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Practical AI
Prompting the future
Mar 20, 2024
Jared Zoneraich, founder of PromptLayer, dives into the cutting-edge world of prompt engineering. He highlights its evolution as a vital skill in generative AI. Listeners learn about the importance of tailored communication strategies for different language models. Jared emphasizes the necessity of systematic methodologies and user feedback in optimizing prompts. He discusses managing updates and the balance between stability and adaptability in AI responses. Finally, he explores future trends, focusing on resilient platforms that adapt to user needs.
45:59
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Quick takeaways
- Prompt engineering is crucial for tuning inputs to language models, distinguishing it from traditional ML hyperparameter tuning.
- Tailored prompting strategies are necessary for interacting with different language models to elicit desired responses.
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Understanding Prompt Engineering and Its Evolution
Prompt engineering has emerged as a crucial skill alongside generative AI advancements, with a focus on tuning the inputs to language models (LMs). Starting from the GPT-3 days, the importance of prompt engineering became evident, leading to a deeper exploration of its potential. The term has evolved as more companies like Scale AI have embraced it, with a focus on tuning inputs, including prompts and model configurations, distinguishing it from traditional ML hyperparameter tuning.
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