Skip to content
hackertubeai

UC Berkeley EECS

John Schulman - Reinforcement Learning from Human Feedback: Progress and Challenges

About this video

UC Berkeley EECS colloquium by OpenAI's John Schulman on reinforcement learning from human feedback. He covers why RL helps with truthfulness, hallucination, and the limits of behavior cloning.

Keep your curiosity going.

A few more ideas from the same corner of the archive.

The spelled-out intro to neural networks and backpropagation: building micrograd

Andrej Karpathy

But what is a neural network? | Deep learning chapter 1

3Blue1Brown

A Better Default Colormap for Matplotlib | SciPy 2015 | Nathaniel Smith and Stéfan van der Walt

Enthought

How Self-Driving Cars will Destroy Cities (and what to do about it)

Not Just Bikes