Introduction to ChatGPT study guide 2024

What is ChatGPT? ChatGPT, by OpenAI, is a conversational language model, which means it can answer questions or perform tasks that yield a text-based response. Standard chatbot vs. ChatGPT Standard chatbots are usually designed to return a predetermined response to a limited number of questions. ChatGPT is far more generalizable, as it uses its understanding of language to interpret the question or task and determine the most appropriate response. Generative AI ChatGPT is an example of a generative AI model. Generative AI is a subset of artificial intelligence and machine learning, where a model creates new content based on patterns in information it has already seen. In ChatGPT's case, this generated content is text, but other models exist for image, audio, and even video generation. From prompt to response the user writes a question or instruction, which is more generally called a prompt. This prompt is passed as an input to a large language model, or LLM. LLMs use complex algorithms to determine patterns and structure in language. These patterns are then used to interpret the prompt and generate new, relevant language in response to it. From prompt to response part 2 Finally, the generated text, or response, is returned to the user. Summarizing text ChatGPT is great at summarizing text or concepts for a particular audience, which is useful when summarizing reports for different stakeholders or interpreting complex information. Summarizing text Example t would be better if we could boil it down to two key sentences. Notice that we don't have to instruct it to summarize GDPR again; ChatGPT will actually remember the information and context from earlier in the conversation. The ability for ChatGPT to remember the conversation history and for the user to provide follow-up corrections to responses are two extremely powerful capabilities of the model. Creating marketing content Let's ask ChatGPT to write a tweet encouraging people to acquire data literacy skills. ChatGPT is already being applied to streamline many different marketing tasks, including creating email templates, writing blog post titles and descriptions, and copyediting large bodies of text. Generating and debugging code ChatGPT is able to generate template code, explain why code isn't working, and even make suggestions for improvements! Why utilize ChatGPT? ChatGPT is able to perform many time-consuming tasks with greater efficiency. This workflow of AI doing the legwork and a human providing the finishing touches saves a substantial amount of time and money. Implementing ChatGPT into products will also allow for greater personalization of content, delivering more value to customers. Demystifying the LLM the LLM was shown a huge amount of text data, which is like the large building block wall. From this data, it builds its understanding of the structure of language by looking at the frequency and order of words, which are like the differently-colored building blocks. the training data, and the sheer amount and variety of data used to train ChatGPT is a large part of its success. The model itself used complex algorithms to detect these language patterns in the training data, and it was fine-tuned through iterative processes that included rating the quality of the responses. So when we provide a prompt to ChatGPT, it is essentially trying to complete a building block wall, using its understanding of the training data to generate the words that are most likely to follow the prompt. Limitation 1 - Knowledge cutoff ChatGPT was trained on data up to a certain date, and the model isn't connected to the internet or other external sources, so it isn't aware of events beyond this date. Limitation 2 - Training data bias ChatGPT was trained on a massive text dataset from a variety of sources, including books, articles, and websites, but this data could contain biases. The model may learn these biases and produce biased responses. Limitation 3 - Context tracking ChatGPT has the ability to build on information and context from earlier in the conversation, so follow-up corrections can be made. However, if the topic of the conversation shifts multiple times, ChatGPT can struggle to keep track of the context and generate inaccurate or irrelevant responses. A good rule of thumb is to keep a conversation to one topic and create new conversations for different topics. Limitation 4 - Hallucination hallucination, which is when the model confidently tells us inaccurate information. This often occurs when attempting to go beyond ChatGPT's knowledge cutoff or abilities. Limitation 5 - Legal and ethical considerations It's easy to fall into one of these legal gray areas if the use cases for ChatGPT aren't properly scoped so that ownership and legal implications are well-understood and accepted. How does ChatGPT interpret a prompt? First, ChatGPT identifies the broad topic of the prompt. In this case, the phrases job description, data scientist, and New York help the model identify that the prompt is about a job description for a specific role and location. How does ChatGPT interpret a prompt? part 2 Next, ChatGPT attempts to understand what the prompt is requesting. In this case, the verb, write, and job description indicate the task being given to ChatGPT. Data scientist and New York provide additional context to help populate the response with relevant information. How does ChatGPT interpret a prompt? part 3 More context could be added to the prompt for greater personalization, such as key role-specific skills and company culture information. Prompt engineering Prompt engineering is the process of writing prompts to maximize the quality and relevance of the response. Writing tips for prompt engineering The first guideline is to be clear and specific. In the prompt, we should specify roughly how long we want the resulting summary to be: one page, one paragraph, or even one sentence. Second, keep prompts concise. This means removing any unnecessary information or linguistic frills that don't provide extra context for the task at hand - these extras will only dilute the important information and keywords. Finally, use correct grammar and spelling in prompts. Provide examples if necessary... Another way to superpower our prompts is to provide examples. For example, let's use ChatGPT to create a list of example customer name