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With the recent news from OpenAI announcing customizable GPTs, we are revisiting the program simulation prompt engineering technique talk. This is a second screening of this talk because the first one was so popular. Program simulation prompt engineering could very well prove to be the most powerful technique available to leverage this new functionality.
You don’t want to miss this meetup.

We had the pleasure of hosting Giuseppe Scalamogna discussing his research on “Prompt Engineering Evolution: Defining the New Program Simulation Prompt Framework”, we are thrilled to welcome him back for another insightful session. His research delves into the captivating realm of prompt engineering, which offers many ingenious techniques to shape the responses of AI models like ChatGPT. From Chain-of-Thought (CoT), Instruction-Based, N-shot, Few-shot, to unconventional methods like Flattery/Role Assignment – each method is a source of inspiration for creating a library of prompts that cater to various requirements. Bearing in mind the rapid pace of innovation in prompt engineering, there’s a chance this method may already exist in some form.



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