This Day in AI Podcast
EP31: Fine-Tuned MrBeast Model Results, Chris Makes a Game, AGI Safety Paper + ERNIE GPT
Sep 8, 2023
MrBeast, an internet personality and YouTuber known for his philanthropy and expensive challenge videos, talks about fine-tuning an AI model to generate MrBeast video ideas. The podcast also discusses the challenges of selecting a model and dataset for fine-tuning, the value of wrapper apps and commercializing language models, collaborative game development using Chat Dev, skepticism about easily controlling AI, and OpenAI's recent announcements and company identity.
56:52
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Quick takeaways
- Training models with code reveals sparks of AGI, showcasing the potential for advanced AI capabilities.
- Implementing prompt-to-model for generating Mr. Beast episode ideas is challenging but yields more specific and creative outputs compared to GPT-4.
Deep dives
The importance of training models to think with code is highlighted in the podcast
The podcast discusses the significance of training models to think with code, emphasizing that it reveals sparks of AGI inside the models being trained. The experiment conducted involves using GPT-4 and prompt-to-model to generate Mr. Beast episode ideas. While GPT-4's output is generic, prompt-to-model's output is more specific and creative. The process of implementing prompt-to-model and achieving results was challenging, requiring several iterations and troubleshooting. The paper on code llama emphasizes the value of training models on code-heavy data sets to improve code generation capabilities and performance.
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