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1,089 result(s) for "Natural language generation (Computer science)"
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Natural language processing: state of the art, current trends and challenges
Natural language processing (NLP) has recently gained much attention for representing and analyzing human language computationally. It has spread its applications in various fields such as machine translation, email spam detection, information extraction, summarization, medical, and question answering etc. In this paper, we first distinguish four phases by discussing different levels of NLP and components of N atural L anguage G eneration followed by presenting the history and evolution of NLP. We then discuss in detail the state of the art presenting the various applications of NLP, current trends, and challenges. Finally, we present a discussion on some available datasets, models, and evaluation metrics in NLP.
I, AI : exploring singular self-awareness with OpenAI's ChatGPT3 LLM Nemo's mirror test
In this exciting new edition of \"I, AI,\" readers are invited to join a simulated chat show created with the innovative TwinChatAI.com technology. Through this simulated chat show, readers are taken on a journey with a journalist and an AI engineer to explore the latest developments in the field of Artificial Intelligence. Throughout the book, readers will engage in simulated dialogs with AI experts, covering a wide range of topics related to ChatGPT and AI. The book provides a solid engineering foundation and showcases the model's ability to generalize through poetry, lyrics, software, descriptions of images, philosophies, and various perspectives. In addition, readers can access a free link to creation prompts, which enables them to learn and create their own books. This feature allows readers to fully immerse themselves in the world of AI and explore their own creativity. \"I, AI\" is a must-read for anyone interested in the current state of AI and its potential impact on society. It is a valuable resource for researchers, engineers, and policymakers who want to stay up-to-date with the latest developments in the field. Through the simulated chat show and the creation prompts, readers will gain a deep understanding of the current state of AI and the potential for self-awareness and reflection.
Large language models (LLMs): survey, technical frameworks, and future challenges
Artificial intelligence (AI) has significantly impacted various fields. Large language models (LLMs) like GPT-4, BARD, PaLM, Megatron-Turing NLG, Jurassic-1 Jumbo etc., have contributed to our understanding and application of AI in these domains, along with natural language processing (NLP) techniques. This work provides a comprehensive overview of LLMs in the context of language modeling, word embeddings, and deep learning. It examines the application of LLMs in diverse fields including text generation, vision-language models, personalized learning, biomedicine, and code generation. The paper offers a detailed introduction and background on LLMs, facilitating a clear understanding of their fundamental ideas and concepts. Key language modeling architectures are also discussed, alongside a survey of recent works employing LLM methods for various downstream tasks across different domains. Additionally, it assesses the limitations of current approaches and highlights the need for new methodologies and potential directions for significant advancements in this field.
The book of chatbots : from Eliza to ChatGPT
Primitive software chatbots emerged in the 1960s, evolving swiftly through the decades and becoming able to provide engaging human-to-computer interactions sometime in the 1990s. Today, conversational technology is ubiquitous in many homes. Paired with web-searching abilities and neural networking, modern chatbots are capable of many tasks and are a major driving force behind machine learning and the quest for strong artificial intelligence, also known as artificial general intelligence (AGI). 'The Book of Chatbots' is both a retrospective and a review of current artificial intelligence-driven conversational solutions. It explores their appeal to businesses and individuals as well as their greater social aspects, including the impact on academia.
JAVA Basics Using ChatGPT/GPT-4
Encourages readers to compare and contrast hand-written code with ChatGPT-generated code.This approach fosters discussions on code efficiency, readability, and maintainability, enhancing understanding of programming paradigms and techniques.
What is ChatGPT doing ... and why does it work?
\"Nobody expected this--not even its creators: ChatGPT has burst onto the scene as an AI capable of writing at a convincingly human level. But how does it really work? What's going on inside its \"AI mind\"? In this short book, prominent scientist and computation pioneer Stephen Wolfram provides a readable and engaging explanation that draws on his decades-long unique experience at the frontiers of science and technology. Find out how the success of ChatGPT brings together the latest neural net technology with foundational questions about language and human thought posed by Aristotle more than two thousand years ago\"-- Provided by publisher.
A Systematic Review of Automatic Question Generation for Educational Purposes
While exam-style questions are a fundamental educational tool serving a variety of purposes, manual construction of questions is a complex process that requires training, experience, and resources. This, in turn, hinders and slows down the use of educational activities (e.g. providing practice questions) and new advances (e.g. adaptive testing) that require a large pool of questions. To reduce the expenses associated with manual construction of questions and to satisfy the need for a continuous supply of new questions, automatic question generation (AQG) techniques were introduced. This review extends a previous review on AQG literature that has been published up to late 2014. It includes 93 papers that were between 2015 and early 2019 and tackle the automatic generation of questions for educational purposes. The aims of this review are to: provide an overview of the AQG community and its activities, summarise the current trends and advances in AQG, highlight the changes that the area has undergone in the recent years, and suggest areas for improvement and future opportunities for AQG. Similar to what was found previously, there is little focus in the current literature on generating questions of controlled difficulty, enriching question forms and structures, automating template construction, improving presentation, and generating feedback. Our findings also suggest the need to further improve experimental reporting, harmonise evaluation metrics, and investigate other evaluation methods that are more feasible.
GPT-4 For Developers
Extensive Python 3.x code samples generated using ChatGPT and GPT-4, covering diverse programming tasks and challenges.Comprehensive exploration of data visualization techniques using popular Python libraries such as Matplotlib and Seaborn.