#3230

Mentioned in 14 episodes

The bitter lesson

Book • 1973

National Union of Teachers.

This publication by the National Union of Teachers focuses on the issues of teacher turnover and the effects of the London Allowance.

It presents a sample survey and analysis aimed at understanding the factors influencing teacher retention and the financial incentives provided by the London Allowance.

Mentioned by

Chamath Palihapitiya

João Gabriel Oliveira

Mentioned in 14 episodes

Mentioned by

Chamath Palihapitiya

and explained as advocating for general learning approaches in AI.

Grok 4 Wows, The Bitter Lesson, Elon's Third Party, AI Browsers, SCOTUS backs POTUS on RIFs

Mentioned by

Omar Khattab

, who references Rich Sutton's essay when discussing observed phenomenon in AI engineering.

How Foundation Models Evolved: A PhD Journey Through AI's Breakthrough Era

Mentioned by

Jeremie Harris

in the context of DeepSeek's efficiency and implications for hardware.

#198 - DeepSeek R1 & Janus, Qwen2.5, OpenAI Agents

Recommended by

Anish Agarwal

as a short, insightful read on AI and reinforcement learning.

From DevOps ‘Heart Attacks’ to AI-Powered Diagnostics With Traversal’s AI Agents

Mentioned by

Anjney Midha

when discussing Rich Sutton's perspective on AI development.

Tesla's Road Ahead: The Bitter Lesson in Robotics

Mentioned by

Andrew Sharp

when discussing Tesla's approach to self-driving technology.

AI’s Uneven Arrival, TikTok’s Potential Departure, Xiaohongshu and the Delights of Cultural Exchange

Mentioned by

Ken Goldberg

as the author of "The Bitter Lesson", highlighting his argument that data-driven approaches outperform rule-based methods in AI.

154. Can Robots Get a Grip?

Mentioned by

Nathan Lambert

as the author of "The Bitter Lesson", highlighting his essay on verification in AI.

RL backlog: OpenAI's many RLs, clarifying distillation, and latent reasoning

Mentioned by

Tim Scarfe

in relation to self-supervised learning and human knowledge in machine learning systems.

#55 Self-Supervised Vision Models (Dr. Ishan Misra - FAIR).

Mencionado por

João Gabriel Oliveira

ao discutir a importância do poder computacional e da escala no desenvolvimento de modelos de IA.

166: Desenvolvendo o Gemini Diffusion, com João Oliveira, pesquisador da DeepMind

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