The Future is Fine Tuned (with Dev Rishi, Predibase)
Thinking Machines: AI & Philosophy
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Fine-Tuning Models for Optimal Performance
The chapter explores the challenges and benefits of fine-tuning models for specific tasks, discussing methods like Lorax and Lora fine-tuning to optimize performance. It delves into the implications of managing GPU resources efficiently, the competition between model providers like OpenAI, and the debate over the necessity of smaller models for different applications. The conversation also touches on the strategic direction of OpenAI in model development and the business models surrounding hosting AI models.
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