Navigating the text generation revolution: Traditional data-to-text NLG companies and the rise of ChatGPT

IF 2.3 3区计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Natural Language Engineering Pub Date : 2023-07-01 DOI:10.1017/S1351324923000347

R. Dale

引用次数: 0

Abstract

Abstract Since the release of ChatGPT at the end of November 2022, generative AI has been talked about endlessly in both the technical press and the mainstream media. Large language model technology has been heralded as many things: the disruption of the search engine, the end of the student essay, the bringer of disinformation … but what does it mean for commercial providers of earlier iterations of natural language generation technology? We look at how the major players in the space are responding, and where things might go in the future.

查看原文本刊更多论文

引导文本生成革命:传统的数据到文本的NLG公司和ChatGPT的兴起

摘要自2022年11月底ChatGPT发布以来，生成人工智能在技术媒体和主流媒体上一直被谈论不休。大型语言模型技术被认为有很多东西：搜索引擎的破坏、学生论文的结束、虚假信息的传播……但这对自然语言生成技术早期迭代的商业提供商意味着什么？我们来看看太空中的主要参与者是如何应对的，以及未来的发展方向。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Natural Language Engineering COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-

CiteScore

5.90

自引率

12.00%

发文量

审稿时长

>12 weeks

期刊介绍： Natural Language Engineering meets the needs of professionals and researchers working in all areas of computerised language processing, whether from the perspective of theoretical or descriptive linguistics, lexicology, computer science or engineering. Its aim is to bridge the gap between traditional computational linguistics research and the implementation of practical applications with potential real-world use. As well as publishing research articles on a broad range of topics - from text analysis, machine translation, information retrieval and speech analysis and generation to integrated systems and multi modal interfaces - it also publishes special issues on specific areas and technologies within these topics, an industry watch column and book reviews.