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Computation and Language - The Prompt Report A Systematic Survey of Prompt Engineering Techniques
Hey PaperLedge crew, Ernis here, ready to dive into another fascinating piece of research! Today, we're tackling something super relevant in our increasingly AI-powered world: prompt engineering. Now, I know that sounds a bit technical, but trust me, it's something we all do, whether we realize it or not, whenever we interact with AI like ChatGPT.
Think of it like this: you're a chef, and the AI is your incredibly powerful but somewhat clueless kitchen appliance. It can do amazing things, but only if you give it the right instructions – the right prompt. Prompt engineering is basically the art and science of crafting those perfect instructions.
So, what exactly is prompt engineering? This paper dives deep into that question. The researchers noticed that even though everyone's talking about prompts, there's a lot of confusion. Different people use different words to mean the same thing, and nobody really agrees on what makes a good prompt. It's like everyone's speaking a slightly different dialect of "AI language."
What the researchers did was wrangle all of this chaos into something organized. They created a taxonomy – essentially, a giant family tree – of all the different prompting techniques out there. They identified 33 key terms you need to know, and cataloged 58 different techniques specifically for Large Language Models (LLMs) like ChatGPT, and another 40 techniques for other types of AI.
But it's not just a list. They also provide best practices and guidelines. They give advice on how to actually use these techniques effectively, especially with cutting-edge AIs like ChatGPT. They even did a deep dive – a meta-analysis – on one particular type of prompting called "prefix-prompting."
"This paper presents the most comprehensive survey on prompt engineering to date."
So, why should you care about this? Well, if you're a:
Ultimately, it's about understanding how to communicate effectively with these increasingly powerful AI systems. It's about moving beyond just typing in random requests and learning how to engineer the perfect prompt to get the desired result.
Now, this research raises some interesting questions for our discussion. For example:
I'm really looking forward to unpacking this one with you all. It's a crucial area for understanding our AI-driven future!
Credit to Paper authors: Sander Schulhoff, Michael Ilie, Nishant Balepur, Konstantine Kahadze, Amanda Liu, Chenglei Si, Yinheng Li, Aayush Gupta, HyoJung Han, Sevien Schulhoff, Pranav Sandeep Dulepet, Saurav Vidyadhara, Dayeon Ki, Sweta Agrawal, Chau Pham, Gerson Kroiz, Feileen Li, Hudson Tao, Ashay Srivastava, Hevander Da Costa, Saloni Gupta, Megan L. Rogers, Inna Goncearenco, Giuseppe Sarli, Igor Galynker, Denis Peskoff, Marine Carpuat, Jules White, Shyamal Anadkat, Alexander Hoyle, Philip Resnik
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By ernestasposkusHey PaperLedge crew, Ernis here, ready to dive into another fascinating piece of research! Today, we're tackling something super relevant in our increasingly AI-powered world: prompt engineering. Now, I know that sounds a bit technical, but trust me, it's something we all do, whether we realize it or not, whenever we interact with AI like ChatGPT.
Think of it like this: you're a chef, and the AI is your incredibly powerful but somewhat clueless kitchen appliance. It can do amazing things, but only if you give it the right instructions – the right prompt. Prompt engineering is basically the art and science of crafting those perfect instructions.
So, what exactly is prompt engineering? This paper dives deep into that question. The researchers noticed that even though everyone's talking about prompts, there's a lot of confusion. Different people use different words to mean the same thing, and nobody really agrees on what makes a good prompt. It's like everyone's speaking a slightly different dialect of "AI language."
What the researchers did was wrangle all of this chaos into something organized. They created a taxonomy – essentially, a giant family tree – of all the different prompting techniques out there. They identified 33 key terms you need to know, and cataloged 58 different techniques specifically for Large Language Models (LLMs) like ChatGPT, and another 40 techniques for other types of AI.
But it's not just a list. They also provide best practices and guidelines. They give advice on how to actually use these techniques effectively, especially with cutting-edge AIs like ChatGPT. They even did a deep dive – a meta-analysis – on one particular type of prompting called "prefix-prompting."
"This paper presents the most comprehensive survey on prompt engineering to date."
So, why should you care about this? Well, if you're a:
Ultimately, it's about understanding how to communicate effectively with these increasingly powerful AI systems. It's about moving beyond just typing in random requests and learning how to engineer the perfect prompt to get the desired result.
Now, this research raises some interesting questions for our discussion. For example:
I'm really looking forward to unpacking this one with you all. It's a crucial area for understanding our AI-driven future!
Credit to Paper authors: Sander Schulhoff, Michael Ilie, Nishant Balepur, Konstantine Kahadze, Amanda Liu, Chenglei Si, Yinheng Li, Aayush Gupta, HyoJung Han, Sevien Schulhoff, Pranav Sandeep Dulepet, Saurav Vidyadhara, Dayeon Ki, Sweta Agrawal, Chau Pham, Gerson Kroiz, Feileen Li, Hudson Tao, Ashay Srivastava, Hevander Da Costa, Saloni Gupta, Megan L. Rogers, Inna Goncearenco, Giuseppe Sarli, Igor Galynker, Denis Peskoff, Marine Carpuat, Jules White, Shyamal Anadkat, Alexander Hoyle, Philip Resnik