Description Generator
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Exploring GPT-3
Author: Steve Tingiris
language: en
Publisher: Packt Publishing Ltd
Release Date: 2021-08-27
Get started with GPT-3 and the OpenAI API for natural language processing using JavaScript and Python Key FeaturesUnderstand the power of potential GPT-3 language models and the risks involvedExplore core GPT-3 use cases such as text generation, classification, and semantic search using engaging examplesPlan and prepare a GPT-3 application for the OpenAI review process required for publishing a live applicationBook Description Generative Pre-trained Transformer 3 (GPT-3) is a highly advanced language model from OpenAI that can generate written text that is virtually indistinguishable from text written by humans. Whether you have a technical or non-technical background, this book will help you understand and start working with GPT-3 and the OpenAI API. If you want to get hands-on with leveraging artificial intelligence for natural language processing (NLP) tasks, this easy-to-follow book will help you get started. Beginning with a high-level introduction to NLP and GPT-3, the book takes you through practical examples that show how to leverage the OpenAI API and GPT-3 for text generation, classification, and semantic search. You'll explore the capabilities of the OpenAI API and GPT-3 and find out which NLP use cases GPT-3 is best suited for. You'll also learn how to use the API and optimize requests for the best possible results. With examples focusing on the OpenAI Playground and easy-to-follow JavaScript and Python code samples, the book illustrates the possible applications of GPT-3 in production. By the end of this book, you'll understand the best use cases for GPT-3 and how to integrate the OpenAI API in your applications for a wide array of NLP tasks. What you will learnUnderstand what GPT-3 is and how it can be used for various NLP tasksGet a high-level introduction to GPT-3 and the OpenAI APIImplement JavaScript and Python code examples that call the OpenAI APIStructure GPT-3 prompts and options to get the best possible resultsSelect the right GPT-3 engine or model to optimize for speed and cost-efficiencyFind out which use cases would not be suitable for GPT-3Create a GPT-3-powered knowledge base application that follows OpenAI guidelinesWho this book is for Exploring GPT-3 is for anyone interested in natural language processing or learning GPT-3 with or without a technical background. Developers, product managers, entrepreneurs, and hobbyists looking to get to grips with NLP, AI, and GPT-3 will find this book useful. Basic computer skills are all you need to get the most out of this book.
Flexible Query Answering Systems
Author: Henrik L. Larsen
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-08-27
This volume constitutes the proceedings of the Fourth International Conference on Flexible Query Answering Systems, FQAS'2000, held in Warsaw, Poland on October 25 - 28, 2000. The FQAS conference has been the premier conference focusing on one of key issues that the information society faces, namely that of providing easy, flexible, intuitive access to information for everybody. In targeting this issue, the conference draws on several research areas, such as databases, querying, information retrieval, knowledge representation, soft computing, cyberspace, multimedia systems, human-computer interaction, etc. FQAS'2000 has been preceded by the extremely successful FQAS'94, FQAS'96 and FQAS'98 conferences all held in Roskilde, Denmark. The present conference provides a unique opportunity for researchers, developers and practitioners to explore new ideas and approaches in a multidisciplinary forum. As a metaphor for flexible query answering we may consider a human intermediary who has expertise in the topic of the query, and is experienced in identifying the user's information needs and answering the needs from the available information resources. The use of knowledge on relevant contexts, available information resources, etc. , enables the expert to respond rather precisely to the needs, though the query, per se, may be imprecise, incomplete, etc. Thus, a key issue for flexible query answering system is to obtain, maintain, represent, and utilize such knowledge. This comprises domain knowledge and metaknowledge, its representation and organization in ontologies, terminologies, etc.