Memo Akten
AI for Testing: The Development of Bots that Play Battlefield V