What is Generative AI?
Generative AI refers to a type of artificial intelligence that creates new content, ranging from text to images, based on the input it receives. These AI models, such as GPT (Generative Pre-trained Transformer), are trained on vast datasets comprising diverse forms of human-created content like articles, books, and websites. The AI learns patterns, language structures, and context from this data, allowing it to generate coherent and contextually relevant responses when given a prompt.
How the Models Work:
Generative AI models work by predicting the next word or phrase in a sequence, given an initial input or “prompt.” This prediction is based on patterns it learned during training. The model continues generating content by repeating this process, effectively “writing” in real-time. The quality and accuracy of the output depend largely on the prompt given, which is where prompt engineering comes into play.
What is a Prompt?
A prompt is the initial input or instruction you provide to a generative AI model to guide its output. Think of it as a question, command, or sentence starter that tells the AI what kind of content you want it to generate. The more precise and well-structured your prompt, the more accurate and useful the AI’s response will be.
For example, a simple prompt might be, “Write a short story about a dragon.” The AI would generate a story based on the patterns it learned during training. However, if you provide a more detailed prompt like, “Write a short story about a young dragon learning to fly in a magical forest,” the output will be more tailored to your specific request.
Let’s compare two examples:
“What is climate change?”
And
“Write about how climate change influences storm surge along the coasts during a tropical cyclone. Also, provide real world examples of climate change’s attribution to storm surge.”
In the first example we provided a very broad prompt. We are liable to get a very broad but superficial response back from the model. In our second example, we have provided very specific