I just binged this playlist at 1 am. Absolutely worth it. You deserve more views.

PLEASE COMEBACK!! You are an amazing theacher!

All of your videos are amazing, please upload more

Please come back, your videos are great!

Joel, excellent explanation and talk! Thank you!

help me a lot, can't wait to see more

Welcome back! Hope to see more of these videos..

Amazing content! Please keep them coming!

Super helpful - thank you for this series!

Good teaching.

Great content!!

come back :(

You are the Best

Who is this guy? He made all the complexity so simple with his words. Anyone know this gentleman name?

🎯 Key Takeaways for quick navigation: 00:00 🤖 Reinforcement learning improves large language models like ChatGPT. 00:25 🃏 Large language models face issues like bias, errors, and quality. 01:11 📊 Training data quality impacts results; removing bad jokes might help. 01:55 🧩 Training on both good and bad jokes improves language models. 02:38 🔄 Language models are policies, reinforcement learning uses policy gradient. 03:08 🎯 Reinforcement Learning from Human Feedback (RLHF) challenges data acquisition. 03:35 🤔 RLHF theory: Language model might already know jokes' boundary. 04:18 🏆 Training a reward network predicts human ratings for model's output. 04:47 🔄 Reward network is a modified language model for predicting ratings. 05:14 📝 Approach: Humans write text, train reward network, refine model with RL. 05:57 ⚖️ Systems convert comparisons to ratings for reward network training. 06:11 😄 RLHF successfully improves language models, including humor. Made with HARPA AI

How long it takes to train a reward network? And how reliable would it be?