Daniella Dorio, Consultant
As technology continually pushes the boundaries of human ingenuity, conversational AI has emerged as a fascinating and transformative force. These natural language processing (NLP) advancements, like ChatGPT, have revolutionized the way we interact with virtual assistants. This article explores Generative Pre-Trained Transformer (GPT) 4 architecture, prompt engineering, potential uses, and limitations.
GPT 4 Architecture
Conversational AI has become a highly sought-after component of human-computer interaction, with language models playing a crucial role in this development. NLP has undergone significant advancements with the emergence of large language models (LLM).(1) These advancements gave way to ChatGPT’s model version GPT 4 architectures, employed on an unprecedented and disruptive scale of 175 billion parameters.(2) Given the speed and scale of AI technological advancements, there is evidently a monumental shift in human-computer interaction.
Developed on November 30, 2022, by OpenAI, ChatGPT is a groundbreaking advanced language model capable of generating responses remarkably similar to those of human conversations.(3) The “GPT” in ChatGPT stands for Generative Pre-trained Transformer, a type of neural network that learns context and can perform data analytics, typically on language data.(4) GPTs are “generative” because they can create new data and are “pre-trained” because they leverage existing models instead of creating new ones.
Prompt Engineering
To optimally use conversational AI, such as ChatGPT, it is important to understand prompt engineering. Prompt engineering is the process of describing a task that a user wants an AI chatbot to accomplish.(5) By understanding how AI processes the query, a prompt engineer can manipulate responses to achieve the intended results. For example, if an AI bot is asked “what is the weather,” the results can widely vary from indoor and outdoor temperatures, location, and any additional desired information, such as humidity or air quality. By refining the prompt to “what is the outdoor temperature, humidity, and air quality in Washington, DC” the chatbot can more accurately respond with the requested information.
ChatGPT Potential Uses
- Simplify Complex Ideas
Subject matter experts must simplify their technically robust findings into digestible, easy-to-understand topics. For example, if a client is working with AI and does not understand what LLMs are, they can ask ChatGPT to “explain what a large language model is, at a high-level.” Or they can ask ChatGPT to “rewrite this sentence to remove unnecessary jargon” to provide concise explanations. - Code Composition Development
ChatGPT can additionally be applied as a code composition resource. Users can instruct ChatGPT to write code in specific languages by inputting, “write code to concatenate Employee and Salary data tables in Python,” for example. ChatGPT should be used as a supplementary resource similar to developers leveraging Stack Overflow to ask coding questions and investigate syntax best practices. - Résumé Review and Evaluation
ChatGPT can write, edit, and read résumés, making the AI chatbot an invaluable resource for recruiting staff. ChatGPT can assist with content analysis, keyword matching, and overall impressions of the applicant’s résumé. To optimize ChatGPT for résumé evaluation, recruiters and users should consider uploading the job description, sample résumés, and other materials to maximize context and relevance.
Limitations
With every new technology, there are always areas of potential improvement. While ChatGPT provides powerful conversational capabilities, users should also be mindful of its limitations and exercise caution to relying solely on its responses, especially in sensitive domains. Limitations include virtual assistants’ lack of contextual understanding, sensitivity to prompt engineering, and ethical and legal considerations.
Conclusion
The emergence of conversational AI has heralded a new era in human-computer interaction, transcending the boundaries of what was once thought possible. As technology continues to advance, AI’s capacity to comprehend and engage in meaningful conversations with users has become increasingly sophisticated. Language models’ wide-ranging applications make it a powerful tool for democratizing AI technology for average consumers. However, addressing ethical and legal considerations is critical to effectively harness AI’s full potential while ensuring its responsible integration into our lives.
Sources
(1) What is Natural Language Processing? | IBM
(2) Introducing ChatGPT (openai.com)
(3) ChatGPT — Release Notes | OpenAI Help Center
(4) The A to Z of Artificial Intelligence | Time
(5) What is prompt engineering? Definition + skills | Zapier
ChatGPT | OpenAI
How to Get a Six-Figure Job as an AI Prompt Engineer | Time
How to write an effective GPT-3 or GPT-4 prompt | Zapier