VPT Model Video Explanation

https://youtu.be/oz5yZc9ULAc

Minecraft is one of the harder challenges any RL agent could face. Episodes are long, and the world is procedurally generated, complex, and huge. Further, the action space is a keyboard and a mouse, which has to be operated only given the game's video input. OpenAI tackles this challenge using Video PreTraining, leveraging a small set of contractor data in order to pseudo-label a giant corpus of scraped footage of gameplay. The pre-trained model is highly capable in basic game mechanics and can be fine-tuned much better than a blank slate model. This is the first Minecraft agent that achieves the elusive goal of crafting a diamond pickaxe all by itself.

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OUTLINE:

0:00 - Intro

3:50 - How to spend money most effectively?

8:20 - Getting a large dataset with labels

14:40 - Model architecture

19:20 - Experimental results and fine-tuning

25:40 - Reinforcement Learning to the Diamond Pickaxe

30:00 - Final comments and hardware

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Blog: https://openai.com/blog/vpt/

Paper: https://arxiv.org/abs/2206.11795

Code & Model weights: https://github.com/openai/Video-Pre-Training