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You’re probably thinking that I’m talking nonsense; just hear me out.
Ever since, OpenAI has released ChatGPT for the public to use. There has been an influx of new ideas due to the varied use cases of this tool. Well, as this tool is discovered more and more and adopted worldwide by several big organizations, a new phrase has come out that people on Twitter are often referring to. That is prompt engineering.
Since you are reading this, I assume you are aware that having good knowledge to prompt generative AI systems such as ChatGPT is significant to staying ahead of the competition.
Seeing the above job description, I believe that a new set of abilities will be highly valuable, will emerge as a new highly skilled and highly paid job, and will be beneficial to those who learn to master them.
Prompt engineering will be on demand
ChatGPT was released approximately two months ago, and ever since its release, AI has gone mainstream, and more and more people have started talking about it.
Now that organizations such as Google and Microsoft have decided to go all in on AI, it will reach the zenith of consumer technology.
Bill Gates has also said that ChatGPT will “change our world” just like the internet did. He also said that tools like these will kill boilerplate or boring work and make people more creative and productive.
Even though ChatGPT has been the first truly global phenomenon and an unprecedented success story, it’s far from reaching the 1 billion+ users that other software products, like Microsoft Windows or Google Search, have.
As this technology is adopted more widely, the interface for using it needs to be improved as well. That’s where prompt engineering comes into play.
The goal of prompt engineering is to control the output of the language model (AI tool) by providing it with specific context, constraints, rules, and so on. This can be accomplished by carefully and manually crafting the input text or by providing additional information, such as keywords or labels, along with the input text to ChatGPT or other tools.
The prompt engineering process can be iterative, with the model’s output being analyzed and the prompt adjusted based on the results. You can also generate questions and answers and learn a lot from the different responses.
Current prompt engineering is in its early stages. There’s huge room for improvement, and we’re only scratching the surface of a rich spectrum of possibilities.
Prompt Engineering will not last forever
As we have discussed so far, prompt engineering is a method of communicating with AI systems using human language.
In an interview, Sam Altman said that prompt engineering is “just” a phase in the goal of making machines understand human language naturally. He did expand upon the idea that newer methodologies will replace prompt-based queries.
But it will still be important to know how to interact with AI machines to get the best output possible.
Prompt engineering will be, pretty much literally, the only means we’ll have to talk to these increasingly powerful AI machines. Several websites that teach prompting have emerged, and one such website is Learn Prompting, which has already amassed over 100,000 followers.
These are exciting times in technology, and I can’t wait to see what it has in store for us.