DataFramed
#241 Getting Generative AI Into Production with Lin Qiao, CEO and Co-Founder of Fireworks AI
Sep 5, 2024
Lin Qiao, CEO and Co-Founder of Fireworks AI, is a former engineering leader at Meta and LinkedIn, specializing in generative AI. She discusses the transition of generative AI from experimentation to mainstream use, emphasizing the importance of fine-tuning models for specific business needs. Lin addresses the challenges of AI integration, including cost efficiency and managing hallucinations. She also explores the rising competitiveness of smaller models and the critical role of quality evaluation datasets in deploying effective AI solutions.
44:47
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Quick takeaways
- Experimentation and careful problem framing are essential for effectively transitioning generative AI models from prototypes to production environments.
- Fine-tuning large language models requires clear evaluation metrics and collaboration between product managers and machine learning engineers to meet organizational objectives.
Deep dives
The Importance of Experimentation in AI
Experimentation is crucial in the development and implementation of AI, particularly in framing the problems that need solving. The way a problem is framed directly influences the choice of technology and models integrated into an AI solution. As generative AI applications move from prototypes to production, organizations face challenges in maintaining performance and managing costs effectively. Achieving a balance between customer satisfaction and financial viability is essential in this rapidly evolving landscape.
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