The Information Bottleneck

John Platt (Google): AI for Climate and Science

Yuandong Tian on Recursive Self-Improvement

Chris Manning: Language Is the Real Unlock for Intelligence

Why AI Still Can't See wtih Andrew Dai

Can AI Replace Doctors? Zachary Lipton on the Future of Healthcare and AI

Sara Hooker on the End of Static AI

Tiny Recursive Models Beat the Giants - Alexia Jolicoeur-Martineau (Microsoft)

Continual Learning Is the Next Bottleneck | Rohan Anil (Core Automation )

Rohan Anil, a former Google Brain researcher and co-founder of Core Automation, explores critical bottlenecks in current AI research, specifically focusing on the limitations of existing optimization methods and the necessity for more efficient, automated kernel generation. The discussion highlights the evolution from ...

World Models | John Langford (Microsoft AI Labs)

Which Tabular Model Should You Actually Use? | David Holzmüller (INRIA)

Why You Can't Just Rent 1,000 GPUs | Charles Frye (Modal)

Stella Biderman (EleutherAI) - Open Source, AI Safety, and Who We Can Trust

Why Deep Learning Finally Works on Tables | Frank Hutter (Prior Labs)

Surya Ganguli: The Physics of Intelligence

Text Diffusion Models with Brendan O'Donoghue (Google DeepMind)

Nathan Lambert: Inside Post-Training and the Open Model Fight

Daphne Koller - The Future of AI in Biology and Drug Discovery

RL Was Broken at Every Level - With Joseph Suarez (PufferAI)

The Model Found a Way Out - with Florian Brand (Prime Intellect)

Pierre-Carl Langlais on Building Models from Data You Can Account For