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"The Cognitive Revolution" | AI Builders, Researchers, and Live Player Analysis

OpenAI Fine-Tuning Update, Acceleration Debate, and Bundling AI Services

Sep 26, 2023
01:18:49
Snipd AI
The podcast discusses OpenAI GPT-3.5 fine-tuning updates, using GPT-4 outputs for training, when to accelerate AI, and the potential of AI bundles. They also explore training models on synthetic data, improving model performance with chain of thought prompts, and the displacement of human roles by AI. The podcast dives into policies and risks in AI development, job displacement concerns, and the challenges of coordinating businesses for AI bundling.
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Podcast summary created with Snipd AI

Quick takeaways

  • Training on synthetic data using GPT-4 can significantly improve the performance of models like GPT 3.5, offering cost and time savings.
  • The concept of AI bundles, similar to cable bundles, can provide affordable and accessible access to multiple AI apps, benefiting both customers and developers.

Deep dives

GPT 3.5 Turbo Fine Tuning Update

GPT 3.5 turbo fine-tuning has been a great experience, with fast and easy-to-use models. The process of training on chain of thought has shown impressive results, significantly improving performance. Synthetic data generation from GPT-4 and fine-tuning on 3.5 has proven successful, providing cost and time savings. This approach of training on synthetic data shows promise and could be a game-changer in various industries. There is also potential for a bundle model, similar to cable bundles, where users can access multiple AI apps through a single subscription. This concept could help address the high churn rate and cost of multiple subscriptions faced by AI app developers and customers.

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