ChatGPT is a variant of GPT (short for "Generative Pre-trained Transformer") that is specifically designed for generating text in a chat-like style. It is trained on a large dataset of conversational exchanges and is able to generate text that is appropriate for use in chatbots and other conversations. GPT, on the other hand, is a large language model developed by OpenAI, a Silicon Valley-based startup founded in December 2015 by Sam Altman, Elon Musk, Peter Thiel, Reid Hoffman, and Jessica Livingston, with $1Bn in funding.
You can do a lot of things with the ChatGPT AI tool. From writing essays, emails, resumes, songs, and computer software to explaining complex topics in almost any field, ChatGPT is a jack of all trades. Here's a partial list of things that ChatGPT can do:
- Classify content
- Answer questions
- Summarise long texts
- Translate languages
- Convert programming languages
- Write a job description
- Write emails
- Write essays, poetry
- Write music
- Generate lines of code based on a prompt
- Debug, and Explain Code
- Explain complicated concepts
Everyone can use ChatGPT as it is one of the biggest technology revelations of recent times. Its use cases are seemingly endless, so from students and high school teachers to programmers and writers, everyone will find a good use for ChatGPT.
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ChatGPT and other similar foundation models are one of many hyper-automation and AI innovations. It will form a part of architected solutions that automate, augment humans or machines, and autonomously execute business and IT processes. It will also likely be used to replace, recalibrate and redefine some of the activities and tasks included in various jobs.
It’s hard to say. There will be new jobs created, while others will be redefined. The net change in the size of the workforce will vary dramatically depending on the industry, location, enterprise size and offerings, etc. However, it is clear that the use of tools such as ChatGPT, hyper-automation and other AI innovations will focus on tasks that are repetitive and high-volume, with an emphasis on efficiency, increasing productivity and improving quality control. ChatGPT will also be integrated into business applications. This will make adoption easier, and relevant contextual information will be available in the applications.
No, not anytime soon. Transformer AI models like ChatGPT have a hard time telling facts from fiction. They aren't intelligent in the real sense of the word, they are just incredibly good at predicting the sequence of words that should come next to create responses that make sense.
For instance, the auto-correct and auto-complete features on your smartphone. Your smartphones can't tell what you want to type. It just predicts which sequence of words would make more sense and in what order based on what you've already typed. That's how some Transformer AI models work, but they are incredibly better at their prediction game.
Yes. OpenAI stores data that's generated when you interact with ChatGPT. According to OpenAI, the content generated by your interaction with ChatGPT is used to "improve" the AI model and could be reviewed by human AI trainers. Eventually, someone may read excerpts of your conversations.
It’s hard to say the extent of the impact created by ChatGPT and other AI tools. The creation of new jobs will occur, as well as the redefining of others. The net change in the size of the workforce will vary dramatically depending on the industry, location, enterprise size and offerings, etc. However, the use of ChatGPT, hyper-automation and other AI innovations is likely to be focused on repetitive, high-volume tasks, with an emphasis on efficiency, productivity, and quality control. Business applications will also be integrated with ChatGPT. Consequently, adoption will be easier, and applications will have relevant contextual information.
A ChatGPT prompt refers to the input or initial text provided to the ChatGPT language model to generate a response. The prompt sets the context and provides instructions for the model to understand the user's query or conversation. It helps guide the model's behavior and influences the output it produces.
ChatGPT prompt engineering refers to the practice of crafting well-defined and strategic prompts to guide the behavior and output of the ChatGPT language model. ChatGPT, developed by OpenAI, is a powerful language model based on the GPT-3 architecture, capable of generating human-like responses to a wide range of input prompts.
Prompt engineering involves designing prompts in such a way that they elicit desired responses from ChatGPT, aligning with specific goals and objectives. The goal is to make the model more controlled and tailored to the task or context at hand. This process is essential because ChatGPT, being a generative language model, can generate responses that may not always align with user expectations or may lack context.
- Specific Instructions: Providing clear and explicit instructions to ChatGPT, specifying the desired output or behavior. This may involve instructing the model to answer questions, summarize text, provide creative writing, or follow a conversation flow.
- Contextual Information: Supplying relevant context to ChatGPT to ensure that it understands the topic or domain and can provide context-aware responses.
- Control Tokens: Using special tokens or flags to guide the model's behavior and generate more controlled outputs, allowing users to fine-tune the responses.
- Constraints: Incorporating constraints to limit the model's response space, reducing the likelihood of generating inappropriate or harmful content.
- Iterative Refinement: Iterating on prompt design and testing to achieve the desired behavior and response quality.