NCsoft’s New AI: The Ultimate Stuntman! 🏋 | Summary and Q&A

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January 22, 2022
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NCsoft’s New AI: The Ultimate Stuntman! 🏋

TL;DR

Using a deep neural network, AI can learn and create video game motions from unorganized human motion data, resulting in quick and fluid gameplay.

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Questions & Answers

Q: How does AI learn to create video game motions from unorganized human motion data?

The process involves training a deep neural network with unorganized motion data, allowing the AI to learn and weave together various motions seamlessly.

Q: Can the AI create realistic and agile gameplay?

Yes, the AI promises time-critical responses to commands, ensuring that the character's actions execute in real-time. This results in agile and realistic gameplay.

Q: What is policy distillation?

Policy distillation is a technique where a teacher network is trained to efficiently perform complex moves, and then a student neural network seeks to achieve the same proficiency with a smaller and more compact neural network.

Q: How quickly can the AI be trained to create video game motions?

The AI can be trained with just a few minutes of training data and takes a few hours to train. Once trained, the neural network can be used indefinitely.

Summary & Key Takeaways

  • Previous techniques have successfully used motion capture data to teach AI to learn and improve human movements, as well as simulate and predict the motion of video game characters.

  • A new method uses a deep neural network to weave together motions and create video game actions that can be played almost immediately.

  • The AI promises time-critical responses to commands, ensuring that the action executes in real-time, resulting in agile and realistic gameplay.

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