Prompt Engineering
The practice of crafting and optimizing input prompts to elicit desired outputs from AI language models, emerging as both a skill and a job category in the AI economy.
Prompt engineering has emerged as one of the new AI-related job categories identified by the World Economic Forum. AI job postings have grown 5.4x since 2019, with prompt engineering among the fastest-growing specializations. The skill bridges the gap between human intent and AI capability, and is increasingly valued as 78% of organizations now use AI in at least one business function.
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Related Terms
Artificial General Intelligence (AGI)
A hypothetical form of AI that can understand, learn, and apply knowledge across any intellectual task at or above human level, rather than being specialized for specific tasks.
ChatGPT
OpenAI's conversational AI assistant, launched in November 2022, which catalyzed the current generative AI boom by demonstrating the capabilities of large language models to a mainstream audience.
Fine-Tuning
The process of further training a pre-trained AI model on a specific, smaller dataset to specialize it for a particular task or domain, requiring far less compute than training from scratch.
Foundation Model
A large AI model trained on broad data that can be adapted to a wide range of downstream tasks — examples include GPT-4, Claude, Gemini, and Llama.
Frontier Model
The most capable and advanced AI models at any given time, typically trained with the largest compute budgets and achieving state-of-the-art performance on benchmarks.
Generative AI
AI systems that can create new content — text, images, code, audio, video — rather than simply analyzing or classifying existing data. Large language models and diffusion models are the primary architectures.
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