What is Prompt engineering?

If we give commands to generative artificial intelligence in a way that is easy for it to understand, it will give you the best results, because these artificial intelligence programs are based on a technological engineering field called prompt engineering.

In this article, we will learn about Prompt engineering from many aspects.

Here are the most important points that will be covered in the article:

• What is command engineering?
• What is the importance of command engineering?
• What are the applications of command engineering?
• The future of command engineering
• What are the duties of a command engineer?
• Command Engineering Basics
• The most important command engineering techniques

What is command engineering?

Command engineering, also known as indoctrination engineering, is a growing field these days and continues to evolve over time.

It is a new field that has emerged on the scene with the aim of developing and improving the commands directed to artificial intelligence in order to exploit the capabilities of language models to the best advantage.

Generative language models such as ChatGPT are models that contain a huge number of neural networks that enable them to train on a huge amount of data to be able to produce new content of various types.

Command engineering can be defined as a way of dealing with language models in order to perform some tasks or achieve certain goals by improving large language models, or providing some data to artificial intelligence programs to obtain the required results.

Command engineering involves using natural languages ​​to communicate with AI.

Researchers use command engineering to improve the ability of large language models to perform both mundane and complex tasks, and developers use it to design different techniques for directing efficient commands to language models.

Command engineering involves optimizing commands so that the machine understands the command and responds efficiently, and is the link between the user’s intent and the machine’s understanding.

Although there are language models that have been trained to write efficient commands and reduce human intervention, these models need experts in the field of command engineering.

What is the importance of command engineering?

1. Understand the nature of generative language models, their advantages and disadvantages, and how to direct commands to different language models.
2. Ability to improve the quality of AI output.
3. Reduce the number of revisions and modifications, which means saving time and effort.
4. Making language models produce amazing results and can be used in many applications.
5. Improving user experience in creative AI solutions.
6. It plays an important role in the business field, and through it you can improve customer service through the automated assistance provided by chatbots.

What are the applications of command engineering?

1. Content production: Command engineering can be used to generate different ideas for articles and posts, and to summarize, write, and extract information from texts.

2. Medicine: Command engineering can be used to extract information from medical data, suggest treatments, give diagnoses, suggest necessary tests, and interpret X-ray results, helping healthcare professionals make appropriate decisions.

3. Programming: Command engineering can be used to write code in different programming languages, write functions, find errors, and optimize code, which helps developers complete their tasks in less time.

4. Cybersecurity: Command engineering can be used to simulate cyber attacks, design defense systems, and detect software vulnerabilities.

The future of command engineering

The field of artificial intelligence is witnessing a qualitative leap and is developing at an increasing speed. It is expected that what will dominate the scene in the future of command engineering is automatic command generation. Language models will be more advanced and have the ability to improve and generate commands in order to obtain better results.

Researchers are working to develop ways that AI models can generate commands based on context and without the need for human intervention, a process known as adaptive prompting.

With the development of language models that process images and texts, we will find that the directed commands will not be limited to text commands, but will include images, audio, and videos, which is known as multimodal prompts.

There will be an urgent need to address AI ethics that ensure transparency, fairness, and reduce bias, known as Ethical prompting.

What are the duties of a command engineer?

The job of a command engineer is one of the jobs that companies have created in order to exploit the power of artificial intelligence, and it is one of the jobs that did not exist several years ago.

Here are the most important tasks that a command engineer may perform:

• Training AI models to produce specialized content.
• Tuning and improving AI models.
• Writing, testing, and improving commands to improve the quality of AI output.
• Building a prompt library.
• Integrating AI commands into various applications and systems.

It is worth noting that command engineers are not technicians, but rather are closer to artists who know how to address artificial intelligence in the appropriate language that it understands.

Here are the most important technical and personal skills that a command engineer must have:

• Has experience with at least one programming language such as Python.
• Able to test software and debug software.
• He has knowledge of the basics of Artificial Intelligence, Machine Learning and Natural Language Processing.
• He has knowledge of deep learning, neural networks, and how language models work.
• He has knowledge of command engineering techniques.
• He is fluent in grammar and has a large vocabulary.
• Experience in the field of specialization.
• Creative thinking.
• Problem solving.
• Data analysis.
• He has knowledge of AI ethics.
• communication.

Command Engineering Basics

The quality of the results depends on how much information you provide to the AI ​​and how you phrase the command.

To write commands directed to language models correctly, we must understand that each command consists of several basic elements, which are:

1. The role that the language model is required to perform, whether it is a marketer, a programmer, etc.
2. The task to be executed.
3. Context is additional information that gives more details about the command.
4. Input Data.
5. Output Indicator or required format, whether a table, image, etc. is required.

Note that all of these elements are not necessary to come together.

Let’s take an example that illustrates the elements of a command prompt for AI models.

It goes like this:

“You are an expert Spanish teacher, and I want to learn Spanish from scratch so that I can speak with Spaniards. Give me a 6-month timetable, stating how many hours I will study each day, what I will learn each week, and what activities and resources.”

Let’s explain this example and show the elements of the command:

In this example we used the role element in the sentence “You are an expert teacher of Spanish.”

As for the context, it was in the sentence “And I want to learn Spanish from the beginning so that I can speak with the Spanish.”

The task was in the sentence “Give me a 6-month time plan, stating the number of hours of study per day, what I will learn each week, and what the activities and resources will be.

“I want the plan in table form.”

The output was in the sentence: “I want the plan in the form of a table.”

Note that we didn’t use the input element because we didn’t need it, and we explained the task in some detail.

The basic rules followed in command engineering are:

• Clarity in directing the matter.
• Set specific conditions, such as: “Describe the pyramids to me in one line.” Here we specified one line.
• Constantly experimenting, testing and improving commands.

Now that we know some of the basics of command engineering, let’s take a look at some of its techniques.

The most important command engineering techniques

There are many techniques used in the field of command engineering, the most famous of which are:

1- Zero-Shot Prompting Technology

Large language models are trained on massive data that enables them to execute zero-shot commands like Classify, order, and any command that we don’t provide examples and context for is zero-shot.

If this technique does not work, we resort to the following technique.

2- Few-Shot Prompting Technology

In the case of complex commands we need some context to get the right answer, so some context must be provided.

The language model learns through one or more examples, and this technique is not suitable for all tasks such as reasoning tasks.

3- Chain-of-thought technique

This technique is used in thinking tasks, in which the task must be divided into smaller tasks, and we explain to him the way of thinking with examples, as it is a technique based on the sequence of ideas.

4- Self-consistency technique

It is one of the most advanced techniques and requires a number of examples for the language model to learn from.

There are other techniques but we will not discuss them in this article.

Conclusion

Command engineering is the art of addressing language models, and it requires understanding how these models work and experimenting with and optimizing commands to get more accurate results in less time.

Although the command engineer job is a newly emerging job, and it is expected to have a major impact on the future of artificial intelligence, the need for command engineers may decrease after a while due to the development of language models and their ability to improve commands automatically without human intervention in the future.