【AI Beginner's Guide】2: AI Prompt Words

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【AI Beginner's Guide】2: AI Prompt Words

The term "prompt" in Chinese means "trigger." In the field of Natural Language Processing (NLP), it is more akin to a concept of "mutual understanding" rather than a strictly defined term.

In essence, a prompt is the user's input to a large language model, which can be a complete question, a dialogue snippet, or even just a single word or sentence.

The model generates a response or output based on this prompt.

You can think of it as the "starting point" of a conversation with the model, where you set the context and requirements, and the model generates a response based on that information.

If you'd like to delve further, we can explore a question:

We already understand the concept of prompts, but how can the quality of responses obtained through prompts be significantly improved when using applications like ChatGPT?

We need to understand the workings of Transformer models (such as GPT). These models are trained to predict the next word given a sequence of words (or context).

They analyze vast amounts of text data to grasp semantics and grammatical rules and use these rules to predict the next word.

Prompts play a role in this process by providing context for the model to generate output.

You can think of them as guiding the model's direction among numerous possible outputs.

High-quality prompts act as explicit guidance for the model, helping it better understand user intent and generate more accurate responses.

Rather than being a command, it's more like "guiding" the model's output.

Below, I'll provide an example to illustrate:

For instance, if you're not a single nobleman like the author, you'll likely encounter situations like the following when spending time with your girlfriend:

When you're out for dinner and ask your girlfriend what she wants to eat, and she replies with "anything."

So, you foolishly order something randomly, but when you sit down happily to serve her, she tells you to buzz off.

Faced with this heartless and cruel situation, you're left wondering where you went wrong.

Now, let's consider a successful scenario:

One day, your girlfriend comes back from grocery shopping and sees you lying on the couch, so she walks over.

Sitting next to you, she mutters to herself, "I'm so torn about whether to buy xxx."

If you're a novice, you might have no reaction or even be indifferent to the girl's words.

But if you're experienced, upon hearing the girl's words, you might smirk,

Then, you casually pull out your wallet, give it to her, and say, "Buy it!"

And at that moment, seeing that the other person understands your hint, the final outcome... well, those who understand know.

After reading the examples above, I believe clever folks should understand it to some extent.

Those who don't understand prompts when interacting with GPT will be like the first example.

Although GPT does write corresponding responses according to your request, you might still be dissatisfied because it hasn't understood your meaning at all.

Moreover, what's more frustrating is that you can't even blame it.


On the other hand, those who understand prompts when communicating with GPT will make GPT inherently emotionally intelligent.

This enables it to provide better answers to your questions.

In short, a prompt is the user's input to a large language model, which can be a complete question, a dialogue snippet, or even just a single word or sentence.

The model generates a response or output based on this prompt.

You can think of it as the "starting point" of a conversation with the model, where you set the context and requirements, and the model generates a response based on that information.

AI prompts, or Artificial Intelligence prompts, are a technique used to make computers understand and generate human language through Natural Language Processing technology.

They are widely used in scenarios such as smart customer service, virtual assistants, machine translation, text generation, etc.

Learning AI prompts can help us better understand and master Natural Language Processing technology, thereby improving efficiency in interacting with artificial intelligence.

Specifically, it has the following benefits:

  1. Improve work efficiency: In daily life and work, we often need to deal with large amounts of text information, such as reading emails, writing reports, analyzing data, etc. By learning AI prompts, we can quickly obtain key information and improve work efficiency.

  2. Enhance AI application capabilities: With the continuous development of artificial intelligence technology, more and more application scenarios require the use of AI prompts. Mastering AI prompts can help us better utilize artificial intelligence technology and improve application capabilities.

  3. Promote interdisciplinary learning: AI prompts involve multiple disciplines such as Natural Language Processing, computer science, linguistics, etc. Learning AI prompts can promote the integration of interdisciplinary knowledge and improve comprehensive qualities.

  4. Broaden career development paths: With the widespread application of artificial intelligence in various industries, the demand for professionals mastering AI prompts is increasing. Learning AI prompts can broaden our career development paths and enhance competitiveness.

To learn AI prompts effectively, you can follow these steps:

  1. Learn the basic concepts of prompts and become proficient in using various types of large models for dialogue (you can directly query and use them in the lower right corner of the public account).

  2. Read the prompt technique section of the official OpenAI documentation thoroughly.

  3. Find the prompts you need for reference and questioning and identify the points where template prompts cannot meet your needs, and optimize them accordingly.

  4. Master at least one or two classic prompt frameworks and be able to write your own prompts based on the framework principles.

To further advance your understanding and application of prompts, you can:

  1. Familiarize yourself with prompt tuning methods and frameworks.

  2. Master the deployment and construction of small models, and have your own methodology and tools for dataset training.

  3. Familiarize yourself with adversarial prompt-related knowledge.

  4. Test competitors and your own prompt defense capabilities through prompt leaking.

  5. Keep abreast of the latest knowledge related to prompt attacks and continuously improve your prompt product defenses.

  6. Understand prompt robustness-related knowledge and have methods and tools for high-frequency testing of prompts.

  7. Familiarize yourself with customer service models, use effective communication methods to grasp user needs and expectations for implementation results.

  8. Extend prompt writing skills to product and service capabilities, including but not limited to product packaging, payment channels, compliance, intellectual property agreements, contract law, operation mode, promotion strategies, customer maintenance, pre-sales consultation, after-sales service, etc.

To learn AI prompts effectively, you can:

  1. Learn the basics of Natural Language Processing: Understand the basic concepts, techniques, and methods of Natural Language Processing to lay a foundation for learning AI prompts.

  2. Master programming languages: Learn Python and other programming languages to master basic skills in data processing and model training.

  3. Learn AI prompt-related technologies: Understand common AI prompt models and algorithms, such as BERT, GPT, etc., and grasp their principles and application methods.

  4. Practice projects: Participate in practical projects, apply the knowledge learned to solve practical problems, and improve practical capabilities.

  5. Keep abreast of industry trends: Pay attention to the development trends of artificial intelligence, understand the latest AI prompt technologies and application scenarios.

  6. Join communities: Join AI prompt-related learning communities, exchange learning experiences with peers, and make progress together.

  7. Continuous learning: Artificial intelligence technology is constantly evolving and iterating. Learning AI prompts requires continuous follow-up of new technologies

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