Imagine spending hours tailoring content for different audiences based on their persona. Now, consider being able to generate that content with just a single click, saving time. Sounds unrealistic, doesn't it? Well, a claim like that requires evidence, right?
Let's give it a try...
To begin with, first, we need to understand what is large language model (LLM)!
What is Large Language Model (LLM's)?
A large language model (LLM) is like a brainy friend in the digital world. It's an AI program that's really good at understanding and creating text, and it can do other cool stuff too. LLMs learn by studying massive amounts of data, kind of like how we learn from lots of experiences. They're based on a special kind of neural network called a transformer model, which helps them process information in a smart way.
The large language model has access to a vast amount of data and requires very little effort on our part to generate content—that's prompting. Our communication with the large language model involves the instructions we give it and the responses it generates based on our input.
How audience persona work?
What we want is to think of ChatGPT as an actor that can play different roles. When we give it information about the situation, it uses that info to adjust its responses and act accordingly. It's like giving the actor a script, and it tailors what it says based on that.
The contextual statements to play around with this prompt is simple,
Explain X to me.
Assume that I am Persona Y.
You will need to replace "Y" with an appropriate persona, such as "have limited background in computer science" or "a healthcare expert". You will then need to specify the topic X that should be explained.
The idea behind this persona pattern is to give some instruction to LLM to generate output tailoring based on a particular persona it has provided.
The cool thing is, you don't have to give a bunch of big instructions or say follow guidelines, just type "act as <persona>" and it'll come up with the right response.
For example, I just ask ChatGPT, "Explain large language model to me, assume that I've no background in Computer Science".
Now, just tweak a bit further now I'm going to ask, "Explain large language model to me, assume that I'm Christopher Columbus".
Now, notice how it figures out on its own, "Who is the audience I'm giving this information to?" We get two responses for different audiences with a little tweak, and eventually, it knows how to give the right information to the audience.
Again tested a bit more, "Explain large language model to me, assume that I'm not well educated and bored easily".
Now just make a minor change, "Explain large language model to me, assume that I'm good at maths and need explanation in maths."
Now, apply this strategy to diverse marketing content, customizing it to meet audience needs. It serves as a valuable approach for structuring an effective social marketing techniques.
Remember, the more context you give to LLM, the more personalized output it makes. You have to try different techniques and prompts to get the most out of generic information.
Few more Examples you can test out by yourself:
Explain large language models to me. Assume that I am a bird.
Explain how the supply chains for US grocery stores work to me. Assume that I am Ghengis Khan.
Explain how AI is threatening to humans. Assume that I've no technical background in AI.
Decode the mysteries of quantum physics. Assume that I am a time-traveling astronaut.
Elaborate on the impact of AI in the field of robotics. Assume that I am Shakespeare.
Clarify the workings of the finance industry. Assume that I am a time-traveling pirate.
Discuss the complexities of international diplomacy. Assume that I am a doctor.
References:
https://www.cloudflare.com/learning/ai/what-is-large-language-model/#:~:text=A%20large%20language%20model%20(LLM)%20is%20a%20type%20of%20artificial,network%20called%20a%20transformer%20model.
https://www.coursera.org/learn/prompt-engineering/lecture/nH9vM/audience-persona-pattern
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