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ChatGPT's year of wonder – Part 1: Catalysing transformation in the cultural landscape

ChatGPT's year of wonder – Part 1: Catalysing transformation in the cultural landscape
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Google Bard , Manas Gulati , Sam Altman , Rajiv Dingra , Adobe Firefly , Neural Text , Performance Max , Dynamic Search ,

Prompt Engineering

Prompt Engineering, also known as In-Context Prompting, refers to methods for how to communicate with LLM to steer its behavior for desired outcomes without updating the model weights. It is an empirical science and the effect of prompt engineering methods can vary a lot among models, thus requiring heavy experimentation and heuristics.
This post only focuses on prompt engineering for autoregressive language models, so nothing with Cloze tests, image generation or multimodality models. ....

Monte Carlo , Wikipedia Apis , Autoprompt Shin , Li Liang , Toolformer Schick , Program Of Thoughts , Prompt Engineering , In Context Prompting , Reinforcement Learning , Human Feedback , Self Taught Reasoner , Interleaving Retrieval Cot , Neural Text , Automatic Prompt Engineer , Open Domain Question Answering , Google Search , Tool Augmented Language Models , Before Use , Improving Few Shot Performance , Language Models , Makes Good In Context Examples , Ordered Prompts , Find Them , Overcoming Few Shot Prompt Order Sensitivity , Context Instruction Learning , Consistency Improves Chain ,