4 Years of Prompt Engineering in 16 Minutes: GPT Masterclass
Jan 30, 2025
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Exploring prompt engineering in GPT models, techniques for language processing, Bloom's Taxonomy application, language model capabilities, and imagination in problem-solving. Speaker shares insights from prompt engineering journey since GPT-2 and discusses versatile applications of language processing techniques.
21:47
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Quick takeaways
Prompt engineering involves condensing and transforming content succinctly.
Language models exhibit emergent capabilities like logical reasoning and creative hallucination.
Deep dives
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Understanding Different Types of Prompt Operations
Prompt engineering involves reductive operations such as summarization, extraction, and characterization, which aim to condense, extract, or define content succinctly. Transformational operations like reformatting, refactoring, and modification focus on changing presentation or rewriting content for clarity or different intent. Generative operations, such as drafting, planning, and brainstorming, expand and create new content based on specific instructions or parameters.
Exploring Latency, Emergent Capabilities, and Bloom's Taxonomy
Latency and emergence in language models refer to activating latent content and discovering emergent capabilities like implied cognition, logical reasoning, and in context learning. Bloom's Taxonomy highlights language models' ability to remember, understand, apply, analyze, evaluate, and create, reflecting their comprehensive cognitive functions. The discussion emphasizes leveraging latent knowledge, emergent intelligence, and creative hallucination in utilizing language models for diverse tasks.
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