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Top Links: >> 80. Technology >> Internet Technology Summit Program >> 7. Enterprise, Knowledge Architecture, IoT, AI and ML >> 7.1.Critical Thinking - the first step to Knowledge Engineering
Current Topic: 7.1.4. Prompt Engineering
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What is Prompt Engineering?
Prompt engineering is a crucial aspect of effectively interacting with AI language models.
Today it is the necessary element to upgrade development skills, regardless of the type of development .
The term refers to the art of crafting inputs (or "prompts") to an AI in a way that elicits the most accurate, relevant, or creative responses.

Why Prompt Engineering?
With all excitement coming of the recent AI tools, they are really just the tools. There is a need for education and business to make them really useful.
We offer the platform and services to convert the tools into useful helpers, to support education and business decision making and accelerate knowledge sharing via conversational AI.
While using our platform and services you master the new skill: efficient interaction with AI.

What is the best practice on prompt engineering?

Here are some best practices for prompt engineering:

Be Specific and Detailed: Clearly articulate what you want. The more specific your prompt, the more likely you are to get a relevant response. For example, instead of asking "tell me about cars," ask "can you provide an overview of the evolution of electric cars since 2010?"

Use Clear and Concise Language: Avoid ambiguity and overly complex sentences. Clear and straightforward language helps the AI understand your request better.
Was it clear so far? Highlight the text in question Or

Provide Context When Necessary: If your question or request is about a less common topic or requires specific knowledge, include a brief background. For example, "In the context of quantum computing, what are the potential implications of using qubits instead of bits?"

Sequence Your Questions Logically: If you have multiple questions, arrange them in a logical order. This helps the AI provide coherent and structured responses.

Utilize Keywords and Relevant Terms: Incorporate specific keywords or technical terms related to your query. This signals the AI to focus on the relevant domain or context.

Set Clear Expectations: If you're looking for a specific type of response (like a summary, a list, an explanation, etc.), state that explicitly in your prompt.

Iterative Approach: If the first response isn't quite what you're looking for, refine your prompt based on the response to guide the AI more precisely.

Be Ethical and Responsible: Frame prompts in a manner that is respectful, non-offensive, and avoids biases. Ensure that your requests comply with ethical guidelines and legal standards.

Understand the Model's Limitations: Recognize that AI models have limitations in terms of understanding and accuracy, especially for very recent, very niche, or subjective topics.

Experiment and Learn: Prompt engineering often involves trial and error. Experiment with different phrasings and structures to see what yields the best results.

By following these best practices, you can enhance the effectiveness of your interactions with AI language models and get more accurate and relevant responses to your queries.

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