George Hotz | Programming | RL is dumb and doesn't work | Reinforcement Learning LunarLander Part 2 | Summary and Q&A

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January 10, 2024
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George Hotz | Programming | RL is dumb and doesn't work | Reinforcement Learning LunarLander Part 2

TL;DR

George Hotz discusses the potential of switching to alternative streaming platforms, X and Kick, due to frustration with Twitch's revenue split and content guidelines.

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Key Insights

  • ❓ George is considering switching to alternative streaming platforms due to dissatisfaction with Twitch's revenue split and content guidelines.
  • ✋ X offers higher revenue sharing percentages, while Kick provides more creative freedom.
  • ⛔ Twitch's revenue split and content restrictions pose challenges for George, potentially limiting his earnings and creative freedom.

Transcript

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Questions & Answers

Q: Why is George considering switching to alternative streaming platforms?

George is dissatisfied with Twitch's revenue split and content guidelines, prompting him to explore other options like X and Kick.

Q: What are the benefits and drawbacks of switching to X and Kick for streaming?

X offers higher revenue sharing percentages, while Kick provides more freedom with content. However, both platforms have limitations that may impact audience reach and discoverability.

Q: What challenges does George face on Twitch?

Twitch's revenue split and content restrictions pose challenges for George, limiting his potential earnings and creative freedom.

Q: What updates does George provide on his ongoing projects?

George discusses the significance of Reinforcement Learning (RL) in his streaming content and hints at potential upcoming projects in this field.

Summary & Key Takeaways

  • George Hotz considers the possibility of streaming on alternative platforms, X and Kick, due to dissatisfaction with Twitch.

  • He explores the potential benefits and drawbacks of these platforms and discusses the challenges of streaming on Twitch, including revenue sharing and content restrictions.

  • George also discusses the significance of RL (Reinforcement Learning) in the context of his streaming content and provides updates on his ongoing projects.

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