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Prompting the future
Practical AI: Machine Learning, Data Science, LLM
Navigating the Challenges of Prompt Engineering
The evolution of prompt engineering has seen a shift from hobbyists to AI-first startups and eventually to 'real' companies making revenue from AI products. There is a maturation in the approach of companies towards AI and language models (LMs), where prompt engineering has become crucial for collaboration among stakeholders. The discipline of prompt engineering requires systematic methodologies due to building upon probabilistic technology, leading to models providing varying answers and being perceived as black boxes, making traditional deterministic troubleshooting methods impractical.
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