Welcome to the Generative Model InfoGuide. Here you will find information and resources from the Daytona State College library to help you with Generative Model information. Explore the side tabs and if you need more help, please contact one of your Daytona State College librarians!
Text generation is a process that uses algorithms and language models to process input data and generate output text. AI models, such as GPT and Google's PaLM, are trained on large datasets of text to learn patterns, grammar, and contextual information. They use deep learning techniques, specifically neural networks, to understand sentence structure and generate coherent, contextually relevant text. The model predicts the most probable next words or phrases, continuing to generate text until a desired length or condition is met.
Generative AI and Language Learning Models have revolutionized the field of artificial intelligence, transforming the way machines understand, process, and generate human language. These technologies have had a profound impact on various applications, from natural language processing and machine translation to content generation and virtual assistants.
Generative AI refers to a class of machine learning models designed to generate new data that is similar in structure and content to the data they were trained on. These models are capable of creating text, images, or other forms of data from scratch, making them exceptionally versatile tools for various creative and problem-solving tasks.
Language Learning Models, on the other hand, are a specific category of generative AI models that are primarily focused on understanding and generating human language. These models have the ability to comprehend the nuances of grammar, semantics, and context, enabling them to produce coherent and contextually relevant text. Language learning models have been instrumental in tasks such as text generation, sentiment analysis, language translation, and more.
One of the most notable advancements in this field is the development of large-scale deep learning models, such as GPT (Generative Pre-trained Transformer) and BERT (Bidirectional Encoder Representations from Transformers). These models have achieved remarkable results by pre-training on vast amounts of text data and fine-tuning for specific language tasks. They can answer questions, complete sentences, and even create human-like text, pushing the boundaries of what machines can do with natural language.
Generative AI and Language Learning Models have opened the doors to a wide range of applications across industries, from automating customer support with chatbots to aiding content creators in generating written material more efficiently. As these models continue to evolve and improve, they hold the potential to further enhance our interactions with technology, making it more intuitive and responsive to human language and ultimately shaping the future of AI.
The process of creating written content by an AI system that mimics the linguistic patterns and styles of humans is called text generation. The procedure entails writing relevant, cogent language that mimics casual human conversation. Text generation has become more important in several domains, such as content production, code support, natural language processing, and customer service.
Reproduced in full from the Student Handbook:
Daytona State College is committed to providing students with quality instruction, guidance, and opportunities for academic and career success by fostering academic excellence in a supportive and personalized learning environment.
Maintaining high standards of academic honesty and integrity in higher education is a shared responsibility and an excellent foundation for assisting you in making honorable and ethical contributions to the profession for which you are preparing.
To preserve academic excellence and integrity, the College expects you to know, understand and comply with the Academic Integrity Policy, which prohibits academic dishonesty in any form, including, but not limited to, cheating and plagiarism. Grades conferred by instructors are intended to be accurate and true reflections of the coursework produced and submitted by you.
Unless otherwise explicitly instructed, students are not allowed to use any alternative/Artificial Intelligence (AI) generation tool (including, but not limited to, Chat GPT) for any type of submission or assessment.
Faculty reserve the right to use Artificial Intelligence (AI) detection software to find instances of AI-generated writing in student submissions.
Suspected violations of the student academic dishonesty code will be handled by individual instructors as outlined in their course syllabus. An instructor who finds that a student has violated Academic Integrity may apply an academic consequence ranging from a zero for the assignment, up to and including failure for the entire course.
Instructors are encouraged to report cases of academic integrity violations to their academic department chairperson and to the Office of Judicial Affairs to help track habitual violations of academic integrity and for review and possible additional academic consequences.
In addition, some students may be referred to the student disciplinary process for appropriate disciplinary resolution.
AI (Artificial Intelligence) "is the science and engineering of making intelligent machines, especially intelligent computer programs. It is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to methods that are biologically observable." (McCarthy, n.d.)
The intelligence of created systems and algorithms is typically compared to human intelligence. Sometimes, LLMs and ML products can appear to have human intelligence, but it is simply the product of coding, not actual intelligence.
ML (Machine Learning) is "algorithms that give computers the ability to learn from data, and then make predictions and decisions". Examples include automatically detecting spam emails, suggesting videos to watch after finishing one, etc. (CrashCourse, 2017)
LLMs (Large Language Models) "can generate natural language texts from large amounts of data. Large language models use deep neural networks, such as transformers, to learn from billions or trillions of words, and to produce texts on any topic or domain. Large language models can also perform various natural language tasks, such as classification, summarization, translation, generation, and dialogue." (Maeda & Chaki, 2023)
GPT (Generative Pre-trained Transformer) "models give applications the ability to create human-like text and content (images, music, and more), and answer questions in a conversational manner." (What Is GPT AI?, n.d.)