How to write effective text inputs for AI

Writing effective text inputs for AI can be tricky. Robots are programmed and may not understand subtle nuances that humans can understand. When writing for AI, it is important to avoid complex language and semantics so that robots can more easily comprehend the information being given to them. It should also be written in as natural a way as possible instead of robotic terminology or robot-specific instructions — this ensures that the conversation between a human and an AI will flow just as naturally as if two humans were speaking. Writing effective text inputs for AI requires planning, forethought, and immersive understanding of how robots process input — but with effort and practice, anyone can become adept at crafting compelling, accurate text formats for robots.

Robots are becoming an increasingly important part of our lives, but for them to operate as seamlessly as possible, humans must provide effective written input. Writing for robots should be simple and precise - using plain language that is natural and easy to understand. Special attention should be paid to ensuring that Robots understand the instructions they are given. Robots can't intuit what we want them to do so it's important to double check your writing before submitting it to ensure your Robots are receiving well-defined instructions. Getting writing right when giving instructions to Robots is key in achieving efficient outcomes.

What are text inputs for AI

For those unsure as to what text inputs (or prompts), these are the instructions we feed AI writers in order to get the most useful output. If the input is not clear, then the results it produces will often be irrelevant, or not aligned with the purpose of the content.

Be specific

As the writer, you need to give AI clear, descriptive instructions where possible, so that content generated is relevant to the story you want to tell. In general, the more information we are able to feed the machine, the better the results are going to be.

For technical or niche subjects, this is particularly true.

Most Natural Language Programming (NLP) models (including Mark Copy AI), are built on GPT-3 by OpenAI. It’s the most powerful AI machine learning tool built to date, so it makes sense. GPT-3 generates text based on what it has learned from reading approximately 10% the internet, and features about 175 billion trainable parameters (the values that a neural network tries to optimise during training).

So while the training is excellent on nearly every topic under the sun, if your writing that is very technical, or very niche, try making the instructions you are giving the machine as detailed as you can. The longer the input the better in most cases.

To make things even more interesting, the input that a user puts into Mark Copy AI, isn’t the prompt that is sent to GPT-3.

I hope you were still sitting down.

This is because there is additional training going on behind the scenes to make sure that the result is as intended. Below is an example – exaggerated for comedic effect – of a text to image AI program DALL-E: