What is Prompt Engineering?
Prompt engineering is a highly lucrative skill that allows you to instruct an AI to
perform a task by providing it with a set of instructions called prompts. The
quality of your input determines the quality of your output, so constructing
effective prompts is crucial for extracting value from large language models like
GPT3.
The OpenAI Playground is a flexible platform for interacting with the OpenAI suite
of products in their natural state, which is important for learning how to engineer
prompts for the base models through the playground. In this video, we will be using
the playground to learn prompt engineering for GPT3.
Why is Prompt Engineering Important?
The importance of prompt engineering can be illustrated with a simple example of a
math equation that yields an incorrect answer due to a poor prompt. By changing the
prompt to include specific instructions, we can get the correct answer. This
concept of "garbage in, garbage out" applies to more complex tasks as well, making
prompt engineering a valuable skill for creating optimal results.
How to Prompt for Optimal Results
Within the OpenAI Playground, there are several important settings that can be
adjusted to achieve optimal results, including the model used, temperature, max
length, frequent penalty, and presence penalties. Role prompting is one method of
prompting that involves setting the AI into a certain role by including specific
prompts in your input. By mastering prompt engineering, you can create millions of
dollars worth of value and access more opportunities with AI.
When it comes to using AI models like GPT-3, there are several methods for
prompting the model to generate specific responses. One method is role prompting,
where the model is set into a specific role or persona, such as a mathematician or
a friendly assistant. By giving the model more context and understanding of the
question, it can generate better answers.
Zero-shot prompting is another method where the model is used as an autocomplete
engine, given a question or phrase to respond to without any expected structure.
One-shot prompting provides a specific structure for the model to follow based on
one example, while few-shot prompting provides multiple examples for the model to
learn from.
Chain of thought prompting is a useful tool for tasks like arithmetic, common
sense, and symbolic reasoning. By encouraging the model to explain its reasoning
step by step, it can generate more accurate responses.
The concept of zero shot chain of thought prompting is discussed in this passage.
By adding the phrase "let's think step by step" to the zero shot prompt, one can
get accurate answers. Prompt engineering is a highly valuable skill, and the
biggest opportunities for prompt engineers in 2023 and beyond are discussed in this
passage.
Opportunities for Prompt Engineers
The first opportunity is to sell prompt engineering services as demand for this
skill is exploding. The second opportunity is to create a teaching business out of
prompt engineering, as companies will need to pivot to understand and use these
models. The third opportunity is to build businesses around a well-written prompt,
such as LITA AI by Dr. Alan D Thompson, which uses a GPT-3 model to create an AI
assistant.